We recommend viewing this document with the latest version of your PDF reader.Japan Automobile Manufacturers Association,Inc.Taxes on AutomobilesThe Burden on Motor Vehicle UsersTax Incentive Measures.Climate ChangeVehicle Fuel EfficiencyAlternative Fuel Vehicles and CO2 Reductions at Manufacturers FacilitiesHazardous SubstancesRecyclingEmissionsMeasuring Motor Vehicle Fuel Consumption and Emissions233PageAutomobile Manufacturing:A Core IndustryMotor VehiclesAutomotive Shipments in Value TermsAutomotive TradeAutomobile-Related Industries and Total Employment4566789.ProductionNew RegistrationsImported Vehicle SalesUsed Vehicle SalesMotor Vehicles in Use and Motor Vehicle DensityExportsExports by DestinationMotorcycles1010111112ProductionSalesMotorcycles in UseExportsExports by DestinationRoad Safety131314Road SafetyVehicle Safety Features and SystemsAutomated Driving.15151616171818Attention to the Environment192020Taxes2323Vehicle-Based SystemsDrivers Licenses and the Driving PopulationMotor Vehicle Classification242525Global OperationsOverseas ProductionOverseas Production VolumesGlobal Industry Ties2728292930Motor Vehicles WorldwideGlobal ProductionNew RegistrationsMotor Vehicles&Motorcycles in Use/Motor Vehicle&Motorcycle DensityExportsCustoms Tariffs,EPAs-FTAs31323333Japan Mobility Show(formerly the Tokyo Motor Show)JAMA Member ManufacturersLocations of Auto Manufacturing PlantsRelated Automotive Associations.Contents.THE MOTOR INDUSTRY OF JAPAN 2024.Machinery IndustriesAutomotive ShipmentsAutomotiveChemicalsIron&SteelNon-FerrousMetalsMetalProductsGeneralMachineryElectricalMachinery&EquipmentSubtotalOtherTotalAs%of Value of Machinery ShipmentsAs%of Total Value of Manufacturing ShipmentsTransport EquipmentNotes:1.Data through 2020 includes shipments from all manufacturing operations with four or more employees.2.Compilation of data on production in value terms was discontinued in 1996 and replaced by data on shipments in value terms.3.Figures in value terms include domestic consumption tax revenue from shipments.4.“Electrical Machinery&Equipment”includes IT-related electronic parts and equipment as of 2002.SHIPMENTS OF MAJOR MANUFACTURING SECTORS IN VALUE TERMS,1970-2022x 100 million yenYear SHIPMENTS OF MAJOR MANUFACTURING SECTORS IN VALUE TERMS(2022)x 100 million yenAutomotive627,942(17.4%)GeneralMachinery448,015(12.4%)Other1,134,073(31.3%)ElectricalMachinery&Equipment445,372(12.3%)TransportEquipment705,284(19.5%)Chemicals342,810(9.5%)Iron&Steel239,410(6.6%)Metal Products169,199(4.7%)Non-FerrousMetals133,586(3.7%)Breakdown of automotive shipments:Automobiles(including motorcycles).249,851 Auto bodies and trailers.8,318 Automotive parts and accessories.369,773Total3,617,749(100%)Automotive Shipments Total 63 Trillion Yen;Equipment Investments,1.5 Trillion Yen;R&D Expenditures,3.9 Trillion YenNote:Japans fiscal year(FY)starts on April 1 and ends on March 31 of the following year.INVESTMENTS IN EQUIPMENT OF MAJOR MANUFACTURING SECTORS(FY 2023)x 100 million yenAutomotive shipments(both domestic and export shipments,including motorcycles,auto parts,etc.)in value terms reached 62.8 trillion yen in 2022,up 11.4%from the previous year,accounting for 17.4%of the total value of Japans manufacturing shipments and 39.3%of the value of the machinery industries combined shipments.Investments in equipment by the automobile industry in 2023 totalled 1.5 trillion yen and its research and development expenditures stood at 3.9 trillion yen in 2022;those figures represent roughly 20%and 30%,respectively,of the value of overall investments of Japans major manufacturing sectors.With motor vehicle exports in value terms amounting to 21.6 trillion yen in 2023 and auto-related employment in Japan totalling 5.58 million people,the automotive industry is one of the Japanese economys core industrial sectors.Automobile Manufacturing:A Core IndustryAutomotive Shipments in Value TermsTransportEquipment15,756(26.2%)Other8,760(14.6%)Petroleum1,668(2.8%)Chemicals11,163(18.5%)Paper&Pulp1,253(2.1%)Iron&Steel3,745(6.2%)GeneralMachinery5,868(9.7%)ElectricalMachinery7,626(12.7%)Automotive15,333(25.5%)Total60,204(100%)INVESTMENTS IN EQUIPMENT OF MAJOR MANUFACTURING SECTORS,2014-2023x 100 million yen07,00014,00021,0002014Fiscal year2023201520162017201820192020202120222013201420152016201720182019202020212022AutomotiveIT&Telecommunications EquipmentElectronic Circuits,Parts&EquipmentTransport EquipmentPharma-ceuticalsChemicalsGeneral Machinery&EquipmentIron&SteelElectrical Machinery&EquipmentFoodsOtherTotalSource:Survey on Research Activities in Science and Technology,Ministry of Internal Affairs and Communications R&D EXPENDITURES OF MAJOR MANUFACTURING SECTORSx 100 million yenFiscalyearSources for data in above charts:Economic Census for Business Activity,Ministry of Economy,Trade and Industry,Ministry of Internal Affairs and Communications;Census of Manufactures,Ministry of Economy,Trade and IndustryTransport equipmentOtherOtherChemicalsChemicalsIron&steelIron&steelGeneral machineryGeneral machineryPetroleumNon-ferrousmetalsPaper&pulpPaper&pulp COMPARISON OF VALUE OF AUTOMOTIVE SHIPMENTS TO TOTAL VALUE OF ALL MANUFACTURING SHIPMENTS02040608010012014016018020022024026028030032034038056.453.452.0 53.357.1330.262.8 361.8 303.6292.1305.1313.157.860.7302.0319.262.3331.8 60.0322.5360 x 1 trillion yenTotal value of all manufacturing shipmentsTotal value of automotive shipments2013Year2021 20222014 2015 2016 2017 2018 2019 2020197019751980198519901995200020052010201320142015201620172018201920202021202255,402104,381179,787205,524235,030233,625237,994250,271262,120274,092281,230286,222272,496287,242297,880292,528287,305317,082342,81065,648113,063178,956177,543182,687140,727119,630168,964181,463179,053192,022178,420156,693176,867186,520177,476151,183197,188239,41030,54739,08781,18663,83678,21764,96462,18967,11689,11488,05994,22096,79588,89297,620102,29096,14294,527119,507133,58637,27765,731106,465130,944185,736176,465155,868140,159122,920130,606139,328143,057143,986151,989158,217159,653152,036158,811169,19968,028106,112175,998241,904332,249298,844304,132312,108306,186320,911337,273359,715363,611392,279412,807397,686376,065416,717448,01573,305108,213222,346408,422545,286548,309595,817495,083442,848368,283394,772408,060376,748398,955418,426390,650389,109420,761445,37272,758147,935249,536361,793468,582442,145444,474539,999542,136582,032600,633646,539649,912682,635700,906679,938602,308631,198705,28454,673105,241212,346276,927423,106395,613400,429489,548472,962519,710533,101570,524577,604606,999623,040600,154534,472563,679627,94224.527.731.126.230.329.728.935.336.640.940.040.341.541.240.740.939.138.439.37.98.39.910.413.112.913.216.516.417.817.518.219.119.018.818.617.617.117.4223,008379,551682,4571,055,9321,397,4391,330,3641,385,6121,385,0371,291,1701,271,2261,332,6781,414,3141,390,2711,473,8691,532,1391,468,2741,367,4821,468,6761,598,671287,383589,807952,7241,063,2401,205,9391,155,2771,115,720988,717944,290977,8851,011,9221,012,477968,0181,004,0801,041,0481,031,261983,0141,040,9361,134,073690,3481,274,3292,146,9982,653,2063,233,7263,060,3563,035,8242,962,4172,891,0772,920,9213,051,4003,131,2853,020,3563,191,6673,318,0943,225,3343,035,5473,302,2003,617,749Non-FerrousMetals4,365(7.3%)Electrical machineryElectrical machinery2014201520162017201820192020202120222023AutomotivePaper&PulpChemicalsPetroleumIron&SteelNon-Ferrous MetalsGeneral MachineryElectrical MachineryTransport EquipmentTotalOtherSource:Survey on Planned Capital Spending,Development Bank of Japan INVESTMENTS IN EQUIPMENT OF MAJOR MANUFACTURING SECTORSx 100 million yenFiscal year1,3721,2741,2521,2831,6721,6021,4891,4691,3521,2537,8018,1009,0369,15211,56511,70211,32010,37212,11511,1632,8412,3702,1562,2152,3992,4972,4842,0622,4071,6685,7995,5657,0555,1334,8774,4353,7113,6663,4423,7451,7631,8071,7752,2192,4592,5461,6112,2892,8474,3656,1007,3677,7027,7278,9996,8025,7155,6066,8405,8688,9208,2855,9336,1496,7084,9344,5945,1386,4247,62612,24413,92814,38713,59516,09614,38612,80814,28914,64715,75611,19913,02113,30612,90215,34913,80312,25213,94014,19715,33356,82058,19659,83358,25566,16259,69652,48653,78559,50160,2049,9809,50010,53710,78211,38710,7928,7548,89410,7798,76016,70816,23815,47613,57213,37411,86311,93011,51810,2268,2905,9986,1816,0936,0756,4278,5238,06711,55710,96412,31124,97228,44729,52929,25530,64630,62831,79138,79636,85240,11814,37114,95314,57713,51614,65314,04713,39213,21613,98614,3047,5197,5348,1668,4948,5258,3699,5299,7649,4319,55518,02718,44019,00519,04719,18020,61519,11016,37116,37217,9471,3921,5011,5521,5771,5981,5471,6551,5471,2321,23610,72411,18911,56911,21111,25512,66013,1828,1358,3779,3202,3372,0972,1952,2672,7532,6862,9642,7642,8842,47810,56710,97110,47910,73411,40712,21312,09310,89811,78412,524112,615117,551118,641115,748119,818123,151123,713124,566122,108128,08324,13727,49528,37228,07129,29629,31730,60037,16435,76839,194Automotive R&D EXPENDITURES OF MAJOR MANUFACTURING SECTORS(FY 2022)x 100 million yen R&D EXPENDITURES OF MAJOR MANUFACTURING SECTORS,2013-20222013Fiscal year202220142015201620172018201920202021010,00030,00020,00040,000AutomotiveTransport equipmentGeneral machinery&equipmentPharmaceuticalsChemicalsElectronic circuits,parts&equipmentFoodsIT&telecommunications equipmentIT&telecommunications equipmentChemicalsElectrical machinery&equipmentElectrical machinery&equipmentElectrical machinery&equipmentChemicalsElectronic circuits,parts&equipmentIron&steelIT&TelecommunicationsEquipment8,290(6.5%)Other12,524(9.6%)Foods2,478(1.9%)ElectricalMachinery&Equipment9,320(7.3%)General Machinery&Equipment17,947(14.0%)Iron&Steel1,236(1.0%)ElectronicCircuits,Parts&Equipment12,311(9.6%)Pharmaceuticals14,304(11.2%)Chemicals9,555(7.5%)Total128,083(100%)Automotive39,194(30.6%)TransportEquipment40,118(31.3%)x 100 million yenElectronic circuits,parts&equipmentOther2Notes:1.“Passenger Cars,Trucks,Buses”includes chassis.2.FOB:Free on board;CIF:Cost,insurance,and freight.3.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Source for all statistical data on this page:The Summary Report on Trade of Japan(2023),Japan Tariff Association20132014201520162017201820192020202120222023Motor VehiclesExports TotalPassenger Cars,Trucks,BusesAuto PartsMotorcycles&Motorcycle PartsChg.(%)Chg.(%)Year142,411147,849158,912151,175161,092166,972159,052127,738147,099172,743216,409111.7103.8107.595.1106.6103.795.380.3115.2117.4125.3104,125109,194120,463113,329118,254123,072119,71295,796107,222130,117172,65434,76234,75034,83034,61738,96639,90936,01729,12436,00038,48338,8363,5243,9053,6193,2293,8723,9903,3242,8183,8764,1434,918697,742730,930756,139700,358782,865814,788769,317683,991830,914981,7361,008,738109.5104.8103.492.6111.8104.194.488.9121.5118.2102.8 AUTOMOTIVE EXPORTS IN VALUE TERMS(FOB)x 100 million yen20132014201520162017201820192020202120222023Motor VehiclesImports TotalPassenger Cars,Trucks,BusesAuto PartsMotorcycles&Motorcycle PartsChg.(%)Chg.(%)Year AUTOMOTIVE IMPORTS IN VALUE TERMS(CIF)x 100 million yen EXPORTS BY PRINCIPAL COMMODITY(FOB)IN 2023x 10 billion yenMotor Vehicles(including motorcycles and parts)2,164(21.5%)Transport Equipment2,363(23.4%)Scientific&OpticalEquipment250(2.5%)Other1,946(19.3%)Chemicals1,102(10.9%)Non-FerrousMetals&Metal Products377(3.7%)Textile Yarn&Textiles79(0.8%)GeneralMachinery1,845(18.3%)ElectricalMachinery&Equipment1,675(16.6%)In Value Terms,Motor Vehicle Exports Total 21.6 Trillion Yen;Motor Vehicle Imports Total 3.3 Trillion YenIn 2023 Japans gross exports increased 2.8%from the previous year,whereas imports decreased 7.0%.In value terms,automotive exports rose 25.3%from 2022 to 21.6 trillion yen and imports grew 22.4%year-on-year to 3.3 trillion yen.EMPLOYMENT IN THE AUTOMOBILE MANUFACTURING AND AUTO-RELATED INDUSTRIESAuto-Related Employment Totals 5.58 Million PeopleAutomobiles are the focus of an extremely wide range of industrial and related activity,from materials supply and vehicle production to sales,servicing,freight shipping and other auto-centered operations.Auto-related employment in Japan at present totals 5.58 million people.Number of employeesTotal employment in auto manufacturing&auto-related industries:5.58 million(8.3%)Automobile Production.883,000 Automobile manufacturing(including motorcycles)Auto parts and accessories manufacturing Auto body and trailer manufacturing.190,000.668,000.25,000Road Transport.2,793,000 Road freight transport Road passenger transport Road transport-related services Vehicle rental services Postal activities.1,777,000.476,000.387,000.50,000.103,000Automotive Fuel/Insurance/Recycling.368,000 Automotive fuel retailing Auto damage insurance Automobile recycling Automobile parking.294,000.7,900.1,700.64,000Materials&Equipment Supply.534,000 Electrical machinery&equipment Non-ferrous metals Iron&steel Metal products Chemicals(including paints),textiles,and petroleum Plastics,rubber,and glass Electronic parts&equipment Manufacturing machinery Information services.98,000.19,000.107,000.40,000.34,000.160,000.35,000.5,000.36,000Sales&Services.1,009,000 Automobile retailing(including motorcycles,used vehicles,and auto parts and accessories)Automobile wholesaling(including motorcycles,used vehicles,and finished/used parts and accessories)Automobile servicing .568,000.221,000.220,000Note:Figures are rounded off to the nearest thousand.Sources:Labor Force Survey(2023 Annual Average),Ministry of Internal Affairs and Communications Statistics Bureau;Economic Census for Business Activity,Ministry of Economy,Trade and Industry,Ministry of Internal Affairs and Communications;Census of Manufactures,2020 Input-Output Tables for Japan,Ministry of Economy,Trade and IndustryIron&SteelProducts 450(4.5%)IMPORTS BY PRINCIPAL COMMODITY(CIF)IN 2023x 10 billion yenTransport Equipment413(3.8%)Other1,918(17.4%)Foodstuffs934(8.5%)Raw Materials719(6.5%)Mineral Fuels2,733(24.8%)Petroleum&Petroleum Products1,402(12.7%)Chemicals1,155(10.5%)Non-Ferrous Metals&Metal Products406(3.7%)GeneralMachinery959(8.7%)ElectricalMachinery&Equipment1,782(16.2%)Motor Vehicles(including motorcycles and parts)329(3.0%)Automobile Manufacturing:A Core IndustryAutomotive TradeAutomobile Manufacturing:A Core IndustryAutomobile-Related Industries and Total EmploymentTotal10,087(100%)Total11,020(100%)18,94820,92521,26121,02323,41925,22324,02019,51323,48526,89732,924122.2110.4101.698.9111.4107.795.281.2120.4114.5122.410,85711,62311,39811,78113,07014,28414,08411,65313,71815,12319,0746,9818,1488,7708,3299,3289,8618,9066,7478,25210,02211,8371,1091,1541,0939131,0211,0791,0301,1131,5141,7522,013812,425859,091784,055660,420753,792827,033785,995680,108848,7501,185,0321,101,956114.9 105.7 91.3 84.2114.1109.795.086.5124.8139.693.0Total employment(workforce)in Japan:67.47 million(100%)3 MOTOR VEHICLE PRODUCTION TRENDS IN MOTOR VEHICLE PRODUCTIONSource:Ministry of Economy,Trade and Industry MOTOR VEHICLE PRODUCTION IN VALUE TERMSTotalPassenger CarsTrucks&Busesx 1 million units MOTOR VEHICLE PRODUCTION BY TYPE IN 2023In vehicle unitsMotor Vehicle Production Totals 9 Million UnitsTrucks1,127,470(12.5%)Standard492,823(5.5%)Buses104,010(1.2%)Motor VehiclesProductionx 1 million yen TRENDS IN MOTOR VEHICLE PRODUCTION IN VALUE TERMS x 1 trillion yen In vehicle units024681012142014Year202320152016201720182019202020212022TotalPassenger CarsTrucks&BusesBusesTrucksLargeSubtotalSubtotalTractorsMiniSmallStandardMiniSmallStandardYearSmallSubtotalPassenger CarsTotal8,998,538(100%)Standard5,027,107(55.9%)Small1,330,329(14.8%)Mini1,409,622(15.7%)Mini401,802(4.5%)Small232,845(2.6%)Passenger Cars7,767,058(86.3%)Notes:1.Passenger cars and trucks are classified under Japans Road Vehicles Act in three categories,based primarily on engine capacity:“standard”(over 2,000cc),“small”(661cc-2,000cc),and“mini”(660cc and under);see page 23 for details.2.KD sets have been excluded since 1979;they represent less than 60%of the cost of compositional components per vehicle and have been treated as components since 1988.3.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).TotalSources:Japan Automobile Manufacturers Association;Current Survey of Production,Ministry of Economy,Trade and Industry1985199019952000200520102014201520162017201820192020202120222023Passenger Cars1970197519801985199019952000200520102014201520162017201820192020202120222023TrucksBusesTotal1970197519801985199019952000200520102014201520162017201820192020202120222023SmallStandardSubtotalChg.(%)Chg.(%)Chg.(%)Chg.(%)YearMiniSmallStandardYearMiniSubtotalIn 2023 motor vehicle production in Japan stood at 8.99 million units,up 14.8%from 2022,registering an increase for the first time in five years.Passenger car production jumped 18.3%to a total of 7.77 million units,with standard cars surging 23.7%to 5.03 million units,small cars growing 10.7%to 1.33 million units,and minicars rising 8.3%to 1.41 million units.Meanwhile,truck production decreased 4.8%from the previous year to 1.13 million units whereas bus production climbed 22.9%to 104,000 units.1,253,8611,610,4752,113,3111,877,8931,262,943909,321483,282436,763238,776327,928330,814317,182292,901306,259293,002254,310261,715238,561 232,845 258,100288,170885,1981,278,2121,249,525824,140649,180723,663520,627604,768586,645505,970515,521517,641506,390405,451516,988512,809 492,823 121.7116.2114.0108.1109.997.5103.2103.4121.1101.194.6100.6106.0100.199.683.695.199.2 118.3 3,178,7084,567,8547,038,1087,646,8169,947,9727,610,5338,359,4349,016,7358,310,3628,277,0707,830,7227,873,8868,347,8368,359,2868,328,7566,960,4096,619,202 6,566,318 7,767,058 749,450160,272195,923160,592835,965916,2011,283,0941,408,7531,304,8321,868,4101,530,7031,263,8341,484,6101,497,8981,473,2111,357,6481,284,2871,301,090 1,409,622 2,377,6394,198,5506,438,8476,991,4327,361,2244,140,6293,699,8933,416,6222,159,1191,750,8951,555,5481,610,4861,715,9701,605,1621,538,3801,409,9941,169,2841,201,978 1,330,329 551,922438,987914,6791,388,583986,171804,276594,356546,185449,776425,065392,290377,921411,319433,211433,525377,970375,351433,183 401,802 2,063,8832,337,6323,913,1884,544,6883,498,6392,537,7371,726,8181,706,6111,209,1791,357,7611,309,7491,201,0731,219,7411,257,1111,232,9171,037,7311,154,0541,184,553 1,127,470 102.190.8115.2105.289.093.998.898.6122.7103.896.591.7101.6103.198.184.2111.2102.695.246,56636,10591,58879,59140,18547,26654,54476,313109,334139,834137,850129,743123,097113,197122,62169,80173,65984,611104,010111.378.8146.4110.295.596.2112.7126.3126.0105.498.694.194.992.0108.356.9105.5114.9122.95,289,1576,941,59111,042,88412,271,09513,486,79610,195,53610,140,79610,799,6599,628,8759,774,6659,278,3219,204,7029,690,6749,729,5949,684,2948,067,9417,846,915 7,835,482 8,998,538 113.1105.9114.6107.0103.596.6102.5102.7121.4101.594.999.2105.3100.499.583.397.399.9114.851,619209,032403,338494,7921,750,7832,553,7033,376,4474,191,3604,846,4114,657,7654,744,4714,999,5665,147,2565,256,2265,317,1654,192,7674,165,6314,063,2505,027,1070510152025302014Year20232015201620172018201920202021202212,273,52616,957,27114,108,73714,424,13817,958,82916,828,56019,152,17519,643,50719,390,06820,426,51820,792,21320,845,953 17,391,34217,651,73319,287,43825,636,557 204,060201,003197,088189,904290,674329,659442,524468,112472,126463,407413,631428,976238,665185,607226,239 312,048 101,00766,98889,441109,007163,069211,359318,410328,498299,220288,317275,391298,524170,077153,578183,529 244,310 103,053134,015107,64780,897127,605118,300124,114139,614172,906175,090138,240130,45268,58832,02942,71067,738 4,039,1773,790,0093,104,2822,058,1842,967,0982,442,3143,167,2323,196,4452,876,5342,970,7913,066,2173,024,491 2,552,6952,982,7472,975,912 3,083,986 46,74564,913124,76445,453104,56775,944118,091131,002129,781126,867128,658141,002106,908105,48685,67098,169 679,498591,144510,579357,765357,615323,800313,522300,368290,991319,178359,483391,156 344,847346,123462,032435,492 1,519,9341,180,028849,511543,408588,224358,081546,377576,037566,781538,716570,136568,616 492,720514,462458,523 474,698 1,793,0001,953,9241,619,4281,111,5581,916,6921,684,4892,189,2422,189,0381,888,9811,986,0302,007,9401,923,7171,608,2202,016,6761,969,687 2,075,627 8,030,28912,966,25910,807,36712,176,05014,701,05714,056,58715,542,41915,978,95016,041,40816,992,32017,312,36517,392,486 14,599,98214,483,37916,085,287 22,240,523 85,925572,188790,3031,237,6051,169,8711,207,4231,795,4401,473,1031,280,8531,517,7861,545,6871,611,427 1,528,2891,379,2941,468,754 1,706,941 7,049,3238,676,7154,869,4274,298,3704,178,6412,609,8612,636,8722,458,1982,438,9062,516,3792,398,8352,357,894 2,178,4941,799,6351,980,042 2,409,069 895,0413,717,3565,147,6376,640,0759,352,54510,239,30311,110,10712,047,64912,321,64912,958,15513,367,84313,423,165 10,893,19911,304,45012,636,491 18,124,513 4 NEW MOTOR VEHICLE REGISTRATIONS TRENDS IN NEW MOTOR VEHICLE REGISTRATIONSx 1 million units NEW MOTOR VEHICLE REGISTRATIONS BY TYPE IN 2023In vehicle unitsMotor Vehicle Sales Total 4.78 Million UnitsPassenger Cars116.8119.794.0100.3115.9105.6102.599.6107.4103.089.798.4105.8100.197.988.696.593.8115.8 2,379,1372,737,6412,854,1763,104,0835,102,6594,443,9064,259,8724,748,4094,212,2674,699,5914,215,8894,146,4584,386,3774,391,1604,301,0913,809,9813,675,6983,448,2973,992,727 717,170157,120174,030161,017795,948900,3551,281,2651,387,0681,284,6651,839,1191,511,4041,344,9671,443,3671,495,7061,479,2051,331,1491,275,8361,224,9941,341,330 1,652,8992,531,3962,608,2152,869,5273,839,2212,654,2912,208,3872,089,9921,507,6931,422,8831,349,9441,311,2751,394,7961,312,6261,235,5441,108,077953,207877,074893,228 9,06849,12571,93173,539467,490889,260770,2201,271,3491,419,9091,437,5891,354,5411,490,2161,548,2141,582,8281,586,3421,370,7551,446,6551,346,2291,758,169 197019751980198519901995200020052010201420152016201720182019202020212022202310,2568,8189,4148,7989,1626,4754,3335,8564,7774,4985,2606,5436,6025,1314,8763,1131,6571,6612,614 17,57211,01813,97312,77515,76310,82812,23811,8987,9987,4858,1278,9558,9918,5718,7106,2215,223 3,8195,796 27,82819,83623,38721,57324,92517,30316,57117,75412,77511,98313,38715,49815,59313,70213,5869,3346,8805,4808,410 104.287.497.5106.4105.997.0114.597.8101.6106.5111.7115.8100.687.999.268.773.779.7153.5 4,100,4674,308,9315,015,5105,556,8347,777,4936,865,0345,963,0425,852,0674,956,1365,562,8885,046,5104,970,2585,234,1655,272,0675,195,2164,598,6154,448,3404,201,3204,779,086 106.9111.997.3102.2107.2105.2101.7100.0107.5103.590.798.5105.3100.798.588.596.794.4113.8 2,844,5543,720,6304,002,1724,028,1325,975,0895,149,4144,095,1173,928,3513,229,7163,290,0983,150,3103,244,7983,390,8243,347,9433,284,8702,880,5272,795,8182,563,1843,034,167 104.9118.893.1101.3107.4104.8102.799.1110.6100.895.8103.0104.598.798.187.797.191.7118.4 1,255,913588,3011,013,3381,528,7021,802,4041,715,6201,867,9251,923,7161,726,4202,272,7901,896,2001,725,4601,843,3411,924,1241,910,3461,718,0881,652,5221,638,1361,744,919 111.782.1118.3104.8106.3106.299.7101.7102.3107.683.491.0106.8104.499.389.996.299.1106.5 1970197519801985199019952000200520102014201520162017201820192020202120222023Motor VehiclesNew Registrations In vehicle units0123456782014Year202320152016201720182019202020212022TotalPassenger CarsTrucks&Buses NEW MINI-VEHICLE SALES BY TYPEIn vehicle unitsSubtotalChg.(%)YearMiniSmallStandardTrucks95.6100.7102.2104.793.7104.699.6101.8108.6106.296.098.9103.0104.2101.588.598.397.6104.1 1,693,5021,551,4542,137,9472,431,1782,649,9092,403,8251,686,5991,085,904731,094851,314817,234808,302832,195867,205880,539779,300765,762747,543777,949 538,743431,181839,3081,367,6851,006,456815,265586,660536,648441,755433,671384,796380,493399,974428,418431,141386,939376,686413,142403,589 986,673999,1551,144,167945,4841,449,6781,411,2961,015,313351,708187,642252,828259,936254,560255,836258,521267,007231,683231,295211,772230,670 168,086121,118154,472118,009193,775177,26484,626197,548101,697164,815172,502173,249176,385180,266182,391160,678157,781122,629143,690 SubtotalChg.(%)Chg.(%)Chg.(%)Chg.(%)MiniSmallStandardBusesTotalLargeSmallSubtotalYearNotes:1.Chassis-based through 2002,data compilation became vehicle registration number-based as of 2003.2.Truck figures include special-purpose vehicles(except large ones).3.Data includes imported cars.4.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Passenger car and commercial vehicle demand in Japan in 2023 stood at 4.78 million units,a 13.8%increase from the previous year.Total passenger car sales expanded 15.8%from 2022 to 3.99 million units,with standard cars climbing 30.6%to 1.76 million units,small cars growing 1.8%to 893,000 units,and minicars rising 9.5%to 1.34 million units.Meanwhile,sales of trucks grew 4.1%from 2022 to 778,000 units and sales of buses surged 53.5%to 8,400 units.Note:“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).200120022003200420052006200720082009201020112012201320142015201620172018201920202021202220231,273,5701,307,2961,291,8891,372,0831,387,0681,507,5981,447,1061,426,9791,283,4291,284,6651,138,7521,557,6811,690,1711,839,1191,511,4041,344,9671,443,3671,495,7061,479,2051,331,1491,275,8361,224,9941,341,330120,010101,78989,53277,29777,54768,71457,50951,62242,93241,63033,02327,73025,19922,92918,53619,45616,37333,90752,54337,31028,96238,98440,913175,594163,412172,644183,995197,141204,838196,040185,806167,358180,505168,705198,843194,728194,431184,127185,927201,873208,822196,034174,479182,851206,008205,138284,346258,203250,690257,775261,960242,469219,164205,486194,452219,620180,665195,192202,893216,311182,133175,110181,728185,689182,564175,150164,873168,150157,5381,853,5201,830,7001,804,7551,891,1501,923,7162,023,6191,919,8191,869,8931,688,1711,726,4201,521,1451,979,4462,112,9912,272,7901,896,2001,725,4601,843,3411,924,1241,910,3461,718,0881,652,5221,638,1361,744,919 98.998.898.6104.8101.7105.294.997.490.3102.388.1130.1106.7107.683.491.0106.8104.499.389.996.299.1106.5Standard143,690(3.1%)Buses8,410(0.2%)Total4,779,086(100%)Standard1,758,169(36.8%)Small893,228(18.7%)Mini1,341,330(28.0%)Mini403,589(8.4%)Small230,670(4.8%)Passenger Cars3,992,727(83.5%)TotalVehiclesTotal Mini-VehiclesChg.(%)Source:Japan Mini Vehicles AssociationCommercialVehicles(“Bonnet”minivans)Passenger Cars(Minicars)CommercialVehicles(Cab-over-engineminivans)CommercialVehicles(Mini-trucks)TotalChg.(%)YearSources:Japan Automobile Dealers Association;Japan Mini Vehicles AssociationTrucks777,949(16.3%)5Motor VehiclesImported Vehicle SalesMotor VehiclesUsed Vehicle Sales TRENDS IN IMPORTED MOTOR VEHICLE SALESIn vehicle units1985199019952000200520102014201520162017201820192020202120222023YearTrucksPassenger CarsOtherTotalBuses5,722,5687,109,5367,945,8678,213,9188,106,4606,539,4966,840,1746,786,8146,756,1226,937,5186,951,3986,988,1586,866,8676,731,0256,301,6516,434,916103.3104.7105.4103.5101.397.699.299.299.5102.7100.2100.598.398.093.6102.144,62054,11884,409173,475144,91087,23876,53674,21776,01375,94276,25188,14480,12778,80676,28076,224116.7107.3119.1105.2106.491.494.597.0102.499.9100.4115.690.998.496.899.911,65513,37713,32715,17318,87114,16312,53113,17313,20413,06613,25612,87912,19411,04010,72010,2321,854,3252,487,9802,281,4851,783,8511,589,5521,155,8231,100,2371,074,1991,050,1961,041,9331,054,1081,024,3341,037,0781,008,437950,464946,4881,125,5451,746,4951,538,7181,169,626980,714732,854721,406700,589670,935656,703663,976641,894640,876615,311581,285574,615589,321555,634521,244412,511368,778245,642215,295211,480217,544218,601216,026213,975226,298220,661205,201207,261139,459185,851221,523201,714240,060177,327163,536162,130161,717166,629174,106168,465169,904172,465163,978164,612103.198.3105.4102.7109.592.697.7105.1100.299.0101.597.294.790.597.195.4Chg.(%)SubtotalMiniSmallStandardChg.(%)Chg.(%)108.3102.1102.299.1101.892.696.797.697.899.2101.297.2101.297.294.399.63,811,9684,554,0615,566,6466,241,4196,353,1275,282,2725,650,8705,625,2255,616,7095,806,5775,807,7835,875,6805,737,4685,632,7425,264,1875,401,972356,726304,782727,2591,448,5461,890,1541,873,4662,367,2352,354,0772,322,5332,414,8742,449,9402,504,5762,394,9632,386,9632,225,0612,298,2333,295,0923,945,0863,845,0763,050,0872,460,4101,816,6961,653,2141,602,7191,564,9821,588,7471,523,5371,485,3391,443,8891,373,1601,257,6591,231,246160,150304,193994,3111,742,7862,002,5631,592,1101,630,4211,668,4291,729,1941,802,9561,834,3061,885,7651,898,6161,872,6191,781,4671,872,493100.9106.2106.6104.8101.098.999.899.599.8103.4100.0101.297.698.293.5102.6Chg.(%)SubtotalMiniSmallStandardChg.(%)Notes:1.Passenger cars and trucks are classified under Japans Road Vehicles Act in three categories,based primarily on engine capacity:“standard”(over 2,000cc),“small”(661cc-2,000cc),and“mini”(660cc and under);see page 23 for details.2.Includes imported vehicles.3.“Other”refers to emergency vehicles,special vehicles equipped with beds,refrigerated trucks,tank trucks,tractors,bulldozers,steamrollers,snowplows,snowmobiles,etc.,that are assigned special registration numbers.4.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Sources:Japan Automobile Dealers Association;Japan Mini Vehicles AssociationVehicles produced by non-Japanese manufacturersPassenger CarsCommercial VehiclesVehicles produced by Japanese manufacturers abroadPassenger CarsCommercial Vehicles246,7351,594248,32930,74132,29763,038277,47633,891311,367100.5Year20232022Vehicles produced by non-Japanese manufacturersVehicles produced by Japanesemanufacturers abroadPassenger Cars TotalCommercial Vehicles TotalGrand TotalsChg.(%)Passenger CarsCommercial VehiclesTotalPassenger CarsCommercial VehiclesTotal100,0000200,000300,000400,000 IMPORTED MOTOR VEHICLES(ON CUSTOMS CLEARANCE BASIS)In vehicle unitsYearPassengerCarsChg.(%)CommercialVehiclesOtherTotal MotorVehiclesChg.(%)MotorcyclesNote:“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Source:Japan Automobile Importers AssociationNotes:1.“Other”denotes special-purpose vehicles and engine-mounted chassis.2.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Source:Trade Statistics of Japan,Ministry of Finance1980198519901995200020052010201420152016201720182019202020212022202346,28552,225251,169401,836283,582282,654230,791336,764320,295331,207336,950358,221335,766282,606306,820279,469320,72571.4118.3128.6136.0109.298.6158.498.095.1103.4101.7106.393.784.2108.691.1114.85473809112,4691,4701,42011,92216,66215,87317,45520,09126,63324,93824,03630,89733,08437,5321,0855467613903766607801,27882065167283997162267159693547,91753,151252,841404,695285,428284,734243,493354,704336,988349,313357,713385,693361,675307,264338,388313,149359,19272.2118.4128.6130.3109.398.4156.798.295.0103.7102.4107.893.885.0110.192.5114.717,0157,08728,69643,93674,906444,635353,260410,143353,519341,254458,415540,008585,578707,491873,855854,893836,639 USED IMPORTED VEHICLE SALESIn vehicle unitsYearChg.(%)Chg.(%)Chg.(%)Chg.(%)TotalOtherSpecial-PurposeVehiclesTrucksPassengerCarsNotes:1.For motor vehicle classifications in Japan,see page 23.2.“Other”includes buses,large special-purpose vehicles and small-sized three-wheeled trucks.3.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).2014201520162017201820192020202120222023504,359514,363531,335560,038565,190577,671599,081580,210555,404556,19899.3102.0103.3105.4100.9102.2103.796.995.7100.118517120216218419515515927625483.992.185.094.994.492.2103.098.895.997.03,9633,6493,1032,9462,7802,5622,6382,6072,5002,42598.2101.4102.4101.699.4103.4111.598.3103.6106.115,15615,37315,73615,98415,89016,43318,31918,00518,65519,79099.4102.1103.5105.6101.0102.2103.596.895.4100.0485,055495,170512,294540,946546,336558,481577,969559,439533,973533,729Source:Japan Automobile Importers Association TRENDS IN NEW AND USED MOTORVEHICLE SALESx 1 million unitsUsed vehiclesNew vehicles USED VEHICLE SALES BY TYPE IN 2023In vehicle units USED MOTOR VEHICLE SALESIn vehicle units0123456789102014Year202320222015 2016 2017 2018 2019 2020 2021311,000 New Imported Vehicles Sold in TotalSales of new imported vehicles in Japan in 2023 totalled 311,000 units,up 0.5%from the previous year,with new passenger cars dropping 0.2%to 277,000 units but new commercial vehicles(trucks and buses)climbing 6.9%to 34,000 units.Meanwhile,sales of used imported vehicles increased 0.1%from the previous year to 556,000 units,with used passenger cars roughly the same at 534,000 units but used trucks rising 6.1%to 20,000 units.Used Vehicle Sales Total 6.4 Million UnitsIn 2023 sales of used motor vehicles increased 2.1%from the previous year to 6.43 million units.Used passenger car sales totalled 5.40 million units,growing 2.6%from the previous year,with standard cars and minicars rising 5.1%and 3.3%to 1.87 million units and 2.30 million units,respectively,but small cars dropping 2.1%to 1.23 million units.Meanwhile,sales of used trucks slipped 0.4%to 946,000 units and sales of used buses dipped 4.6%to 10,000 units.Mini574,615(8.9%)Small207,261(3.2%)Standard164,612(2.6%)Other76,224(1.2%)Total6,434,916(100%)Standard1,872,493(29.1%)Small1,231,246(19.1%)Mini2,298,233(35.7%)Buses10,232(0.2%)Passenger Cars5,401,972(83.9%)Trucks946,488(14.7%)20142015201620172018201920202021294,0601,054295,11433,54715,01248,559327,60716,066343,673104.6284,4711,025285,49628,61014,51643,126313,08115,541328,62297.8288,8301,366290,19630,84714,91745,764319,67716,283335,96097.1240,7581,468242,22637,28930,24467,533278,04731,712309,75989.9258,6371,115259,75256,35228,44884,800314,98929,563344,552108.4305,0431,045306,08828,40816,52444,932333,45117,569351,020102.1308,3891,016309,40534,38122,48056,861342,77023,496366,266104.3298,3781,061299,43927,88320,99448,877326,26122,055348,31695.1254,4041,692256,09642,90918,92861,837297,31320,620317,93391.36103.7 MOTOR VEHICLES IN USE(at end of every calendar year)TRENDS IN MOTOR VEHICLES IN USEx 1 million units PASSENGER CARS IN USE BY YEAR OF FIRST REGISTRATIONIn vehicle units MOTOR VEHICLES IN USE BY TYPE AT END OF 2023In vehicle unitsTrucks14,426,555(18.3%)Small3,512,998(4.5%)Mini8,447,004(10.7%)Special-Purpose Vehicles1,798,264(2.3%)Motor VehiclesMotor Vehicles in Use and Motor Vehicle Density In vehicle units080706050403020102014Year202320152016201720182019202020212022Total78,755,861(100%)Mini23,396,129(29.7%)Small17,998,838(22.9%)Standard20,925,199(26.6%)Standard2,466,553(3.1%)Buses210,876(0.3%)Passenger Cars62,320,166(79.1%)Notes:1.“Special-Purpose Vehicles”refers to emergency vehicles,special vehicles equipped with beds,refrigerated trucks,tank trucks,tractors,bulldozers,steamrollers,snowplows,snowmobiles,etc.,that are identified as special-purpose vehicles by special registration numbers.2.“Three-Wheeled Vehicles”includes three-wheeled passenger cars,trucks,and special-purpose vehicles.3.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).6.05.86.26.66.86.66.55.85.66.15.54.74.24.12.82.62.212.11002,321,1852,252,9162,428,4552,571,4062,639,6372,552,7452,544,9462,238,0712,167,8902,359,4482,136,1171,815,1361,620,7951,581,9721,091,1501,003,266842,1434,715,13938,882,417 April 2022-March 2023April 2021-March 2022April 2020-March 2021April 2019-March 2020April 2018-March 2019April 2017-March 2018April 2016-March 2017April 2015-March 2016April 2014-March 2015April 2013-March 2014April 2012-March 2013April 2011-March 2012April 2010-March 2011April 2009-March 2010April 2008-March 2009April 2007-March 2008April 2006-March 2007-March 2006Total“Vehicles in Use”TotalPassenger CarsTrucks,Buses&Special-Purpose Vehicles(Mini-trucks)(Minicars)Source:Ministry of Land,Infrastructure,Transport and TourismTrailersThree-WheeledVehicles%of“Vehiclesin Use”TotalVehicles in UseYear ofFirst Registration AVERAGE AGE BY TYPEIn years20132014201520162017201820192020202120222023Year8.078.138.298.448.538.608.658.728.849.039.22Passenger Cars10.7310.9311.0911.2311.3211.4111.4211.4411.5311.6711.84Trucks11.3811.5611.7611.8711.8411.8111.8311.8612.0712.3912.76Buses AVERAGE SERVICE LIFE BY TYPEIn years20132014201520162017201820192020202120222023Year12.5812.6412.3812.7612.9113.2413.2613.5113.8713.8413.42Passenger Cars13.2413.3113.7213.8914.3714.7215.1715.3115.7315.8415.96Trucks17.9117.6316.9516.8317.3917.6918.3618.3118.3819.7420.41BusesNotes:1.“Average age”means the average number of years elapsed since first registration.2.“Average service life”means average vehicle lifespan.3.“Average age”and“average service life”figures are as at the end of every fiscal year.4.The above three tables exclude mini-vehicles.Source:Automobile Inspection&Registration Information Association050100150200 1.Fukui 2.Toyama 3.Yamagata 4.Gunma 5.Tochigi 6.Nagano 7.Ibaraki 8.Gifu 9.Fukushima10.Niigata 11.Yamanashi12.Saga13.Ishikawa 14.Tottori15.Mie 16.Shimane 17.Iwate18.Akita19.Shizuoka20.Tokushima21.Okayama22.Shiga23.Kagawa 24.Kumamoto 25.Okinawa26.Miyazaki 27.Oita 28.Miyagi 29.Yamaguchi30.Aichi31.Wakayama 32.Aomori33.Kagoshima34.Ehime35.Kochi36.Nagasaki 37.Hiroshima 38.Nara 39.Fukuoka40.Hokkaido41.Chiba42.Saitama43.Hyogo 44.Kyoto 45.Kanagawa 46.Osaka 47.Tokyo National AverageSource:Automobile Inspection&Registration Information AssociationA Total of 78.76 Million Motor Vehicles in UseAt the end of December 2023,motor vehicles in use in Japan(excluding motorcycles)totalled 78.76 million units,a 0.3%increase from the previous year.Passenger cars in use grew 0.3%to 62.32 million units,with standard cars and minicars rising 2.1%and 0.9%to 20.93 million units and 23.40 million units,respectively,but small cars dropping 2.7%to 18.00 million units.Whereas trucks in use increased 0.4%to 14.43 million units compared to the previous year,buses in use fell 1.2%from 2022 to 210,900 units.At the end of March 2023,the average service life of motor vehicles in Japan was 13.42 years for passenger cars,15.96 years for trucks,and 20.41 years for buses.At March 31,2023Passenger Cars126.6108.7104.4102.6107.1104.7102.5102.0100.6101.1100.5100.7100.7100.4100.2100.1100.0100.0100.3 8,778,97217,236,32123,659,52027,844,58034,924,17244,680,03752,437,37557,090,78958,347,38760,667,51760,987,34261,403,63061,803,11862,025,91662,140,47562,194,25562,164,35662,157,601 62,320,166 2,244,4172,611,1302,176,1102,016,4872,584,9265,775,3869,901,25814,201,71417,986,98220,978,42421,504,19921,850,27522,160,84722,444,05322,678,32622,857,85922,988,16923,177,282 23,396,129 6,457,18114,417,68021,011,09625,116,17930,554,65231,030,46228,593,49126,254,54623,470,00321,974,74121,547,28221,195,62120,842,55820,383,19719,858,36119,414,01418,920,09918,491,389 17,998,838 77,374207,511472,314711,9141,784,5947,874,18913,942,62616,634,52916,890,40217,714,35217,935,86118,357,73418,799,71319,198,66619,603,78819,922,38220,256,08820,488,930 20,925,199 1970197519801985199019952000200520102014201520162017201820192020202120222023104,895102,186106,633108,967114,819114,478110,046109,917108,136108,545110,096112,011112,672112,627112,169108,999106,083104,265 103,251 83,085124,098123,387122,261130,849128,617125,437121,816119,135118,399119,293120,310120,794120,596119,997116,030112,246109,127 107,625 187,980226,284230,020231,228245,668243,095235,483231,733227,271226,944229,389232,321233,466233,223232,166225,029218,329213,392 210,876 110.5101.7100.4100.5101.699.199.9100.399.5100.5101.1101.3100.599.999.596.997.097.7 98.8 333,132584,100789,155941,6471,206,3901,500,2191,750,7331,630,0621,502,5931,669,0191,684,3821,702,6161,720,1181,734,1851,746,7651,759,1801,772,7121,783,395 1,798,264 110.5101.7100.4100.5101.699.199.998.899.2100.9100.9101.1101.0100.8100.7100.7100.8100.6 100.8 17,581,84328,090,55837,856,17446,157,26157,697,66966,853,50072,649,09975,686,45575,361,87677,188,46677,404,33177,750,52078,077,86978,289,43778,416,59178,461,95378,452,91178,523,680 78,755,861 116.2104.9104.5103.7104.7102.8101.3101.4100.0100.7100.3100.4100.4100.3100.2100.1100.0100.1 100.3 23,07939,80856,80465,48587,359120,171133,676147,626152,834159,863162,350165,769169,989174,657180,662185,088189,711194,255 197,943 243,93447,99817,7246,1234,0563,6213,8273,2803,12016,37617,39118,49419,45720,42521,42022,59823,96224,936 25,578 1970197519801985199019952000200520102014201520162017201820192020202120222023SubtotalChg.(%)YearMiniSmallStandardTrucks107.198.9104.8105.5101.198.997.899.798.299.599.299.499.499.8100.099.9100.1100.5 100.4 8,281,75910,043,85313,177,47917,139,80621,321,43920,430,14918,225,50816,733,87115,284,62514,624,98614,503,21814,411,95314,321,16714,296,11314,297,18514,283,48914,297,51414,369,292 14,426,555 3,005,0172,785,1824,527,7948,791,28912,535,41511,642,31110,154,4279,665,1309,177,2828,748,6538,634,6378,539,7018,448,5058,407,2298,376,3268,353,7998,349,0648,411,502 8,447,004 4,478,4866,100,2067,155,2216,679,6656,609,5366,213,4055,474,6604,594,3633,825,6323,581,8843,552,3733,535,0223,516,3833,506,0073,507,3083,497,2273,497,8433,501,679 3,512,998 798,2561,158,4651,494,4641,668,8522,176,4882,574,4332,596,4212,474,3782,281,7112,294,4492,316,2082,337,2302,356,2792,382,8772,413,5512,432,4632,450,6072,456,111 2,466,553 SubtotalChg.(%)Chg.(%)Chg.(%)Chg.(%)MiniSmallStandardBusesSpecial-Purpose VehiclesTotalLargeSmallSubtotalYear PRIVATE PASSENGER CARS IN USE PER 100 HOUSEHOLDS BY PREFECTURE (at March 31,2023)169.8 164.0 163.5 158.5 156.3 154.9 153.6 153.0 152.8 151.3 150.7 149.0 146.2 143.9 143.0 139.0 138.1 136.7 136.3 134.4 134.3 133.8 132.2 129.7 128.4 127.5 127.0 125.5 123.6 123.2 122.2 121.4 118.0 113.2 112.7 110.3 109.5 107.2 104.5 99.3 94.0 93.3 89.0 79.6 67.8 62.3 41.6 102.57 MOTOR VEHICLE EXPORTS TRENDS IN MOTOR VEHICLE EXPORTSNote:“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).x 1 million units MOTOR VEHICLE EXPORTS BY TYPE IN 2023In vehicle unitsMotor Vehicle Exports Total 4.42 Million UnitsMotor VehiclesExports MOTOR VEHICLE EXPORT TRENDS BY DESTINATION In vehicle units In vehicle units012345672014Year202320152016201720182019202020212022TotalPassenger CarsTrucks&BusesNotes:1.Figures represent ex-factory export shipments of motor vehicles manufactured in Japan,which are classified in the above categories as per Japanese law,including the Road Vehicles Act.2.Vehicle type classification in this table differs somewhat from that used in Ministry of Finance export data.3.KD sets have been excluded since 1979;they represent less than 60%of the cost of compositional components per vehicle and have been treated as components since 1988.4.Since December 2017,export figures from one JAMA member manufacturer have not been available.5.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Exports of motor vehicles in 2023 totalled 4.42 million units.Whereas passenger car and bus exports rose 19.8%and20.6%to 3.98 million units and 103,000 units,respectively,truck exports fell 16.0%from the previous year to 341,000 units.AsiaMiddle East Europe(EU)North America(U.S.A.)Latin America AfricaOceaniaOtherTotalChg.(%)574,986490,027775,093548,2531,719,2611,485,641276,923106,631468,64311,1184,422,682116.0Year2014201520162017201820192020202120222023 Asia Middle East Europe North America Latin America Africa Oceania Other(EU)(U.S.A.)1,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0000Source:Japan Automobile Manufacturers AssociationStandard321,546(7.3%)Buses103,401(2.3%)Total4,422,682(100%)Standard3,735,781(84.5%)Small216,052(4.9%)Mini26,308(0.6%)Mini40(0.0%)Small19,554(0.4%)Passenger Cars3,978,141(89.9%)Trucks341,140(7.7%)Passenger Cars272,549643,2321,548,2511,029,757364,376236,92986,32989,94652,90879,61474,24544,13842,28719,0829,78715,28128,20729,56519,55465,170168,370332,2571,196,973944,737612,654530,823521,848397,404408,859392,531339,821326,120331,004315,186244,598350,800376,561321,546129.5105.8127.2111.2101.886.2101.0103.5133.294.3103.5103.7102.4103.3100.377.998.898.6119.8725,5861,827,2863,947,1604,426,7624,482,1302,896,2163,795,8524,363,1684,275,3663,835,5953,970,0034,118,4324,218,4294,357,7824,372,6453,407,9993,367,5903,321,3853,978,14110,1365,45121,1241,301168,0445202922,7552,4564,5055,3673,0767,0183,1637,34964,40354,86926,3083,580,6233,932,4143,138,1471,732,0501,462,0691,198,273818,660239,198205,727241,206270,707230,684231,404235,158175,376176,239216,052715,4501,821,835345,413493,0471,343,9671,156,1222,333,2633,164,6033,453,9513,593,9413,759,7713,871,8593,944,6464,120,0804,138,0783,165,4923,127,8113,090,2773,735,7811970197519801985199019952000200520102014201520162017201820192020202120222023TrucksBusesTotal13,89222,07173,17711,3748276718162000005000040351,611833,6731,953,6852,238,1041,309,121849,859617,870611,956450,312488,473466,776383,959368,407350,091324,973259,879379,007406,126341,140120.995.3137.2108.090.682.8100.889.0142.7103.595.682.392.880.0145.8107.2 84.0 9,57916,65366,11665,60639,96144,73441,16377,937115,782141,556141,299131,642119,012109,597120,51472,95472,31385,728103,401141.6104.3179.4116.7113.760.8107.3139.6125.8103.499.893.2110.060.599.1118.6120.61,086,7762,677,6125,966,9616,730,4725,831,2123,790,8094,454,8855,053,0614,841,4604,465,6244,578,0784,634,0334,705,8484,817,4704,818,1323,740,8323,818,9103,813,2394,422,682126.7102.3130.8110.299.185.0101.0101.9133.995.5102.5101.2100.077.6102.199.9116.01970197519801985199019952000200520102014201520162017201820192020202120222023SmallStandardSubtotalChg.(%)Chg.(%)Chg.(%)Chg.(%)YearMiniSmallStandardYearMiniSubtotal611,446346,405588,648324,1541,495,8831,331,718217,631115,367435,3818,1493,818,910102.1560,304625,708744,138452,3221,662,1601,537,676306,117183,860375,6727,6654,465,62495.5529,291684,886737,518524,7701,749,2081,604,446310,001168,234390,8918,0494,578,078102.5586,954500,325818,931611,5591,898,9131,735,480294,378134,497393,4576,5784,634,033101.2601,204443,963864,518646,6791,925,3561,736,765320,236108,845434,4587,2684,705,848635,045476,157885,705646,9431,929,7811,731,025323,591119,549438,3629,2804,817,470651,814464,195980,516770,5121,919,8351,726,139286,374123,842383,2618,2954,818,132100.0559,998325,027675,630396,4511,532,2471,384,998177,86499,469362,7857,8123,740,83277.6597,296425,423555,007354,3521,429,6041,283,934260,108118,940417,5329,3293,813,23999.982.41 million units100,000 units10,000 units MOTOR VEHICLE EXPORT TRENDS BY DESTINATIONIn vehicle units MOTOR VEHICLE EXPORTS BY DESTINATION IN 2023In vehicle unitsMotor VehiclesExports by Destination21,156202,99382,1096,7071,8804,52024,36913,15116,1521134,639407,6878,902150,83042,79917,39435,60975,37418,13357,064406,10522,7968,28818,14520,40639,46896,98547,07642,66814,05558,54015,4272,39654,016440,26612,644126,15413,671016,31515,8962,678627,624233,0381,444,4241,677,46263,61035,90511,4904,0527,42620,9187,69832,971184,0708972,5691,28112712,59117,90735,372351,00437,0585,559393,6213,8403,735,781AsiaMiddle EastEuropeNorth AmericaLatin AmericaAfricaOceaniaOther Grand Totals South KoreaChinaTaiwanHong KongThailandSingaporeMalaysiaPhilippinesIndonesiaPakistanOtherSubtotalBahrainSaudi ArabiaKuwaitOmanIsraelUnited Arab EmiratesQatarOtherSubtotalSwedenDenmarkNetherlandsBelgiumFranceGermanySpainItalyFinlandPolandAustriaGreeceOtherSubtotalNorwayUKSwitzerlandRussiaTurkeyUkraineOtherSubtotalCanadaU.S.A.SubtotalMexicoPuerto RicoColombiaEcuadorPeruChileBrazilOtherSubtotalAlgeriaEgyptNigeriaKenyaSouth AfricaOtherSubtotalAustraliaNew ZealandOtherSubtotal005,3363,736522,2764,3171,0741,1804,46445722,8921023182163233,0981,3514586306,4964522,6644,6422,36015,05415,1521,99525,7892112,1542,6403,5667,10583,78410123,5512,60302,331284209112,86300023,97502,1663,2793271,4698764,25436,346000452,0701,3783,49322,05310,92084433,817145216,0520002690000026,0182126,308000000000000000000000000000000000000000000000000000000026,30821,156202,99387,44510,7121,9326,79628,68614,22517,33230,49335,117456,8879,004151,14843,01517,71738,70776,72518,59157,694412,60123,24810,95222,78722,76654,522112,13749,07168,45714,26660,69418,0675,96261,121524,05012,745149,70516,274018,64616,1802,887740,487233,0381,444,4241,677,46287,58535,90513,6567,3317,75322,3878,57437,225220,4168972,5691,28117214,66119,28538,865373,05747,9786,403427,4383,9853,978,141227010,3352,4328,9442,27517,4147,91720,58346811,55182,1461,04429,9422,3385,3771,0368,49494113,63462,8062363151573562,5582,90170211,5812746299585203,01624,20303,25517305,7001,05022534,60658241,21741,79913,405813,5841,8603,6871,279016,82740,72303,8595934,6988,56321,77839,49126,3024,1334,37534,8104,759341,140004194269,489288217,2566,2904041,37935,9538552,7592,1881,87202,6938593,39414,62000000000000000000000000007,31102625141,2071306,47715,78401,99180645318,3196,70628,2752,7523993,2446,3952,374103,40121,383202,99398,19913,57020,3659,35946,10239,39844,20531,36548,047574,98610,903183,84947,54124,96639,74387,91220,39174,722490,02723,48411,26722,94423,12257,080115,03849,77380,03814,54061,32319,0256,48264,137548,25312,745152,96016,447024,34617,2303,112775,093233,6201,485,6411,719,261108,30135,98617,5029,70512,64723,6798,57460,529276,9238978,4192,6805,32341,54347,769106,631402,11152,51014,022468,64311,1184,422,682Note:The“Total”figure includes 11,118 units(0.3%)shipped to other destinations.of which U.S.A.1,485,641(33.6%)NorthAmerica1,719,261(38.9%)of which EU 548,253(12.4%)Europe775,093(17.5%)MiddleEast490,027(11.1%)Asia574,986(13.0%)Oceania468,643(10.6%)LatinAmerica276,923(6.3%)Africa106,631(2.4%)Total4,422,682(100%)In 14YearAsiaMiddle EastLatin America AfricaOceaniaOtherEurope(EU)NorthAmerica(U.S.A.)202320152016201720182019202020212022Source:Japan Automobile Manufacturers AssociationPassenger CarsStandardSmallMiniSubtotalTrucksBusesDestinationTotalStandardSmallMiniSubtotalEUA Rise in Motor Vehicle Exports to Almost All DestinationsMotor vehicle exports increased in 2023 from the previous year to North America(1.72 million units),Europe(775,100 units),the Middle East(490,000 units),Oceania(469,000 units),and Latin America(277,000 units),but decreased to Asia(575,000 units)and Africa(107,000 units).Note:Since December 2017,export figures from one JAMA member manufacturer have not been available.Note:The UK was counted as part of the EU through January 2020,but as part of Europe from February 2020 onwards.MOTOR VEHICLE EXPORTS BY DESTINATION&BY VEHICLE TYPE IN 20232.312.56.94.18.414.011.66.83.78.515.012.76.32.98.510.80.10.10.212.86.82.39.29.42.513.26.72.59.19.92.613.55.92.68.09.60.20.20.216.737.2(34.4)16.7(10.1)38.2(35.0)16.1(11.5)41.0(37.5)40.9(36.9)18.4(13.7)40.0(35.9)18.4(13.4)39.8(35.8)20.4(16.0)17.7(13.2)18.02.715.016.04.75.72.73.03.041.0(37.0)39.2(34.9)9.711.48.79.118.0(10.6)15.415.76.83.137.5(33.7)10.911.214.6(9.3)0.20.20.213.02.46.338.9(33.6)10.611.117.5(12.4)0.315.4(8.5)227010,3352,4328,9441,43716,7907,91720,54346811,55180,6441,04429,9422,3385,3771,0368,49494113,63462,80600000008,892021001,73610,64901,217005,7001,050018,61658241,21741,79913,405813,5841,8603,6871,279015,97539,87103,1875934,6988,19521,69438,36726,3024,1334,24934,6844,759321,5460000083862400001,4620000000002363151573562,5582,9017022,6892746089585201,28013,55402,03817300022515,9900000000000852852067200368841,12400126126019,554000000004000400000000000000000000000000000000000000000000000000000000409MotorcyclesProduction MotorcyclesSales MOTORCYCLE PRODUCTION TRENDS IN MOTORCYCLE PRODUCTIONx 1 million units MOTORCYCLE PRODUCTION BY ENGINE CAPACITY IN 2023In vehicle unitsOver 50cc895,5991,030,8222,493,9102,014,8501,343,220951,803636,546298,54987,51376,56966,43899,319130,149140,921131,013122,209142,412152,54793,1011970197519801985199019952000200520102014201520162017201820192020202120222023 In vehicle units00.80.60.40.22014Year202320152022TotalOver 50cc50cc&UnderTotal682,828(100%)126cc-250cc54,237(8.0%)Over 250cc483,148(70.7%)50cc&Under93,101(13.6%)51cc-125cc52,342(7.7%)Motor-Driven Cycles Class 1(50cc&Under)1,407,2051,887,7012,181,2061,373,423686,7341,038,938630,221260,34380,63031,52930,88631,46533,66559,45147,94538,50454,28054,70352,342259,145331,733660,831469,728270,304217,738297,433279,274108,95093,53676,94573,19478,99361,65854,68253,93958,00153,56454,237385,723552,2911,098,577678,346506,637544,760851,191953,419387,082395,424348,125356,558404,176389,854333,736269,944392,261434,154483,1482,052,0732,771,7253,940,6142,521,4971,463,6751,801,4361,778,8451,493,036576,662520,489455,956461,217516,834510,963436,363362,387504,542542,421589,7272,947,6723,802,5476,434,5244,536,347 2,806,8952,753,2392,415,3911,791,585664,175597,058522,394560,536646,983651,884567,376484,596646,954694,968682,828114.484.3143.8112.7100.4101.0107.3103.0103.0106.087.5107.3115.4100.887.085.4133.5107.498.3Motor-Driven Cycles Class 2(51cc-125cc)Mini-Sized Motorcycles(126cc-250cc)Small-Sized Motorcycles(Over 250cc)SubtotalTotalChg.(%)YearNotes:1.KD sets have been excluded since 1979;they represent less than 60%of the cost of compositional components per vehicle and have been treated as components since 1988.2.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).00.80.60.40.2Source:Japan Automobile Manufacturers Association MOTORCYCLE SALES TRENDS IN MOTORCYCLE SALESx 1 million units MOTORCYCLE SALES BY ENGINE CAPACITY IN 2023In vehicle unitsOver 50cc1,978,4261,646,1151,213,512884,718558,459470,922231,247228,918193,842162,130174,259143,129132,086122,416127,736131,34092,82419801985199019952000200520102014201520162017201820192020202120222023 In vehicle units2014Year202320152016201720182019202020212022TotalTotal405,216(100%)51cc-125cc149,655(36.9%)126cc-250cc71,648(17.7%)Over 250cc91,089(22.5%)50cc&Under92,824(22.9%)Motor-Driven Cycles Class 1(50cc&Under)200,238130,574169,618138,115102,11688,74796,36896,24994,851101,42488,765105,536105,403101,737125,674101,678149,65580,799167,213165,692104,17575,887102,03837,64554,31051,27746,42956,58657,22958,35974,39278,91171,29471,64897,281143,324103,876115,43083,96376,84158,10870,15166,62162,90864,00363,22066,45667,37983,571100,88991,089378,318441,111439,186357,720261,966267,626192,121220,710212,749210,761209,354225,985230,218243,508288,156273,861312,3922,356,7442,087,2261,652,6981,242,438820,425738,548423,368449,628406,591372,891383,613369,114362,304365,924415,892405,201405,216122.0101.598.1102.293.6100.797.797.690.491.7102.996.298.2101.0113.797.4100.0Motor-Driven Cycles Class 2(51cc-125cc)Mini-Sized Motorcycles(126cc-250cc)Small-Sized Motorcycles(Over 250cc)SubtotalTotalChg.(%)YearNotes:1.Motor-driven cycle(Class 1 and Class 2)figures represent shipments to domestic dealers.2.Figures for mini-sized and small-sized motorcycles include imported motorcycles.3.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Sources:Japan Mini Vehicles Association;Japan Automobile Manufacturers AssociationMotorcycle Production Totals 683,000 UnitsOverall domestic motorcycle production in 2023 declined 1.7%from the previous year to 683,000 units.By engine capacity,Class 1 motor-driven cycles(50cc and under)fell 39.0%to 93,000 units and Class 2 motor-driven cycles(51cc to 125cc)dropped 4.3%to 52,000 units,but mini-sized motorcycles(126cc to 250cc)rose 1.3%to 54,000 units and small-sized motorcycles(over 250cc)climbed 11.3%to 483,000 units.The combined total for larger motorcycles(all those over 50cc)increased 8.7%to 590,000 units.Motorcycle Sales Total 405,000 UnitsDomestic motorcycle sales in 2023 finished at 405,000 units.By engine capacity,whereas sales of Class 1 motor-driven cycles(50cc and under)dropped 29.3%to 93,000 units and small-sized motorcycles(over 250cc)declined 9.7%to 91,000 units,Class 2 motor-driven cycles(51cc to 125cc)surged 47.2%to 150,000 units and mini-sized motorcycles(126cc to 250cc)grew 0.5%to 72,000 units.Overall sales of motorcycles with engine capacity over 50cc totalled 312,000 units,an increase of 14.1%from 2022.50cc&UnderOver 50cc20162017201820192020202110 TRENDS IN MOTORCYCLE EXPORTSx 1 million units MOTORCYCLE EXPORTS BY ENGINE CAPACITY IN 2023 In vehicle units00.80.60.40.22014Year202320152016201720182019202020212022TotalOver 50cc50cc&UnderTotal518,259(100%)51cc-125cc28,243(5.4%)126cc-250cc49,574(9.6%)Over 250cc420,373(81.1%)50cc&Under20,069(3.9%)0161284Motorcycle Exports Total 518,000 UnitsMotorcycle exports in 2023 grew 6.5%from the previous year to 518,000 units.By engine capacity,whereas exports of Class 1 motor-driven cycles,Class 2 motor-driven cycles,and mini-sized motorcycles declined 20.2%,26.1%,and 4.2%to 20,000 units,28,000 units,and 50,000 units,respectively,exports of small-sized motorcycles climbed 13.1%to 420,000 units.MOTORCYCLE EXPORTSOver 50cc326,815288,843501,027369,167147,30161,62782,03857,86011,52212,77811,76116,03116,55917,02516,12215,57125,93825,14120,0691970197519801985199019952000200520102014201520162017201820192020202120222023 In vehicle unitsMotor-Driven Cycles Class 1(50cc&Under)914,3251,546,1701,907,4811,350,412507,840691,433549,040197,37848,97629,77130,82330,18125,39530,99924,32925,23335,09538,21428,243187,185328,313548,306296,865117,222129,961204,591177,82485,50663,89159,85159,80558,61153,89548,51640,90652,90151,75749,574309,277527,344972,226525,038411,381442,689805,508899,161347,460359,144315,214322,602362,558354,839307,412230,288323,108371,701420,3731,410,7872,401,8273,428,0132,172,3151,036,4431,264,0831,559,1391,274,363481,942452,806405,888412,588446,564439,733380,257296,427411,104461,672498,1901,737,6022,690,6703,929,0402,541,4821,183,7441,325,7101,641,1771,332,223493,464465,584417,649428,619463,123456,758396,379311,998437,042486,813518,259133.883.0144.0119.7107.394.2116.1100.490.7108.089.7102.6108.198.686.878.7140.1111.4106.5Motor-Driven Cycles Class 2(51cc-125cc)Mini-Sized Motorcycles(126cc-250cc)Small-Sized Motorcycles(Over 250cc)SubtotalTotalChg.(%)YearNotes:1.Figures represent ex-factory export shipments of motorcycles manufactured in Japan.2.Class 2 motor-driven cycles include three-wheeled motor-driven cycles.3.KD sets have been excluded since 1979;they represent less than 60%of the cost of compositional components per vehicle and have been treated as components since 1988.4.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Source:Japan Automobile Manufacturers AssociationMotorcyclesMotorcycles in UseMotorcyclesExports TRENDS IN MOTORCYCLES IN USE(at March 31 yearly)x 1 million units MOTORCYCLES IN USE BY ENGINE CAPACITY(at March 31,2023)In vehicle unitsTotal10,302,276(100%)51cc-125cc2,009,621(19.5%)Over 250cc1,872,776(18.2%)TotalOver 50cc50cc&Under10.30 Million Motorcycles in UseAt March 31,2023,motorcycles in use in Japan totalled 10.30 million units,down 0.1%from the previous year.By engine capacity,whereas Class 1 motor-driven cycles,accounting for 42%of all motorcycles in use,dropped 3.5%to 4.33 million units in 2023,Class 2 motor-driven cycles,mini-sized motorcycles,and small-sized motorcycles in use rose 3.0%,1.4%,and 3.4%to 2.01 million units,2.09 million units,and 1.87 million units,respectively.Thus,motorcycles over 50cc in use increased 2.6%,to a total of 5.97 million units.MOTORCYCLES IN USE(at March 31 yearly)Over 50cc3,727,4264,851,1408,794,33514,609,39913,539,26911,165,3909,643,4878,566,6137,448,8626,438,0026,188,7105,899,2765,615,3605,353,4735,103,3954,853,1314,652,6864,489,4014,331,3371970197519801985199019952000200520102014201520162017201820192020202120222023 In vehicle unitsMotor-Driven Cycles Class 1(50cc&Under)4,431,7453,132,8182,281,0061,747,9571,517,2281,421,0311,337,3951,353,7321,511,4401,674,8841,704,0831,717,0921,737,9111,752,2781,787,1331,818,3571,872,4911,950,8582,009,621583,316492,307506,5671,047,4261,669,7711,823,4461,704,5221,857,4391,992,9391,980,4111,978,4621,970,4711,961,1091,966,9731,968,9051,972,3672,014,2512,058,8812,088,542109,771276,715383,639775,6271,045,5191,177,2291,288,3991,397,3921,524,1761,595,3351,611,0891,628,4611,641,5801,657,6131,680,4161,704,5421,748,0261,811,8151,872,7765,124,8323,901,8403,171,2123,571,0104,232,5184,421,7064,330,3164,608,5635,028,5555,250,6305,293,6345,316,0245,340,6005,376,8645,436,4545,495,2665,634,7685,821,5545,970,9398,852,2588,752,98011,965,54718,180,40917,771,78715,587,09613,973,80313,175,17612,477,41711,688,63211,482,34411,215,30010,955,96010,730,33710,539,84910,348,39710,287,45410,310,95510,302,276100.5101.9109.8104.897.698.098.099.398.498.998.297.797.797.998.298.299.4100.299.9Motor-Driven Cycles Class 2(51cc-125cc)Mini-Sized Motorcycles(126cc-250cc)Small-Sized Motorcycles(Over 250cc)SubtotalTotalChg.(%)YearNotes:1.Motor-driven cycle data is as at April 1,and since 2006 motorcycles with engine capacity of 125cc and under whose owners fail to pay the mandatory motorcycle ownership tax are not included in this data.2.“Chg.(%)”means change from the previous year(with the previous years result indexed at 100).Sources:Ministry of Land,Infrastructure,Transport and Tourism;since 2006(only for the 125cc-and-under categories),Ministry of Internal Affairs and Communications50cc&Under4,331,337(42.0%)126cc-250cc2,088,542(20.3%)2014Year20232015201620172018201920202021202211 MOTORCYCLE EXPORTS BY DESTINATION&BY ENGINE CAPACITY IN 2023In vehicle units MOTORCYCLE EXPORTS BY DESTINATION IN 2023In vehicle unitsAsiaMiddle EastEuropeNorth AmericaLatin AmericaAfricaOceaniaGrand Totals South KoreaChinaTaiwanHong KongThailandSingaporeMalaysiaPhilippinesIndonesiaOtherSubtotalSaudi ArabiaIsraelUnited Arab EmiratesOtherSubtotalSwedenDenmarkNetherlandsBelgiumFranceGermanyPortugalSpainItalyPolandAustriaHungaryGreeceCroatiaSloveniaOtherSubtotalNorwayUKSwitzerlandRussiaTurkeyOtherSubtotalCanadaU.S.A.SubtotalMexicoGuatemalaPanamaColombiaPeruChileBrazilArgentinaOtherSubtotalMoroccoGuineaDem Rep CongoEthiopiaKenyaUgandaSouth AfricaOtherSubtotalAustraliaNew ZealandOtherSubtotalof which U.S.A.132,218(25.5%)NorthAmerica149,514(28.8%)of which EU 241,134(46.5%)Europe265,349(51.2%)MiddleEast6,801(1.3%)Asia34,611(6.7%)Oceania28,071(5.4%)LatinAmerica22,106(4.3%)Africa11,807(2.3%)Total518,259(100%)100,000 units10,000 units1,000 units2014YearAsiaMiddle EastLatin America AfricaOceaniaEurope(EU)NorthAmerica(U.S.A.)202320152016201720182019202020212022Source:Japan Automobile Manufacturers AssociationEUAn Increase in Motorcycle Exports to a Majority of DestinationsCompared to the previous year,motorcycle exports in 2023 increased to Europe(265,000 units),Asia(35,000 units),Oceania(28,000 units),and Africa(12,000 units),but decreased to North America(150,000 units),Latin America(22,000 units),and the Middle East(7,000 units).MotorcyclesExports by DestinationMotor-Driven Cycles Class 1(50cc&Under)DestinationMotor-Driven Cycles Class 2(51cc-125cc)Mini-Sized Motorcycles(126cc-250cc)Small-Sized Motorcycles(Over 250cc)SubtotalTotalOver 50ccNote:The UK was counted as part of the EU through January 2020,but as part of Europe from February 2020 onwards.MOTORCYCLE EXPORT TRENDS BY DESTINATION In%2.71.41.01.20.85.75.83.639.4(34.9)7.20.837.5(34.6)7.17.16.74.932.0(27.6)7.21.240.9(38.1)5.94.14.430.2(26.1)7.01.447.0(44.1)7.35.43.128.4(24.3)6.31.048.5(45.8)0.95.02.730.4(26.0)6.30.947.6(45.0)2.98.01.15.52.928.8(24.5)5.51.148.2(46.0)7.32.81.54.32.830.4(26.3)7.51.546.2(42.2)7.31.81.53.81.833.6(29.5)7.01.345.2(41.2)6.21.91.64.81.931.2(27.5)5.51.648.8(45.0)6.72.32.31.31.34.328.8(25.5)5.451.2(46.5)12 0 0 0 0 0 0 24 2 10 48 15 0 48 33 96 0 0 0 0 2,451 537 0 228 273 0 0 0 84 33 93 0 3,699 0 0 81 0 0 0 3,780 1,147 12,257 13,404 6 6 3 18 0 42 6 0 171 252 92 0 0 0 0 0 30 9 131 1,905 447 6 2,358 20,069 4 0 122 0 0 133 0 37 765 39 1,100 58 79 228 88 453 0 0 753 0 2,638 1,222 0 242 398 0 0 0 90 46 95 0 5,484 0 0 47 0 0 0 5,531 2,151 9,483 11,634 38 32 4 302 6 101 36 30 260 809 28 20 1,832 2,048 203 199 266 396 4,992 3,100 618 6 3,724 28,243 2 96 0 126 40 352 24 221 353 66 1,280 39 65 160 257 521 110 62 1,066 248 3,154 1,104 0 281 1,398 132 228 15 93 24 121 161 8,197 15 330 230 0 69 10 8,851 3,226 22,960 26,186 70 230 69 168 26 251 355 66 1,376 2,611 69 0 84 2,485 34 29 664 495 3,860 4,524 1,646 95 6,265 49,574 5,077 5,734 5,175 789 4,880 2,339 3,607 2,770 454 1,358 32,183 1,140 2,507 1,002 1,082 5,731 1,501 1,474 32,316 5,201 58,060 32,055 726 27,197 43,747 3,656 7,306 1,688 4,454 777 1,216 2,380 223,754 913 9,759 6,892 0 5,098 771 247,187 10,772 87,518 98,290 2,364 415 108 2,897 141 1,099 8,453 1,157 1,800 18,434 494 0 60 0 11 0 966 1,293 2,824 13,468 2,071 185 15,724 420,373 5,083 5,830 5,297 915 4,920 2,824 3,631 3,028 1,572 1,463 34,563 1,237 2,651 1,390 1,427 6,705 1,611 1,536 34,135 5,449 63,852 34,381 726 27,720 45,543 3,788 7,534 1,703 4,637 847 1,432 2,541 237,435 928 10,089 7,169 0 5,167 781 261,569 16,149 119,961 136,110 2,472 677 181 3,367 173 1,451 8,844 1,253 3,436 21,854 591 20 1,976 4,533 248 228 1,896 2,184 11,676 21,092 4,335 286 25,713 498,190 5,095 5,830 5,297 915 4,920 2,824 3,631 3,052 1,574 1,473 34,611 1,252 2,651 1,438 1,460 6,801 1,611 1,536 34,135 5,449 66,303 34,918 726 27,948 45,816 3,788 7,534 1,703 4,721 880 1,525 2,541 241,134 928 10,089 7,250 0 5,167 781 265,349 17,296 132,218 149,514 2,478 683 184 3,385 173 1,493 8,850 1,253 3,607 22,106 683 20 1,976 4,533 248 228 1,926 2,193 11,807 22,997 4,782 292 28,071 518,259 12Call center Fire command center Automatic communication of essential information(accident location,vehicle occupant injury status,etc.)Airbag deployment notificationAmbulance dispatch Emergency medical servicehelicopter dispatchEmergency medical facility Information coordination 05101585 and older80-8475-7970-7465-6960-6455-5950-5445-4940-4435-3930-3425-2920-2416-19Elderly fatalities as%of total fatalitiesAdvanced Emergency Braking SystemAcceleration Control for Pedal ErrorAACN:A Schematic OverviewCumulative Number of AACN-Equipped Vehicles in Use by Year,2016-2023In%In001,0001,5002,0002,5003,0003,5004,0004,5005,0002,6104,3884,113 4,1173,9043,6943,5323,2152,8392,6361,4712,3092,193 2,247 2,1382,0201,9661,7821,5961,520Total fatalities(No.of persons)Elderly fatalities 65 years and older(No.of persons)2013Year02550751002023202220212020201920182017201620152014025507510020202019202120182017201620152014202120232014 2015 2016 2017 2018 2019 202020222,6781,46554.756.452.653.354.654.854.755.755.456.257.79.755.674.192.923.182.862.242.542.522.191.811.952.933.687.572013Year202320222013Year ROAD ACCIDENTS/INJURIES/FATALITIES0500,0001,000,0001,500,0002,000,00005,00010,00015,00020,0001980Year19851990199520002005201020152020Fatalities(Number of persons)Injuries(Number of persons)Accidents(Number of accidents)TRENDS IN ELDERLY ROAD FATALITIESPromoting Greater Road SafetyRoad SafetyRoad SafetyNo.of fatal accidents per 100,000 drivers license holdersAge group FATAL ROAD ACCIDENTS PER 100,000 DRIVERS LICENSE HOLDERS BY AGE GROUP TRENDS IN ONBOARD INSTALLATION RATES OF ADVANCED DRIVER-ASSISTANCE SYSTEMS(ADAS)AUTOMATIC COLLISION NOTIFICATIONAccidents(Number of accidents)Year1980198519901995200020052010201120122013Injuries(Number of persons)Fatalities(Number of persons)Source for all data on this page:National Police Agency476,677552,788643,097761,794931,950934,346725,924692,084665,157629,033598,719681,346790,295922,6771,155,7071,157,113896,297854,613825,392781,4928,7609,26111,22710,6849,0736,9374,9484,6914,4384,388Accidents(Number of accidents)Year2014201520162017201820192020202120222023Injuries(Number of persons)Fatalities(Number of persons)573,842536,899499,201472,165430,601381,237309,178305,196300,839307,911711,374666,023618,853580,850525,846461,775369,476362,131356,601365,0274,1134,1173,9043,6943,5323,2152,8392,6362,6102,678In 2023 road fatalities(defined here as deaths taking place within 24 hours of accident occurrence)in Japan rose to 2,678,the first such increase in eight years.Road accidents and road injuries also saw increases,for the first time in nineteen years,to 307,911(in number of accidents)and 365,027(in number of persons).As the aging of Japans society advances,annual road accident statistics show a growing ratio of elderly people(aged 65 years and older)in road fatalities.In addition,the number of fatal road accidents per 100,000 drivers license holders attributable to elderly drivers(aged 75 years and older)is the largest among age groups.Given the circumstances,Japans Ministry of Economy,Trade and Industry,Ministry of Land,Infrastructure,Transport and Tourism,National Police Agency,Financial Services Agency and automobile-related organizations have been working cooperatively to promote the widespread use of“safety support cars”(“sapocars”for short)equipped with safety features such as advanced emergency braking systems(referred to in this publications previous editions as collision-mitigation braking systems),to help drivers of all ages avoid road accident occurrence and to mitigate damage/injury when accidents do occur.Automatic collision notification(ACN)is an onboard-based system that automatically communicates essential information to relevant authorities in the event of a serious road traffic accident,such as when an airbag is deployed,without requiring the driver or witnesses to report the incident themselves.Advanced automatic collision notification(AACN)is an enhanced version of ACN whose onboard installation is steadily expanding.As of the end of 2023,more than 6.6 million vehicles were equipped with AACN.Road SafetyVehicle Safety Features and Systems THE“SAFETY SUPPORT CAR”Ver 1.0 CONCEPTSafety Support Car(“Sapocar”)Safety Support Car S(“Sapocar S”)Advanced emergency braking system(pedestrian collision avoidance)Acceleration control for pedal error(1)Lane departure warning(2)Advanced headlamp control(3)Advanced emergency braking system(vehicle collision avoidance)Acceleration control for pedal error(1)Advanced emergency braking system(vehicle collision avoidance)for low-speed vehicle operation(4)Acceleration control for pedal error(1)“Sapocar S”ClassificationThe“Sapocar S”concept has three sub-classifications,based on the safety features installed.(1)In automatic-transmission vehicles only.(2)Including lane-keeping assist.(3)Automatic high-to-low-beam headlamp control,glare-free high beam headlamp control,or adaptive front-lighting system.(4)30km/h or lower.Note:Drivers license holders here refers to drivers possessing valid licenses for driving automobiles,motorcycles,and motor-driven cycles.Note:In%means the number of passenger cars equipped with the ADAS feature as a percentage of the total number of passenger cars produced for the domestic market.Note:Above figures apply only to AACN-equipped vehicles manufactured by Japanese automakers for the domestic market.Source:Japan Automobile Manufacturers Association Source:National Agency for Automotive Safety and Victims AidPassenger cars equipped with advanced emergency braking systems;suitable for all drivers Passenger cars equipped with advanced emergency braking systems and acceleration control for pedal error;suitable especially for elderly drivers Type:“Wide”Type:“Basic ”Type:“Basic”Source:Japan Automobile Manufacturers Association ACNAACNAutomatic collision notificationAdvanced automatic collision notificationAutomatic communication of essential information(location,etc.)to the authorities concerned in the event of a serious road traffic accidentEssential information automatically communicated to relevant authorities in the event of a serious road traffic accident is augmented with information on the status of vehicle occupant injuries,which is directed also to fire departments and medical facilities for their prompt dispatch of emergency medical service vehicles including,as necessary,a helicopter.In vehicle units97.899.060.172.049.197.295.893.784.677.866.244.941.115.493.194.896.190.883.877.165.247.137.432.212.54,845,1466,617,6503,722,2582,698,7861,742,5241,046,700480,340265,8981,000,0002,000,0003,000,0004,000,0005,000,0006,000,00007,000,00020232022202120202019201820172016YearVehicle avoidanceBicycle avoidance13*I.e.,performing all the requisite processes of recognition,prediction,judgment,and operation.The Transition to Automated DrivingIn 2018 the Japanese government released an outline of the broad spectrum of system-building measures needed for the real-world implementation of automated driving.The adoption in 2020 of a revised Road Traffic Act and a revised Road Vehicles Act made it mandatory for automated driving systems and devices to comply with safety standards.In addition,rules were established regarding the obligations of drivers of vehicles equipped with automated driving systems,with the inclusion of automated driving event data recorders in such systems also being mandated.These initiatives allowed Level 3 self-driving vehicles to run on public roads.In 2022 a further revision of the Road Traffic Act was adopted enabling the creation of an authorization system to facilitate Level 4 automated driving(self-driving vehicles used under specific circumstances,e.g.,on designated and limited routes)and Level 4 automated vehicle use in accordance with those stipulations started in April 2023.JAMA member companies are actively working towards the practical and widespread use of automated driving technologies in line with the initiatives undertaken by the government.MemoACHIEVINGTHE“ZEROS”RESOLVING RELATED ISSUES Through the elimination of human errorZero accidents Through more efficient roadand vehicle use(via telematics)Zero congestion Through optimally efficientdoor-to-door vehicle use,“any time and anywhere”Enabling optimally accessible mobilityEnabling optimally efficient freight transportDriver-assistance systemsAutomated driving functions JAMAS VIEW OF AUTOMATED DRIVINGDriverDriverDriverSystem(Driver,when ADS cannot execute a task)System System Level 0Level 1Level 2Level 3Level 4Level 5Vehicles with driver-assistance systemsVehicles with conditional driving automationVehicles with high driving automationVehicles with full driving automationDriver performs the entire dynamic driving task(DDT).Driver-assistance system performs the subtasks of either longitudinal or lateral vehicle motion control(within a limited operational design domain),while the driver performs all other DDT subtasks.Advanced driver-assistance system performs the subtasks of both longitudinal and lateral vehicle motion control(within a limited operational design domain),monitored by the driver who performs all other DDT subtasks and can take manual control at any time.ADS performs the entire DDT(within a limited operational design domain).However,driver must remain alert and respond appropriately to ADS-issued requests to intervene when ADS cannot execute a task(=human override).ADS performs the entire DDT(within a limited operational design domain)and responds in the event of operational difficulty.However,Level 4 vehicles can operate only under specific circumstances,with human override remaining an option.ADS performs the entire DDT and responds unconditionally(not within a limited operational design domain)in the event of operational difficulty,with no need for human intervention.LevelIn Charge*Vehicle DescriptionDefinitionDriver(human)performs part or all of the dynamic driving taskAutomated driving system(“ADS,”“system”)performs the entire dynamic driving task(while engaged)DEFINITIONS OF DRIVING AUTOMATION LEVELS AND LEVEL-COMPATIBLE VEHICLE DESCRIPTIONSSource:The Public-Private ITS Initiative/Roadmaps initiativeRoad SafetyAutomated Driving14Attention to the EnvironmentVehicle Fuel EfficiencyAttention to the EnvironmentClimate Changex 1 million tonsClimate Change and CO2 Emissions Reduction:The Response of the Transport SectorIn 2022 Japans CO2 emissions totalled 1.04 billion tons,of which the transportation sector accounted for nearly 19%.Despite a small increase in 2022 over the previous year,CO2 emission volumes in Japans transport sector have trended downwards since peaking in 2001,owing largely to increased fuel efficiency in passenger cars and greater efficiency in goods distribution.The automobile industry will continue to vigorously promote CO2 emissions reduction in road transport by further improving vehicle fuel efficiency and expanding the market supply of alternative fuel vehicles.CO2 Emissions Reduction:Improving Vehicle Fuel EfficiencyFuel efficiency targets for passenger cars,trucks,and buses are formulated by applying“top runner”criteria whereby the target value for a given vehicle weight category is established based on the leading fuel efficiency performance to date for that weight category.To comply,first,with stringent 2015 average fuel efficiency targets for heavy-duty vehicles as well as with a 2020 target for passenger cars and,subsequently,with a 2022 target for small trucks,2025 targets for heavy-duty vehicles,and a 2030 target for passenger cars,JAMA member manufacturers have been making continuous efforts to increase the fuel efficiency of conventional vehicles and expand the supply of alternative fuel vehicles.Calculation of the average fuel efficiency target of 25.4 km/L(a 32.4%increase over the actual value in 2016)established for 2030 for new passenger cars took into account,for the first time,the fuel efficiency performances of electric vehicles and plug-in electric vehicles.(4)Fuel efficiency is JC08 test cycle-based(see page 18).(5)Targets were established assuming the same shipment volume ratios by vehicle weight category for target years as those recorded in the years showing the actual value of fuel efficiency performance.Sources:Ministry of Economy,Trade and Industry;Ministry of Land,Infrastructure,Transport and Tourism50km/L1015202.50km/L57.510TrucksUp 12.2 15 target value(7)7.09 km/L2002 actual value 6.32 km/LBusesUp 12.1 15 target value(7)6.30 km/L2002 actual value 5.62 km/L 2015 AVERAGE FUEL EFFICIENCY TARGETS FOR NEW HEAVY-DUTY VEHICLES(GVW3.5t)(6)2.50km/L57.510TrucksUp 13.4%(approx.)2025 target value(8),(9)7.63 km/L2015 target value(9)6.72 km/LBusesUp 14.3%(approx.)2025 target value(8),(9)6.52 km/L2015 target value(9)5.71 km/L 2025 AVERAGE FUEL EFFICIENCY TARGETS FOR NEW HEAVY-DUTY VEHICLES(GVW3.5t)VEHICLE TECHNOLOGIES FOR INCREASED FUEL EFFICIENCY0km/L201030PassengercarsUp 24.1 20 target value(3)20.3 km/L2009 actual value 16.3 km/L 2020 AVERAGE FUEL EFFICIENCY TARGET FOR NEW PASSENGER CARS(1)(6)Fuel efficiency is JE05 test cycle-based.(7)Targets were established assuming the same shipment volume ratios by vehicle weight category for target years as those recorded in the years showing the actual value of fuel efficiency performance.(8)While the 2015 target values for new heavy-duty vehicles are JE05 test cycle-based,the 2025 target values were established on the basis of a new measuring method.(9)Targets were established assuming the same shipment volume ratios by vehicle weight category for 2025 as those recorded in 2014.Sources:Ministry of Economy,Trade and Industry;Ministry of Land,Infrastructure,Transport and Tourism(1)Fuel efficiency is JC08 test cycle-based(see page 18).(2)Fuel efficiency is WLTC-based(see page 18).(3)Targets were established assuming the same shipment volume ratios by vehicle weight category for target years as those recorded in the years showing the actual value of fuel efficiency performance.Sources:Ministry of Economy,Trade and Industry;Ministry of Land,Infrastructure,Transport and TourismReduced rolling resistance Low rolling-resistance tiresImproved powertrain performance Expansion of lock-up area Expanded number of transmission gears Continuously variable transmissionImproved engine efficiency More efficient fuel consumption:Direct injection Variable mechanisms(variable cylinder activation,VVT&L,etc.)Downsized engine superchargingReduction of friction loss:Reduction of piston&piston ring friction loss Low-viscosity lubricating oil Other Electric power steering Idling prevention(stop-start)Reduced aerodynamic drag Improved body configuration Reduced vehicle weight Expanded use of lightweight materials Improved body structurex 1 million tons CO2 EMISSIONS IN JAPANThe transportation sector accounts for nearly 19%of Japans total CO2 emissions,which in 2022 amounted to 1.04 billion tons.TRENDS IN CO2 EMISSION VOLUMES IN JAPANS TRANSPORT SECTOR,BY MODEMotor vehicle-emitted CO2 accounts for about 85%of the totality of CO2 emitted by Japans transport sector.CO2 emissions from road transportation in Japan have seen a significant decrease since transport-sector emissions peaked in 2001.Source:Ministry of the EnvironmentJapans CO2 Emission Volumes,1990-2022CO2 Emission Shares by Sector in 2022Industry34%Transportation19%Energyconversion8%Other0%Waste processing3%Industrialprocesses4%Residential15%Commercial/Other17%Automobiles16%Sources:Ministry of the Environment;Ministry of Land,Infrastructure,Transport and Tourism2022 Total1.04 billiontonsSmall trucks(GVW3.5tons)Up 26.1 22 target value(5)17.9 km/L2012 actual value 14.2 km/L 2022 AVERAGE FUEL EFFICIENCY TARGET FOR NEW SMALL TRUCKS(4)0km/L201030PassengercarsUp 32.4 30 target value(3)25.4 km/L2016 actual value 19.2 km/L 2030 AVERAGE FUEL EFFICIENCY TARGET FOR NEW PASSENGER CARS(2)Note:Figures here are JC08 test cycle-based through 2016 and the JC08 test-cycle equivalents of WLTC-based values from 2017.Source:Japan Automobile Manufacturers Association AVERAGE FUEL EFFICIENCY OF DOMESTIC NEW GASOLINE-POWERED PASSENGER CARSIn km/L121416182022242613.213.813.914.214.314.814.915.616.717.118.219.821.322.422.422.622.622.722.923.123.522.121 222001Fiscal year1,0001,0501,1001,1501,2001,2501,3001,3501,4000350300250200150100501990Fiscal year20771389288918148969592814896101939137971049491481001099510148102115961015810312097111671001239811147981259911147971302000263111579613001111479613502111479313503111489113204111379112805123111379006120111279107120111288908116101188709118101078310118910884111169109811211710111080131131011108014108101110801510810109801610710109781719222120106101097818104111087710210108768951077219218387710874921010773AircraftShipsTrainsTrucksPassenger cars&buses1990Fiscal year19952000200520102015202202 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 2015In-Use Status of Alternative Fuel VehiclesSince 2009,when the governments tax incentive/subsidy programs for the purchase of eco-friendly vehicles were first introduced,new registrations of alternative fuel vehiclesincluding hybrid,plug-in hybrid,electric,fuel cell,clean diesel,and other new-energy vehicleshad been steadily increasing.In 2020,however,new registrations of these vehicles shrank owing to the spread of COVID-19.Nevertheless,as a result of each automakers efforts to develop a range of such models and despite the impact of the pandemic,the share of alternative fuel vehicles in new passenger car registrations continues to expand yearly,reaching 54%in 2023.The more widespread use of these vehicles requires not only further advances in vehicle and related technologies,but also,among other government initiatives,the establishment of the necessary fuel/energy supply infrastructures and the continued provision of purchasing incentives.In vehicle units FACILITY-GENERATED CO2 EMISSION VOLUMES,1990-2022Source:Japan Automobile Manufacturers AssociationCO2 Reductions at Manufacturers FacilitiesJapans automakers,together with the member companies of the Japan Auto-Body Industries Association(JABIA),have for years taken measures to reduce energy consumption and otherwise cut CO2 emissions at their production plants.Having more recently expanded their voluntary CO2 reduction activities to also include administrative and research facilities,their combined facility-emitted CO2 in 2022 totalled 5.17 million tons(preliminary figure),down 10,000 tons from the previous year.With a revised target for 2030 of 4.63 million tons(down from the previous target of 6.16 million tons),JAMA and JABIA member companies will strive for further CO2 reductions at their facilities.CO2 emissions(x 1 million tons)CO2 emissions/productionvalue(x 1,000 tons CO2per 1 trillion yen)RestrictionsSubstanceCompliance StatusAs of January 2006,a 90crease or more from the 1996 level of 1,850 grams(i.e.,a maximum permissible level of 185 grams).*For large commercial vehicles including buses,a 75crease or more from the 1996 level.*Batteries are exempt.As of January 2005,banned except for trace amounts in safety-related components such as:-Instrument panel displays-Liquid crystal displays in navigation devices -Discharge lamps-Fluorescent cabin lampsBanned as of January 2008.Banned as of January 2007.All models have complied since January 2006.All models have complied since January 2003.Components listed here in the left column are now mercury-free in all models.All models are in compliance.All models have complied since January 2006.LeadMercuryHexavalent chromiumCadmium RESTRICTIONS ON THE USE OF FOUR HEAVY METALS IN NEW VEHICLES&COMPLIANCE STATUS ALTERNATIVE FUEL PASSENGER CAR NEW REGISTRATIONS,2008-2023Voluntary Initiatives to Eliminate the Use of Four Heavy Metals in Motor Vehicles TARGET VALUES FOR INDOOR CONCENTRATION LEVELS OF 13 SUBSTANCES(VOCs)(revised in January 2019)Target Value forIndoor Concentration LevelSubstancePrincipal Sources 100 g/m3 (0.08 ppm)260 g/m3 (0.07 ppm)200 g/m3 (0.05 ppm)240 g/m3 (0.04 ppm)3,800 g/m3 (0.88 ppm)220 g/m3 (0.05 ppm)1 g/m3 (0.07 ppb)17 g/m3 (1.5 ppb)330 g/m3 (0.04 ppm)100 g/m3 (6.3 ppb)0.29 g/m3 (0.02 ppb)48 g/m3 (0.03 ppm)33 g/m3 (3.8 ppb)Adhesives for plywood,wallpaper,etc.Adhesives/paints for interior finishing materials,furniture,etc.Adhesives/paints for interior finishing materials,furniture,etc.Moth repellents,lavatory air freshenersAdhesives/paints for plywood,furniture,etc.Insulation materials,bath units,tatami-mat core materialsInsecticides(esp.ant exterminators)Paints,pigments,adhesivesKerosene,paintsWallpaper,flooring materials,wire-coating materialsPesticidesAdhesives for construction materials,wallpaper,etc.Insecticides(esp.termite exterminators)FormaldehydeTolueneXyleneParadichlorobenzeneEthylbenzeneStyreneChlorpyrifosDi-n-butyl phthalateTetradecaneDi-2-ethylhexyl phthalateDiazinonAcetaldehydeFenobucarbA Voluntary Approach to Reducing Vehicle Cabin VOCsEstablished in January 2002 by Japans Ministry of Health,Labor and Welfare,target values for indoor concentration levels of 13 volatile organic compounds(VOCs)were amended in January 2019,with a view to enabling automakers,on a voluntary basis,to meet the revised target values in all new-model vehicles marketed from January 2022.To measure VOC concentration levels in vehicle cabin air,in-cabin test procedures developed by JAMA and covering passenger cars as well as trucks and buses were introduced in 2005.However,in July 2012 JAMA member companies adopted the global standard for testing in-cabin VOCs in passenger carsnamely,the ISO 12219-1 test procedure(revised in 2021)established by the ISO that same month.Ten years later,JAMA member companies adopted the ISO 12219-10 test procedure for measuring in-cabin VOCs in trucks and busesformulated on the basis of a JAMA-developed procedureestablished by the ISO in 2022.The automakers at present continue to work to achieve further reductions in in-cabin VOC concentration levels.Attention to the EnvironmentHazardous SubstancesAttention to the EnvironmentAlternative Fuel Vehicles and CO2 Reductions at Manufacturers FacilitiesJAMA member manufacturers have,on a voluntary basis,eliminated the use of four heavy metalslead,mercury,hexavalent chromium and cadmiumin new vehicles to reduce their environmental impact,particularly when they are dismantled and processed at the end of their service life.Restrictions on the use of these substances in motorcycles have been established separately.Source:Japan Automobile Manufacturers AssociationPlug-in hybridvehiclesElectricvehiclesFuel cellvehiclesClean dieselvehiclesTotalHybridvehiclesYear108,518347,999481,221451,308887,863921,0451,058,4021,074,9261,275,5601,385,3431,431,8561,472,2811,346,8421,434,7191,450,5821,843,6620001510,96814,12216,17814,1889,39036,00423,23017,60914,68022,67737,71952,12601,0782,44212,60713,46914,75616,11010,46715,29918,09226,53321,28114,57421,65858,78688,51200000074111,0548496126857612,46484842004,3648,9278,79740,20175,43078,822153,768143,468156,162176,725175,145147,139149,298140,340169,683108,518353,441492,590472,727952,5011,025,3531,169,5191,253,7601,444,7711,596,4501,658,9561,687,0011,523,9961,630,8161,688,2752,154,4032008200920102011201220132014201520162017201820192020202120222023Source:Japan Automobile Manufacturers AssociationIn%TRENDS IN ALTERNATIVE FUEL VEHICLE SHARE IN NEW PASSENGER CAR REGISTRATIONSNotes:1.This voluntary initiative applies only to vehicles that are manufactured and sold in Japan.2.The use of paradichlorobenzene,chlorpyrifos,diazinon and fenobucarb does not apply to vehicle cabins.50101520253035404555502.624.929.734.836.437.839.240.044.449.09.011.713.420.822.52008Year09 10 11 12 13 14 15 16 17 18 19 2021 22 2301002003004005006007001990Fiscal year2008 0910111213141516172030(Target)181920212245678910119.905446.703545.873776.143726.503887.364187.473837.163586.663236.713266.613066.232865.825.22271287 2852375.18 5.174.6354.01635218.617.218.8 18.8 19.521.022.724.319.816.917.718.119.120.821.620.0 19.921.021.221.220.817.517.610.3332018128621.411.1 1.3 0.6 0.4 0.3 0.4 0.3 0.30.4 0.3 0.30.2 INDUSTRY MEASURES IN LINE WITH NATIONAL LEGISLATION THE ELV RECYCLING FLOW(as per the provisions of the End-of-Life Vehicle Recycling Law)Under Japans End-of-Life Vehicle(ELV)Recycling Law which entered into force in January 2005,automobile manufacturers and importers are responsible for recovery,recycling and appropriate disposal with respect to fluorocarbons,airbags,and automobile shredder residue(ASR).Compliance with the law was anticipated to enable ASR to be recycled at a rate of 70%by 2015,resulting in an automobile recycling rate,by vehicle weight,of 95%(as compared with the 80%rate prevailing prior to the introduction of the law);those rates were in fact surpassed in 2008.Japans vehicle recycling infrastructure as mandated by its ELV Recycling Law is the first in the world to administer the entire process of auto recyclingfrom ELV recovery to final disposalon the basis of electronic“manifests”(or compliance checklists).In line with legislative provisions promoting the so-called 3R initiatives(“reduce,reuse,and recycle”),Japans automakers are also striving to design vehicles using lightweight materials that are easy to dismantle and recycle,and to reduce and recycle waste generated in the manufacturing process.In 2022 the volume of auto plant-generated waste destined for landfill disposal totalled 300 tons(preliminary figure).Having long surpassed the target of 1,000 tons set for 2025,JAMA members will nevertheless continue to promote the reduction of plant-generated waste for landfill disposal.2023(Preliminary)2,726,0662,388,7542,414,9652,551,0812022(Actual)2,739,4212,391,5062,377,6392,565,991Fiscal YearNo.of ELVs recoveredAppropriate recovery of three designated items(1)Through recovery/appropriate disposal of inflators or through onboard deactivation.(2)Covers all categories of processors,whether for direct disposal or for transfer to other markets.(1)Nineteen products including automobiles have been designated in this legislation as requiring“reduce”initiatives in their design.(2)Twenty-three products including automobiles have been designated in this legislation as requiring“reuse”and“recycle”initiatives in their design.Sources:Japan Automobile Recycling Promotion Center;Japan Auto Recycling Partnership;Toyotsu Recycle Corporation;“ART”group of companiesSources:Government-affiliated entitiesVehicle Recycling and Waste ReductionPromotion of Effective Utilizationof Resources Law(the“3R”Law)Product DesignWaste ManagementELV RecyclingEnd-of-Life VehicleRecycling LawBasic premise:-Environmentally responsible vehicle design on the part of automobile manufacturers-Recovery and recycling of:1)Fluorocarbons 2)Airbags 3)ASRNote:Motorcycles are not covered by the ELV Recycling Law.For designated products(1):-Weight reduction/Downsizing-Longer product life-Reduced use of hazardous substancesFor designated products(2):-Use of reusable/recyclable materials-Ease of dismantling-Ease of sorting-Non-hazardous recycling-Materials identificationDistribution,Servicing and Use“Reduce”initiatives“Reuse”initiatives“Recycle”initiatives ELV RECOVERY IN NUMBERSIn vehicle unitsFluorocarbonsAirbags(1)ASR(2)Achieved2.39 million vehicle units(2022)95%(2022)96.4-97.4%(2022)TargetDestruction85 05:30 10:50 15:70%Three DesignatedItemsFluorocarbonsAirbagsASR RECYCLING RATES:TARGETED&ACHIEVED Delegated Funds Management Entity(Japan Automobile Recycling Promotion Center)Delegated Information Management Entity(Japan Automobile Recycling Promotion Center)Automobile Manufacturers/Importers/Delegated Organization(Japan Automobile Recycling Promotion Center)RecoverymanifestsDeliverymanifestsRecoverymanifestsDeliverymanifestsRecoverymanifestsDeliverymanifestsRecoverymanifestsDeliverymanifests*Fluorocarbons are destroyed.Payment of recovery,recycling and disposal costsNote:The Japan Automobile Recycling Promotion Center assumes the same responsibilities as automobile manufacturers and importers when an ELV has no manufacturer representation under the provisions of this law.It also assumes transport-to-mainland costs for ELVs turned in on Japans smallest islands.FluorocarbonDisposal*FacilitiesPurchasers ofNew VehiclesPurchasers ofUsed VehiclesFinal OwnersDismantlersFluorocarbonRecoveryOperatorsELVCollectorsInspection®istration verification(MOTAS)Mini-vehicle inspectionAirbagDisposal FacilitiesShredder ResidueRecycling FacilitiesShredder ResidueRecycling FacilitiesShredder Residue ProcessorsPress&ShearOperatorsTo markets for recyclable parts,metals,etc.Shredderresidue Fluorocarbons Paymentfor recoveryPaymentfor recoveryShredding&Sorting OperatorsFluorocarbon&airbag disposal managed byJapan Auto Recycling Partnership(JARP)Designated Handling AgentDesignated Handling AgentMOTAS:Japanese-derived acronym for“motor vehicle inspection and registration system”VehiclecarcassesELVsELVsELVsELV flowInformation flowFee remittance/payment flowsRecycling feeremittances REDUCTIONS IN PRODUCTION PLANT-GENERATED WASTESource:Japan Automobile Manufacturers AssociationWaste for landfill disposal(x 1,000 tons)025201510505004003002001001990Fiscal year20012025(Target)21 22Total value of vehicle production including motorcycles(x 1 billion yen)Attention to the EnvironmentRecyclingDisposal/RecyclingFacilities(14)THE MOTORCYCLE RECYCLING FLOWNotes:1.The only cost to final owners(where applicable)is for the delivery by ELV dealers of end-of-life motorcycles to certified collection centers.2.The disposal of municipally owned end-of-life motorcycles requires advance approval by the Japan Automobile Recycling Promotion Center.FinalOwnersSource:Japan Automobile Recycling Promotion CenterCertified Collection Centers(170)Deliveryto certifiedcollectioncentersEnd-of-Life Motorcycle DealersELV Motorcycle Dealer DesignationDigits represent dealers ID code.Verificationof ownershipVerificationof recyclingdocumentationDelivery of end-of-lifemotorcycle toan ELV motorcycle dealerDelivery of end-of-life motorcycle directly to a certified collection centerEnd-of-Life Motorcycle Processing(nationwide operations)AirbagsMotorcycle Recycling MarkVerificationof ownershipVerificationof recyclingdocumentation02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20For designated areas of activity:-Reduction/recycling of designated waste products generated in vehicle manufacturing operations:1)Scrap metals 2)Casting sand residue-Total waste volume:*1990(baseline):352,000 tons 2022:300 tons JAMA target:1,000 tons by fiscal 2025*For landfill disposal,including scrap metals,casting sand residue,and other waste17 MOTOR VEHICLE EMISSIONS REGULATIONS IN JAPAN Japans vehicle exhaust emissions regulations have always been among the worlds most stringent,and its automakers have worked very hard to develop the advanced technologies required to comply with them.As a result,NOx and other atmospheric pollutant levels have been,even in large urban areas,on a steady decline.Japan has participated in international discussions on the global harmonization of emission test cycles and in 2010 introduced the UN test cycle for motorcycle emissions.In 2018 Japan began applying the UN“WLTC”to measure emissions from new gasoline-powered passenger cars and light commercial vehicles,following its application in 2016 of the UN“WHTC”for measuring diesel exhaust emissions from new heavy-duty vehicles(see corresponding notes below).GasolineandLPG VehiclesDiesel VehiclesMotorcyclesSources:Ministry of the Environment;Ministry of Land,Infrastructure,Transport and Tourism(1)WLTC:Worldwide Harmonized Light Vehicles Test Cycle,on the basis of values measured in cold-start state.(2)The PM and PN values for gasoline and LPG vehicles and the PM value for motorcycles apply only to lean burn direct-injection vehicles.(3)Small-sized diesel passenger cars have an equivalent inertia weight(EIW)of 1.25t(GVW of 1.265t)or less,and mid-sized diesel passenger cars have an EIW over 1.25t.(4)WHTC:World Harmonized Transient Cycle,on the basis of(values measured in cold-start state)x 0.14 (values measured in warm-start state)x 0.86.(5)WHSC:World Harmonized Steady-State Cycle.(6)Class I motorcycles:Over 0.050L and under 0.150L in engine capacity with a maximum speed of 50km/h,or under 0.150L in engine capacity with a maximum speed of 50km/h and 100km/h.Equivalent to motor-driven cycles,Class 1 and Class 2.Class II motorcycles:Under 0.150L in engine capacity with a maximum speed 100km/h and 130km/h,or 0.150L or over in engine capacity with a maximum speed of 130km/h.Equivalent to mini-sized and small-sized motorcycles with a maximum speed of 130km/h.Class III motorcycles:With a maximum speed of 130km/h.Equivalent to mini-sized and small-sized motorcycles with a maximum speed of 130km/h.(7)WMTC:World Motorcycle Test Cycle.Note:CO:Carbon monoxide;NMHC:Non-methane hydrocarbons;NOx:Nitrogen oxides;PM:Particulate matter;PN:Particle number;THC:Total hydrocarbons.Japans Test Cycles for Measuring Fuel Consumption and Exhaust EmissionsJapan not only promotes the international standardization of test cycles for measuring motor vehicle fuel consumption and CO2 and other emissions but has actively contributed to the development of the Worldwide Harmonized Light Vehicles Test Cycle(also referred to as the Worldwide Harmonized Light-Duty Test Cycle),or WLTC,under the United Nations World Forum for Harmonization of Vehicle Regulations.In line with that initiative,Japan is now in the process of replacing its JC08 test cycle for passenger cars and other non-heavy-duty vehicles with WLTC.WLTC incorporates three driving cycles:the“urban,rural and expressway modes,”as they are called in Japanese.The indication wherever necessary of fuel consumption rates measured in the three driving“modes”as well as their certified mean(i.e.,average)rate has been required since October 2018.COMPARISON OF WLTC AND THE JC08 TEST CYCLE FOR LIGHT VEHICLES HOW LIGHT-VEHICLE FUEL CONSUMPTION RATES(EXAMPLES)ARE INDICATED IN JAPANMeasured on the basis of the JC08 test cycle01,600Time(sec)1,4001,2001,0008006004002001000102030405060708090(1)Fuel consumption rates are obtained on the basis of designated test conditions.In real-world on-road driving,rates will vary as a result of multiple factors(weather and traffic conditions,driving behavior,use of air conditioner,etc.).Vehiclespeed(km/h)The JC08 Test Cycle01,600Time(sec)1,4001,2001,000800600400200WLTCUrban modeRural modeExpressway modeFuel consumption rate(1)certifiedby the Ministry of Land,Infrastructure,Transport and Tourism21.4km/L(1)Fuel consumption rates are obtained on the basis of designated test conditions.In real-world on-road driving,rates will vary as a result of multiple factors(weather and traffic conditions,driving behavior,use of air conditioner,etc.).(2)WLTC is an international test cycle incorporating urban,rural and expressway driving cycles or“modes”with specific time durations designated for each mode.Urban mode:(Assumptions)Low-speed driving characterize
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(C)Copyright Japan Automobile Manufacturers Association,Inc.,All rights reserved.Automated Driving Safety Evaluation Framework Ver 3.0 Japan Automobile Manufacturers Association,Inc.Sectional Committee of AD Safety Evaluation,Automated Driving Subcommittee December 2022 (C)Copyright Japan Automobile Manufacturers Association,Inc.,All rights reserved.List of committee members Chief of Sectional Committee:Hideaki Sato,Toyota Motors Deputy Chief of Sectional Committee,Safety argument WG Leader:Koichiro Ozawa,Honda Motor Co.,Ltd.Deputy Chief of Sectional Committee:Eiichi Kitahara,Nissan Motors Co.,Ltd.Committee member,Virtual Evaluation of Perception WG Leader:Yumi Kubota,Nissan Motor Co.,Ltd Committee member:Kohji Ishiwata,Nissan Motor Co.,Ltd Committee member:Tomofumi Koishi,Honda Motor Co.,Ltd.Committee member:Shinji Narimatsu,Honda Motor Co.,Ltd.Committee member:Yoshiya Kubo,Mazda Motor Corporation Committee member:Yusuke Yamada,Mazda Motor Corporation Committee member:Fumihiko Takegoshi,SUZUKI MOTOR CORPORATION Committee member:Shinji Tsunoda,SUBARU CORPORATION Committee member:Kenichi Yamada,Daihatsu Motor Co.,Ltd.Committee member:Masaru Idoguchi,Hino Motors Ltd.Committee member:Atsushi Ohshiba,Hino Motors Ltd.Committee member:Shinichiro Kawano,Isuzu Motors Limited Committee member:Yasuhiro Furukawa,Mitsubishi Motors Corporation Committee member:Tomoya Yabuzaki,Yamaha Motor Co.,Ltd.Committee member:Tetsuya Ishida,UD Trucks Corporation Advisor:Hiroaki Nakata,Hitachi Astemo,Ltd.Advisor:Koichi Terui,Hitachi Astemo,Ltd.Advisor:Tatsuhiko Monji,Hitachi Astemo,Ltd.Advisor:Yuko Murase,DENSO CORPORATION Advisor:Kenji Suganuma,DENSO CORPORATION Advisor:Shingo Jinno,DENSO CORPORATION Advisor:Masami Suzuki,Pioneer Corporation (C)Copyright Japan Automobile Manufacturers Association,Inc.,All rights reserved.iii Contents Main changes and additions to Ver.3 .1 1 1.Positioning of this Paper .1 1 2.Automated Driving System Safety Argumentation Structure .2 2 2.1.Issues with existing approaches.2 2 2.1.1.Safety evaluation through long-distance/long-duration driving tests .2 2 2.1.2.Data storage/classification scenario-based approach .2 2 2.2.Overview of Physics Principles Approach Process .3 3 2.3.Safety Argumentation Structure Framework .5 5 2.3.1.Automated driving safety principles .5 5 2.3.2.Scope of safety evaluation .6 6 2.3.3.Method of evaluating safety .7 7 2.3.4.Safety evaluation method for perception disturbance .2020 2.3.5.Safety evaluation method for vehicle disturbance.2222 3.Scenario-Based Safety Assurance Process .2525 3.1.Safety argumentation scheme(Steps of the V-shaped model).2525 3.1.1.Item definition .2525 3.1.2.Safety Analysis .2626 3.1.3.Safety Design and Safety Concept .2626 3.1.4.System development .2626 3.1.5.Examination and validation of the sub-system and the vehicle .2727 3.1.6.Safety assessment .2727 3.1.7.Final check process before release .2727 3.1.8.Incident management.2727 4.Scenario structure .2828 4.1.Traffic disturbance scenario .2828 4.1.1.General vehicle scenario .2828 4.1.2.Scenarios unique to motorcycles .3636 4.1.3.Scenarios resulting from the combination of behaviours by several vehicles .3636 4.2.Perception disturbance scenarios .3737 4.2.1.Perception disturbance scenarios .3737 4.2.2.Blind Spot Scenarios .6464 4.2.3.Communication disturbance scenario .7373 4.3.Vehicle motion disturbance scenarios .7676 4.3.1.Classification of vehicle body input .7676 4.3.2.Classification of tyre inputs .7878 4.3.3.Predictable vehicle motion disturbance safety approach.8080 5 Scenario Database .9090 5.1 Three layers of extraction .9090 5.2 Database parameters,format,and architecture .9090 5.3 Test scenario database interface specification .9191 Annex A Road Geometry .9393 A.1 Road geometry component elements .9595 A.2 Basic parameters of road geometry .9696 A.3 Update with actual environmental data .9797 A.4 Updating road geometry parameters based on actual world map data .9797 (C)Copyright Japan Automobile Manufacturers Association,Inc.,All rights reserved.iv Annex B Scenarios for Motorcycles .9999 B.1 Classification of surrounding motorcycle location and motion .9999 B.2 Traffic disturbance scenario unique to motorcycles .9999 Annex C Approach for complex scenarios of traffic disturbance .101101 C.1 Concept of avoidance motion scenario .101101 C.2 Traffic flow scenarios .101101 C.2.1 Avoidance trigger .102102 C.2.2 Avoidance space .102102 C.2.3 Cut-in vehicles into the avoidance area .104104 C.2.4 Road environment .104104 Annex D Verifying the completeness of scenario database based on accident data .106106 D.1 German In-Depth Accident Study(GIDAS)data .106106 D.2 Pre-crash scenario typology for crash avoidance research(NHTSA).107107 D.3 Institute for Traffic Accident Research and Data Analysis(ITARDA)data .107107 Annex E Principle models and evaluation scenarios of perception disturbances .111111 E.1 Processes of principle models description and evaluation scenario derivation .111111 E.2 Principle models and evaluation scenarios of mmWave Radar .112112 E.2.1 mmWave Radar Large difference of signal(S)(recognition target).113113 E.2.2 mmWave Radar Low D/U (road surface multipath).119119 E.2.3 mmWave Radar Low D/U (change of angle).123123 E.2.4 mmWave Radar Low S/N (direction of a vehicle).128128 E.2.5 mmWave Radar Low D/U (surrounding structures).132132 E.3 Principle models and evaluation scenarios of LiDAR .136136 E.3.1 LiDAR Attenuation of signal(recognition target).137137 E.3.2 LiDAR Noise .146146 E.3.3 LiDAR Signal not from recognition target(reflection from raindrops).154154 E.4 Principle models and evaluation scenarios of Camera .160160 E.4.1 Camera Hidden(image cut out).161161 E.4.2 Camera Low spatial frequency/low contrast(caused by spatial obstruction).171171 E.4.3 Camera Overexposure .184184 Annex F Guideline for validation of virtual environment with perception disturbance .193193 F.1 overview of requirements defined in this Annex .193193 F.2 Common requirement and reproductivity validation method.194194 F.2.1 the way of thinking about common requirement .194194 F.2.2 The way of thinking about common requirement for each sensor .196196 F.2.3 Validation method of common requirement .204204 F.3 perception disturbance reproducing requirement and reproductivity validation method .233233 F.3.1 the way of thinking about perception disturbance reproducing requirement .233233 F.3.2 The way of thinking about perception disturbance reproducing requirement for each sensor .233233 (C)Copyright Japan Automobile Manufacturers Association,Inc.,All rights reserved.v F.3.3 Validation method of perception disturbance reproducing requirement .239239 Annex G Validation of Simulation Tools and Simulation Test Methods Related to UN Regulation No.157 .259259 G.1 Purpose and Scope.259259 G.2 Terminology.259259 G.3 Method for Validating the Simulation Tool .260260 G.3.1 Purpose of This Chapter .260260 G.3.2 Validation Method and Criteria .260260 G.3.3 Simulation Tool Requirements .261261 G.4 Procedure for Validating the Simulation Tool .262262 G.4.1 Purpose of This Chapter .262262 G.4.2 Procedure for Validating the Simulation Tool .262262 G.5 ADS Safety Performance Evaluation Simulation Method .263263 G.5.1 Purpose of This Chapter .263263 G.5.2 Test Method .263263 G.5.3 Definition of the Parameters of the Ego and Other Vehicles .264264 G.5.4 Definition of Each Scenario .265265 G.5.5 Criteria for Pass or Fail .265265 G.5.6 Parameter Range for Simulations .266266 G.5.7 Conducting Simulation .269269 G.6 Submission Documents .271271 1 Main changes and additions to Ver.3 Traffic disturbance scenarios The motorway-specific content has been revised to include general roads,and a traffic disturbance scenario for general vehicles that includes general roads has been added along with the addition of ITARDA data to Annex D.Perception disturbance scenarios The content of Annex E and F has been added.Vehicle motion disturbance scenarios Preventability/unpreventability boundary conditions have been added for general roads.1.Positioning of this Paper【Background】The realization and deployment of autonomous driving(AD)is expected to bring forth an even safer society which is also more efficient and with a freer mobility.The fulfillment of these expectations is a major global challenge that stands on the sufficient safety assurance and verification of the autonomous vehicles both in terms of performance and technology.In this document,the Japan Automobile Manufacturers Association Inc.(JAMA)has summarized the best practice on safety argumentation structuring,safety evaluation,and safety assessment methods needed to enable logical completeness,practicability,and transparency of AD safety.The safety assessment and the technical judgment may be revised according to the practical implementation and evolution of the AD safety assurance dialogue,along with technical content modifications.【Aims】To enhance safety and efficiency of AD systems development by providing guidelines that serve as a common ground for each JAMA member at each product development stage,from planning and design,to evaluation.To gain a common technical understanding when international regulations and standards are formulated.To clarify JAMA position when cooperating with international projects.2 2.Automated Driving System Safety Argumentation Structure An overview of the safety argumentation structure for AD systems with SAE automation level 3 through to level 5 is provided in this chapter.2.1.Issues with existing approaches 2.1.1.Safety evaluation through long-distance/long-duration driving tests Long-distance/long-duration driving test strategies aim at ensuring safety by randomly indentifying malfunctions and unintended disengagements in a black box-type manner,until a certain value for a probabilistic metric is guaranteed.These strategies,applied as a safety evaluation process,present issues both in terms of evaluation scope sufficiency and of explainability in emergencies.The main issue related to evaluation scope sufficiency relates to the stochastical increase of factors and associated hazards with driving distance and time.In other words,it is not possible to ensure that hazards due to factors not identified in long-distance/long-duration runs will not occur after release.Further,within a contex in which there is neither legal nor social consensus on criteria based on driving distance or time,the issue on explainability in emergencies relates to the impossibility of clarifying social responsibility for emergency interventions when hazards are encountered by the system.Probabilistic safety criteria based on long-distance/long-time driving also present problems from a technical development point of view,due to the inefficiency of identifying factors that dependend on the environmental conditions in which the driving was conducted,as well as on the characteristics of the vehicle.2.1.2.Data storage/classification scenario-based approach A number of countries are actively developing data driven scenario-based approaches to address the challenges of applying previous ADAS development processes for safety assurance of AD systems of SAE automation level 3 through to level 5.These approaches incorporate normal traffic and accident data,process the data,and systematically categorize the processed information into formats known as scenarios which are stored in a database.The collection,storage and creation of such scenarios and database in the public domain,free from manufacturers intellectual property and bias,may enable the development a safety evaluation ecosystem,that both certification bodies and manufacturers could incorporate for the benefit of the general public through safer vehicles.However,the scenario based approach does not resolve per se the aboved mentioned issue concerning evaluation scope sufficiency before release.When the obtained data is tagged and categorized,the compensation for the phenomenon that may occur in the future still depends on the distance and time or the amount of data,so the previously mentioned issue related to evaluation scope sufficiency remains unresolved.Further,if the driving data shared in the public domain is only comprised of images and vehicle trajectories this will lead to insufficient safety verification range,as such data may exclude factors related to autonomous vehicles misinterpretaion of both the surroundings and its own conditions,as well as factors possibly affecting vehicle stability.3 2.2.Overview of Physics Principles Approach Process In order to address the limitations of existing approaches concerning evaluation scope suffciency and explainability in emergencies,a Physical Principles Approach Process for safety evaluation is proposed.This proposal essentially incorporates physics principles into a scenario-based approach.The number of safety-relevant situations that an AD system may encounter in real traffic is infinite.Therefore,if scenarios are structuralized by solely combining traffic factors without further considerations,the unlimited number of variables that need to be considered will prevent from a complete scope verification.In contrast with the infinite number of safety-relevant situations that an AD system may encounter in traffic,the number of physics principles that the system can apply for safely handling such situations is limited.AD systems decompose all DDT into perception,judgement and operation subtasks,and each of these subtasks is associated with one or several specific physics principles.Therefore,if scenarios are decomposed and structuralized logically in consideration of the physics of the AD system,then it is possible to provide a complete coverage of all the safety-relevant root causes for given DDT.This motivates the incorporation of perception,traffic situation,and operation related disturbances,and the corresponding scenario structures introduced in the following table,in Figure 1 and Figure 2,and elaborated in detail in following chapters.Task Processing results Disturbance Governing physics principles Perception Own position,surrounding traffic environment positional information and other traffic information Perception disturbance Light,radio wave,infrared light propagation principles that affect camera,mili-wave radar and LiDAR sensors,respectively Judgement Path,speed plan instructions Traffic disturbance Kinematics describing the motion of traffic participants,objects and systems of groups of objects,without reference to the causes of motion.Operation Movement instruction allocation for each ACT for achieving path and speed plan instructions Vehicle control disturbance Dynamics,concerned with forces applied on the vehicles body and tires,and their effects on motion.Figure 1.different categories of structuralized scenarios considering physics principles for each corresponding perception,judgement and control tasks 4 Figure 2.Schematic of the three disturbance categories considered to logically structuralize scenarios Perception disturbance refers to conditions in which the sensor system may fail to correctly judge a hazard or a non-hazard for sensor or vehicle intrinsic or extrinsic reasons.Examples of intrinsic reasons include part mounting(e.g.unsteadiness related to sensor mounting or manufacturing variability),or vehicle conditions(e.g.vehicle inclination due to uneven loading that modifies sensor orientation,or sensor shielding with external attachments such as bicycle racks).External reasons include environmental conditions(e.g.sensor cloudiness,dirt,light,etc.)or blind spots induced by surrounding vehicles.Traffic disturbance refers to traffic conditions that may lead to a hazard resultant of a combination of the following factors:road geometry(e.g.,branch),ego-vehicle behaviour(e.g.,lane change),and surrounding vehicle location and action(e.g.cut-in from a near side vehicle).Vehicle disturbance refers to situations in which perception and judgement work correctly but where the subject vehicle may fail to control its own dynamics.This can be due to intrinsic vehicle factors(e.g.total weight,weight distribution,etc.)or extrinsic vehicle factors(e.g.road surface irregularities and inclination,wind,etc.).Collected normal traffic and accident data can be used to confirm possible gaps in terms of whether situations actually occurring in real traffic are being missed by the logically created scenario systems.Further,by assigning probabilistic ranges to physical parameters for each qualitative scenario category,the data and scenarios can also be used to show in a downscaled manner,to what extent certain situations actually occur.Scenario StructureTraffic DisturbancePerception DisturbanceVehicle DisturbanceTraffic participants unsafe behaviorSensing/Localize/Communication limitationCause of vehicle instability 5 2.3.Safety Argumentation Structure Framework 2.3.1.Automated driving safety principles The WP29 document for the harmonisation of international regulations on automated driving reads Automated vehicles shall not cause any non-tolerable risk,meaning that,under their operational domain,shall not cause any traffic accidents resulting in injury or death that are reasonably foreseeable and preventable(UN/WP29,2019,WP29-177-19,Framework document on automated/autonomous vehicles).These definitions allow to contextualize the safety philosophy of the current methodology proposed,with respect to safety principles that international policy makers are applying in the form of a matrix(Figure 3).Considering the two conditions of foreseeability and preventability together generates a 4 quadrant matrix that better contextualises the philosophy of this document.Scenario based safety evaluation,can be found in the top left quadrant of the matrix where no accidents are acceptable.This quadrant accounts for all scenarios for which an accident is foreseeable and preventable.The bottom left quadrant of the matrix depicts the traffic situations that can not be foreseen but that can be prevented.The cases that fall under this category form the basis for learning and serve as a precedent for future generation AD system developments.The top right quadrant of the matrix introduces cases that are foreseeable but not preventable.The situations that fall under this category are situations for which mitigation is the only option.Measures to reduce the damage resultant of these unpreventable(yet foreseeable)cases constitutes the main area of focus in this section.The final quadrant(bottom right)accounts for crashes that are neither foreseeable nor preventable.In these situations,resilience support in the form of legalities,the division of responsibilities,health support,insurance and other such areas need to be the focus of attention.Figure 3.Safety approach in context with foreseeability and preventability matrix 6 2.3.2.Scope of safety evaluation Figure 4 presents a summary of the safety aspects described in the WP29 framework document organized hierarchically.With the common top level safety goal of achieving systems free of unreasonable safety risks,the scope of the current proposal is limited to Validation for System Safety(highlighted in pink).The validation for system safety according to the safety vision framework can be further decomposed as shown in Figure 5.The scope of the current proposal is limited to critical conditions,and excludes Pre critical conditions.The reason for this exclusion is that,in situations in which there may be a potential risk(e.g.frontal vehicle carrying a load that may fall on the road),may induce many actuations that are not motivated by real risks and that alter traffic imposing risks on other participants(e.g.braking frequently despite not being a real risk).Therefore,to address pre-critical situations,rather than applying physics principles approach processes,other means to verify if the vehicle follows traffic rules and keeps sufficient distance with surrounding objects Figure 4.Safety Aspects Hierarchy Diagram Figure 5.Safety argumentation structure diagram 7 2.3.3.Method of evaluating safety The main DDT safety risk is to collision with the surrounding traffic participants or obstacles,which is systematized through traffic disturbance scenarios.By defining quantified ranges of reasonable foreseeability and preventability for each of these traffic disturbance scenarios,quantitative criteria associated to each test are defined.Based on these traffic related hazardous scenarios,it is then possible to expand the evaluation to incorporate perception-and vehicle stability-related hazardous scenarios into the assessment which will enable a comprehensive safety evaluation(Figure 6).Figure 6.Overview of method of judging safety 8 2.3.3.1.Traffic disturbance safety evaluation method Traffic disturbance is the position and actions of traffic participants existing around your own vehicle that prevent safe driving by your own vehicle.As previously described,the basic thinking behind safety principles is to equip the automated driving system with higher level avoidance performance than a competent and careful human driver within a foreseeable range.For this thinking,we need to define and model the performance of a competent and careful drive applied to traffic disturbances.By implementing this defined model in a simulation program and deriving the actual scope avoidable for a competent and careful human driver,it is possible to define safety standards in relation to traffic disturbances.Figure 7.Overview of traffic disturbance safety judgement method The competent and careful human driver performance model definition(Figure 8)is able to define the three elements of perception,judgement,and operation.It is important to have objective grounds for defining parameter coefficients related to performance shown in the respective segments.Figure 8.Competent and careful human driver model Here,the driving action elements of judgement and operation are explained.The main avoidance actions of automatic driving in relation to traffic disturbances are considered to be the brake operation(deceleration action)and,regardless of the type of traffic disturbance(position and action of the traffic participants surrounding the ego vehicle）,this is fulfilled by defining the performance of a competent and careful human driver.Figure 9 9 shows a diagram which demonstrates the brake operation of a competent and careful human driver.The model on the left shows the braking operation made by a competent and careful human driver.The model on the right is a functional model of the collision damage mitigation braking system(AEB:Advanced Emergency Braking),it considers the amount of improvement in avoidance performance when equipped with AEB.Figure 9.Competent and careful human driver brake model Perception response time,the time delay from the moment when a competent and careful human driver perceives risk to the time that deceleration braking force occurs is set at 0.75 s.This time set is used by police and domestic courts in Japan when establishing a drivers“perception response time”.In terms of maximum deceleration force,quoting the Japanese test data shown in Figure 10,is 0.774G.Whereas the brake force generated by normal drivers in emergencies is 0.689G,normal drivers who have received training in driving techniques have a braking force of 0.774G;albeit this is defined as a higher skill value compared to ordinary drivers.Furthermore,from the accident statistics data from NHTSA(Figure 11),0.74G is the peak value;therefore,the maximum deceleration of 0.774G applied to the competent and careful human driver model can be considered appropriate.Figure 10.Emergency brake characteristic Figure 11Maximum deceleration due to deceleration of the preceding vehicle Figure 12 shows a waveform diagram of deceleration braking for drivers who have received driver skill training.This quotes the Japanese test data previously described.In this waveform diagram,the time for reaching the maximum deceleration is demonstrated,and the maximum deceleration arrival of a competent and careful human driver is defined as 0.6 s.10 Figure 12.Emergency brake characteristics study example(arrival time until maximum deceleration)11 2.3.3.1.1.Cut-in scenarios Cut-in scenarios are scenarios in which vehicles travelling in an adjacent lane to the ego vehicle cuts in front of it.Figure 13 shows a schematic expressing boundary conditions where a competent and careful human driver judges it risky when another vehicle cuts in in front of the ego vehicle.Figure 13.Cut-in judgement conditions and danger judgement boundaries The boundary conditions when it is judged that a vehicle travelling in the adjacent lane has cut in front of the ego vehicle are defined as the cut-in vehicle lateral movement distance(wander amplitude).In an actual driving environment,vehicles driving while maintaining their lane will wander a little to the left or right while driving.In the scope of the wander lateral movement distance,it is unlikely that the vehicle traveling in the adjacent lane of the ego vehicle travels whith a recognition that it will cut in.Therefore,the cut-in perception boundary conditions were defined from the lateral distance movement(wander amplitude)distribution(Figure 14)of vehicles changing lanes based on the data observed in the actual traffic environments.After the cut-in judgment,the boundary conditions for perceiving risk for the ego vehicle and perceives a need for the emergency brake(risk perception boundaries)can be defined by multiplying the maximum lateral velocity derived from the actual traffic observation data by the risk perception response time.When calculating the risk perception response time,test data using a driving simulator carried out in Japan was utilised and analysed.The prerequisites for the test are shown in Figure 16.Figure 14.Actual observation statistics for stagger amplitude Figure 15.Maximum lateral velocity observation data statistics 12 Figure 16.Assumptions for driving simulator tests The tests measured the drivers response(reaction time,avoidance operation)for cut-ins from 20 other regular drivers(Table 1).The measurements were performed twice on each participant;by comparing the respective average values of the first and second time,we derived the time until risk was perceived.Table 1.Test participant attributes The test results are shown in Figure 17.The results demonstrated that the time from the start of the cut-in from the other driver to when risk was perceived was 0.8 s for the first time and 0.4 s for the second time.Based on these test results,with the first time perception,the cut-in time is required by the other driver and the time for risk to be perceived,whereas the second time because they were driving while being wary of the cut-in,the time for identifying the cut-in from the other vehicle was not required.However,even when the driver was aware,time was still required for determining risk(Figure 18),and the time until risk was perceived was defined as 0.4 s.Figure 17.Driving simulator test results 13 Figure 18.Relationship between cut-in identification time and danger judgement time As described above,the risk judgement boundary is defined as the time when multiplying the maximum lateral velocity,and the time until perceiving risk.The maximum lateral velocity of 1.8 m/s calculated from the actual traffic observation data and the time until risk is perceived and calculated from the driving simulator test results of 0.4 s are multiplied.Therefore,the risk perception boundary is defined as 1.8 0.40.72 m.When the cut-in perception condition and risk evaluation boundary area applied to the diagram in Figure 8,it results in Figure 19.Figure 19.Competent and careful human driver model(Cut In)14 According to the UNR collision warning guidelines,the boundary that requires emergency action is defined as TTC=2.0 s regarding the longitudinal(distance from the other vehicle)risk evaluation boundary(Figure 2).This is cited to define the longitudinal risk evaluation boundary as TTC=2.0 s.Figure 20.UNR collision warning guidelines(Citation)2.3.3.1.2.Cut-out Scenario The cut-out scenario is a scenario in which the leading vehicle that the ego vehicle is following suddenly changes its lane to the adjacent lane(cut-out).This scenario evaluates safety in relation to the sudden appearance of a decelerating or stopped vehicle(such as broken-down car and the tail end of a traffic jam)in front of the ego vehicle due to the preceding vehicles cut-out.Figure 21 shows the schematic that represents the boundary condition for the competent and careful human driver who perceives the situation to be risky when the preceding vehicle performs a cut-out.Figure 21.Cut-out perception condition and risk evaluation boundary The cut-out perceived boundary condition to perceiving the preceding vehicles cut-out manoeuvre is defined by the amount of lateral movement(drifting amplitude),which is similar to the case with the aforementioned cut-in perception condition.Both the cut-in and cut-out are maneuvres to change lanes.Similar to the case of cut-in,the boundary condition using the distribution of drifting amplitude from the observation data of real traffic is applied to the perception condition of cut-out.Moreover,the time from the cut out perception to the recognition of the vehicle ahead that appears and the risk perception is defined as 0.4 sec based on the experimental data(Figure 17 and 18).15 Figure 22.Competent and careful human driver model(cut out)2.3.3.1.3.Deceleration Scenario A deceleration scenario takes into consideration the sudden deceleration of the leading vehicle that the ego vehicle is following.Although the previous cut-in and cut-out scenarios required the perceived lane change boundaries from the following or leading vehicle,the deceleration scenario only involves the longitudinal behaviour.Therefore,it is only necessary to define the deceleration perception time by the leading vehicle to evaluate the risk boundary.Similar to the preceding case,0.4 s can be applied as the time required to evaluate the risk.Figure 23.Risk evaluation boundary in deceleration scenario When the risk evaluation condition of the deceleration scenario is applied to the diagram in Figure 8,it results in Figure 24.Figure 24.Competent and careful human driver model(Deceleration)16 Definition of Parameters for Deriving Standard The following table lists the parameters required for deriving the safety standards for traffic disturbances.The evaluation scenarios related to traffic disturbances are generated by defining road geometry,the ego vehicles behaviour,and locations and motions of the surrounding traffic participants.The parameter items required in the evaluation scenario are categorized in a specific numerical range,and the Pass/Fail boundary is derived within that range.Table 2.List of traffic disturbance parameters.Operating conditions Roadway#of lanes=The number of parallel and adjacent lanes in the same direction of travel Lane Width=The width of each lane Initial condition Initial velocity Ve0=Ego vehicle Vo0=Leading vehicle in lane or in adjacent lane Vf0=Vehicle in front of leading vehicle in lane Initial distance dx0=Distance in longitudinal direction between the front end of the ego vehicle and the rear end of the leading vehicle in ego vehicles lane or in adjacent lane dy0=Inside Lateral distance between outside edge line of ego vehicle in parallel to the vehicles median longitudinal plane within lanes and outside edge line of leading vehicle in parallel to the vehicles median longitudinal plane in adjacent lines.dy0_f=Inside Lateral distance between outside edge line of leading vehicle in parallel to the vehicles median longitudinal plane within lanes and outside edge line of vehicle in front of the leading vehicle in parallel to the vehicles median longitudinal plane in adjacent lines.dx0_f=Distance in longitudinal direction between front end of leading vehicle and rear end of vehicle in front of leading vehicle dfy=Width of vehicle in front of leading vehicle doy=Width of leading vehicle dox=Length of the leading vehicle Vehicle motion Lateral motion Vy=Leading vehicle lateral velocity Deceleration Gx_max=Maximum deceleration of the leading vehicle in G dG/dt=Deceleration rate(Jerk)of the leading vehicle 17 2.3.3.1.4.Calculation of Boundary As discussed above,the specific standard value can be derived by the numerical calculation of the competent and careful human driver model.The parameter region for the standard value derivations are set to allow combinations of every parameter within the maximum vehicle velocity region allowed by the ADS to be targeted.2.3.3.1.4.1.Derivation result of the preventable boundary of cut-in scenario The safety standard of the cut-in is derived for every relative velocity between the ego vehicle and the counter vehicle.Collision with the cut-in vehicle is not allowed in the parameter region indicated by the green area in Figure 26.Figure 25.Conceptual diagram of cut-in scenario parameters Figure 26.Preventable boundary data sheet of cut-in scenario 18 2.3.3.1.4.2.Derivation result of cut-out scenario standard The cut-out safety standard requires that all decelerating(stopped),vehicles located ahead of the vehicle cut-out,must be able to avoid collisions.This standard is derived by making the aforementioned competent and careful human driver model follow the leading vehicle at THW=2.0 s.This value,i.e.,THW=2.0 s,is applied by referring to the laws and instructions of each country.Figure 27.Conceptual diagram of cut-out scenario parameters Figure 28.Preventable boundary data sheet of cut-out scenario 19 2.3.3.1.4.3.Derivation result of preventable boundary of deceleration scenario The safety standards for deceleration scenarios are required to enable avoidance of collision with the suddenly decelerating vehicle at 1.0 G or less or by stopping the vehicle.This standard is derived by making the aforementioned competent and careful human driver model follow the leading vehicle at THW=2.0 s.This value,THW=2.0 s,is applied by referring to the laws and instructions of each country.Figure 29.Conceptual diagram of decelerating scenario parameters Figure 30.Preventable boundary data sheet of decelerating scenario NOTE：Preventable boundary does not show up at 60 km/h or less because the braking force is sufficient.20 2.3.4.Safety evaluation method for perception disturbance The basic conception of safety standard is as follows:To avoid collisions in any of the traffic disturbance scenarios,even when experiencing perception disturbances.When considering that lane deviation can also contribute to collisions,the perception of objects is necessary to avoid collisions with objects on the runway(Fig.31).Moreover,there are two types of phenomena that result from the perception disturbance,namely,a false negative where the existing objects are not correctly detected,and a false positive where objects that do not exist are falsely detected(Figure32).Figure 31.Types of detection target Figure 32.Detection result caused by disturbance Difficult to detect target Difficult to detect lane 21 When these are combined,evaluations based on the concept of safety standards become necessary for four categories of situations in total(Figure 33).Figure 33.Four categories of detection disturbance situation The following is considered within the ODD region as the parameter region of perception disturbance to define an appropriate region for each disturbance factor.1:Road structure,Road Traffic Law and other regions defined by laws and regulations.(e.g.:When visibility is 50 m or less,the road is closed,i.e.,a level difference of 15 cm on the road surface must be repaired)2:Region that is determined to be possible at certain probability based on statistical data.(e.g.,precipitation,brightness,and sun altitude,etc)Moreover,this safety standard is not the performance standard allocated to an individual sensor.Instead,it should complement the entire recognition system installed.The above flow of safety perception can be summarized as follows.22 Figure 34.Safety assessment of perception disturbance detection flow 2.3.5.Safety evaluation method for vehicle disturbance A vehicle disturbance indicates sudden disturbances(e.g.puddles or sudden gust of wind).Although these are unpredictable phenomena,drivers can safely drive by following common sense related to road design,road maintenance/management and road environmental conditions.Thus,the premise of driving on common roads is that the roads are constructed by responsible public or private organisations which follow basic principles such as legality,ethics and engineering and are always maintained and managed.Most countries have road structure ordinances and guidelines for road maintenance and repair to ensure that the road geometry design enables safe driving by every person with a valid driving license(regardless of their driving skill,reflexes,or age).Moreover,when there is a risky situation,such as freezing or a sinkhole,that can hinder driving,the road administrator is obliged to warn the drivers in advance,e.g.,with a traffic sign.Based on these preconditions,a technical safety approach for foreseeable vehicle disturbances is introduced.As shown in Figure 6,collisions must be avoided in any of the traffic disturbance scenarios,even when experiencing vehicle disturbance.In the current standards,the collision avoidance strategy under the foreseeable and avoidable scenarios and collision mitigation strategies for predictable but unavoidable scenarios are of particular consideration.Henceforth,when a vehicle behaviour changes because of a vehicle disturbance within the scope of avoidable conditions,the AD vehicle is required to possess a controllability that can stabilise the vehicle without halting driving.However,when these disturbances cause instability that cannot be avoided,the AD vehicle must adapt to the best effort strategy to mitigate the possible collision.Figure 35 shows a specific example of the safety approach for foreseeable vehicle disturbances.The upper section of the figure represents an example of the AD vehicle experiencing a rapid decrease of sliding friction while staying within the avoidable conditions on a wet road;in such a state,the vehicle must be able to be safely controlled without interrupting the driving process.However,the lower section of the figure represents an example involving an AD vehicle equipped with summer tires encountering a frozen road,which causes a rapid decrease of sliding friction and generates a vehicle state that was defined to be unavoidable in advance(e.g.,maximum deceleration).Therefore,the safety approach toward vehicle disturbances is based on the principle and clear definitions of vehicle motion engineering related to the definitions of the states where the vehicle is controllable and the states where the vehicle is uncontrollable.(Section 4.3.3 for detail).23 Figure 35.Safety approach for avoidable(above)and unavoidable(below)vehicle disturbance When these considerations are combined with traffic disturbances,the safety of the AD vehicle does not affect the test result if the stability of the vehicle is maintained.Moreover,while wind affects other vehicles,it only influences the lateral velocity as with cut-in,and it is included in the original traffic flow parameters.The safety standards for vehicle motion disturbances are evaluated relatively without including the vehicle disturbance to the traffic flow scenario.Therefore,the safety standards for vehicle disturbances only need to set the most strict condition under the premise that the Road Traffic Act is strictly adhered.Drivers are responsible for the maintenance of their vehicles,the road administrator is appointed as per the Road Traffic Act,and roads are managed and operated according to the Road Structure Ordinance and guidelines for road maintenance and repair,and perception standards do not departing from the road surface.As an example,the disturbance factors and conditions for motorways in Japan(refer to 4.3.3.8 for general roads)are listed below:Road surface state:Friction coefficient is 0.3(lock)or more,external force on the tires is at the set point of the road maintenance and repair or less(e.g.:rut:25 mm,level difference:30 mm,pothole:20 cm)Road geometry:Curve within the regulation of the road structure ordinance,i.e.,R=460 m,vehicle velocity is 100 km/h Natural phenomena:Wind speed of lateral wind without speed control is 10 m/s,i.e.,vehicle velocity is 100 km/h As the most difficult condition here is when the abovementioned disturbances all simultaneously occur,these three factors are added up for evaluation(Figure 36).24 Figure 36.Vehicle motion disturbance evaluation conditions The perception condition under this situation is to avoid departure from the lane.Here,the cases where the vehicle cannot drive under these conditions(e.g.,when lateral wind is 5 m/s or more,i.e.,driving is not possible)must be defined in advance as ODD by the manufacturer.Furthermore,as a functional requirement,the slow puncture that occurs while driving should be managed before the vehicle becomes uncontrollable(before the rim touches the surface of the road).The summary of the flow of safety perception discussed to date is listed below.Figure 37 Safety perception flow of vehicle motion disturbance 25 3.Scenario-Based Safety Assurance Process Figure 38 shows the schematics for the overall safety argumentation system in development and production cycle based on the V-shaped model,which is the project management commonly appointed to the development of advanced driving assistance systems(ADAS)and AD systems.By integrating verification to the sensor setup assessment and software agility basement processes from the planning phase in the first half of development,rather than conducting it only during the latter half of development represented by the right side of the V-shape,it can contribute to the optimisation of the development.Figure 38.Overall scheme of safety assurance process 3.1.Safety argumentation scheme(Steps of the V-shaped model)3.1.1.Item definition The safety argumentation process is for making the vehicle compatible with the safety target within the operation scope of the automatic driving vehicle that was determined in advance.The operation scope of automatic driving vehicles is defined at the initial stage as the operation design scope(ODD).The contents of the ODD must include,at a minimum,information such as the road type,position on the road,vehicle velocity scope and environmental condition.Moreover,a fallback strategy for transition to outside the ODD boundary must be designed;moreover,the AD system must detect whether it is operating within the defined ODD.The definition of OD must be structured in such a manner as to enable notification to the users,as well as allow them to understand,trust and operate the AD system(Khastgir,Birrell,Dhadyalla,&Jennings,2018).Note that by mapping the ODD system and the scenario system as shown in Figure 39,it becomes possible to select the evaluation scenario following the ODD range.Safety Design&ConceptSafety AnalysisSystemDevelopmentSubsystem and vehicle V&VSafety AssessmentSocially acceptable top safety goals defined by authorities Item DefinitionTest scenario DBBConvertConvertFunctional ScenarioTest CaseConcreteScenarioLogicalScenarioTraffic Environment DataParameterrangeParameterDistributionProcessProcessExpert knowledgeFinal development sub-process before customer operationForeseeable Coverage goalsPreventable Coverage goalsIncident management 26 Figure 39.ODD scenario classification and relationship diagram of the system level classification based on the three category scenario level 3.1.2.Safety Analysis It is important to determine as many foreseeable scenarios as possible,as well as systematise detailed scenario-related information on the operation design scope(ODD),vehicle and its surrounding,technically comprehensive definition of ODD based on the system physics,in addition to the overall definition of ODD that employs the systematic combination approach.For instance,the word rain is enough for communicating with the user if rainfall conditions are included in the ODD;however,the AD system itself cannot interpret such a concept in the same manner.This scenario is able to consider the influence of rain from the perspective of system physics instead such as the possibility of the influence of raindrops on the sensor performance or the influence of rain on the vehicle dynamics(e.g.,decrease in friction coefficient between the tire and the wet road surface).To describe ODD in a technical and system-oriented way,it is classified into three categories related to the system physics in order.These categories cover the respective perception,traffic flow and vehicle disturbances that can potentially occur within the AD system safety analysis(Figure 2).3.1.3.Safety Design and Safety Concept The system requirements should be produced based on the safety analysis steps.The safety target defined by our association is integrated into the development cycle during this process,as well as confirmed during the system design.As layers of different complexity are added to the safety design,the safety analysis cycle can be unified as per necessity between this process and the preceding process as long as their outputs follow the safety analysis steps.It is important to ensure compatibility between the ODD and the system requirements to avoid unnecessary specification changes in the system development process.This indicates the importance of the role of the safety analysis step.3.1.4.System development When the system design is complete and its safety is analysed,the actual system that includes the component elements of both software and hardware is developed.27 3.1.5.Examination and validation of the sub-system and the vehicle At this point,the strategy for safety examination and validation of the system and the vehicle is defined without interaction with the driver.The examination and validation are conducted by combing concentrated virtual evaluations and a relatively limited amount of physical tests in real traffic environments and at test courses.The mathematical and physical accuracy of the system,development functions,and employed safety measures are verified in the sub-process of the examination.Moreover,verification is performed in regard to whether all the safety specifications and requirements drawn up during the safety analysis process(sufficiency of sensors,algorithm and actuator-related measures)have been satisfied.For the validation sub-process,verification is performed in terms of whether the system and components,including the employed safety measures,pose an irrational risk to the traffic participants.Moreover,the safety of the AD system is substantiated by confirming that the defined validation targets were met.3.1.6.Safety assessment The test for determining whether the end product is acceptable is conducted during this step,which includes the related inspections,document checks and certifications.3.1.7.Final check process before release In the final check before release,verification is performed in terms of whether the safety of the AD system can be explained,in addition to whether the remaining risk is within the permissible range.This can be conducted by,e.g.,using technologies such as the behaviour safety assessment(BSA),which focuses on the evaluation of the AD system at each test case by applying different measurement standards and confirms the compatibility of AD with predefined behaviour standards.Finally,a determination is made in terms of whether the system can be released during the review of the result,and then the post-release incident management strategy is designed.3.1.8.Incident management During the incident management process,the performance data is fed back into the safety argumentation process.This enables the improvement of the AD technology and reduces the number of unforeseeable situations as time passes.It is expected that,because of this reduction,the threshold between two left quadrants shifts,as well as the boundary between them will be lesser in the way that is beneficial to the foreseeable scenarios(Figure 40).Following the same logic,it is expected that the boundary between the preventable scenarios and unpreventable scenario shifts rightward,and the quadrant on the upper left will expand.It is highly possible that this will occur as more scenarios become preventable.Figure 40.Expansion of foreseeable and preventable scopes following the evolution of the AD system ForeseeableUnforeseeablePreventableUnpreventableScenario based approach for No accidentSocial acceptance or resilience Support for residual social risk Best effort functionality to mitigate the accidentLearning process based in field monitoring PreventableBoundaryBoundaryForeseeableUnforeseeableBoundaryUnpreventableBoundarySocial acceptance or resilience Support for residual social risk Best effort functionality to mitigate the accidentLearning process based in field monitoring Scenario based approach for No accident 28 4.Scenario structure Every approach is constructed by applying the systematic combination approach for defining the combinations derived from all possible factors.This approach requires significant specialized effort for defining all the factors and their interdependency as was the case by examining the safety coverage target.Therefore,it requires a systematic standardization methodology for structuring every factor related to the information.As mentioned earlier,the structures of the scenarios are the possible disturbances that can occur in three different categories related to the physics of the system,namely,the perception disturbance,traffic disturbance and vehicle motion disturbance.4.1.Traffic disturbance scenario Traffic disturbance scenarios are classified as general vehicle scenarios(including automobile and motorcycles),motorcycle-specific scenarios,and vulnerable road user scenarios(Figure 41).These three scenario classifications are further generated by systematically analyzing and classifying the combinations of different factors,namely the road geometry,ego-vehicle behavior,and the locations and motions of the surrounding traffic participants(Figure 42).Figure 41.Traffic disturbance scenario classification Figure 42.Structure of a traffic disturbance scenario NOTE：The vulnerable road user scenario will be included in the next version.4.1.1.General vehicle scenario For traffic disturbance scenarios involving general vehicles,we provide specific explanations for the road geometry,ego-vehicle behavior,and the locations and motions of the surrounding traffic participants.4.1.1.1.Road geometry category The standard road is a non-intersection road (a).Merge zones(b)are formed when another road merges into a single road.When a single road splits,a branch zone(c)is formed.Furthermore,when one straight road intersects another straight road,an intersection(d)is formed(Figure 43).These roads are combined to form various types of roads.Motorways are classified into three categories:main roads(non-intersection),merge zones,and branch zones,with intersections being excluded.The road scenario classification for scenario generation must be also discussed to make it applicable to highways internationally(Association,2004)(Transportation,2008;UK,2006).29 NOTE：Another type of road shape is a roundabout.For this,we must either consider a combination of merging and branching roads or prepare a separate scenario.In addition,we intend to include another Annex that considers parking lots and trams,among other scenarios.Figure 43.Road geometry classifications 4.1.1.2.Vehicle behavior category Vehicles move in a straight line along the lanes of road geometry(a)(also known as lane keeping).In addition,vehicles move between lanes from an adjacent and merging lane(b)(lane change).Here,while a lane change from an adjacent lane and a merging lane have different road geometry categories,as vehicle behaviors,both are considered to be lane changes.At intersections,the vehicle turns without changing lanes(right or left turn).Therefore,the possible vehicle behaviors are classified into three categories:going straight,lane change,and turning.This vehicle behavior category is expressed using a combination of the road geometry information discussed above(Figure 44).NOTE：In addition to right and left turns,there is also the U-turn as a turning behavior,but the ADS will not perform a typical U-turn;however,if a road is designed for U-turns,it is treated as a merge zone.Figure 44.Parameters of road geometry and vehicle behavior 4.1.1.3.Categories of positions and motions of surrounding vehicles Moreover,when there is a significant difference between the speeds of the leading vehicle and the vehicle in front of it,the leading vehicle might perform cut-out to avoid a collision.When a cut-out suddenly occurs,the ego vehicle might be required to take action to avoid a collision.To consider this scenario,the position of the vehicle in front of the leading vehicle is indicated as“ 1”(Figure 45).30 The neighboring positions in six directions around the ego vehicle that have a possibility of entering the driving trajectory of the ego vehicle,the left and right when entering from an intersection,and three oncoming directions,for a total of eleven directions,define the surrounding vehicles positions that must be considered in a scenario structure.Moreover,if the speed difference between the leading vehicle and the vehicle in front of it is significant,the leading vehicle may perform a lane change(cut-out*1:Figure 46)to avoid a collision.If there is a sudden lane change,the ego vehicle may need to take action to avoid a collision.To account for such a scenario,the position of the vehicle in front of the leading vehicle is considered and indicated as“ 1”(Figure 45).An oncoming vehicle may also enter the lane of the ego vehicle by performing a lane change(mark under cut-in*2:Figure 46).Figure 45.Positions of surrounding vehicles 31 Figure 46.The combination of the surrounding vehicle positions and the motions that can potentially obstruct the ego vehicle NOTE：In Ver 2.0,we placed other vehicles next to the ego vehicle;however,it has been eliminated.The reason for this is that the positions next to the ego vehicles would be covered depending on the initial positions of the vehicles in the front and rear(e.g.,positions 3 and 4),.The behaviors of the surrounding vehicles are classified into three categories:going straight(acceleration/deceleration),lane change(cut-in/cut-out)and swerving(e.g.,behavior to avoid a stopped vehicle),and turning(right and left turn,U-turn).From a safety evaluation perspective,it is possible to minimize the number of evaluations by focusing on the behaviors of other traffic participants that have the potential to obstruct the behavior of the ego vehicle(Figure 46).For instance,the turning of the vehicle in position 2 does not interfere with the ego vehicle;thus,it can be excluded from the safety analysis.The check mark in the figure indicates cases where the corresponding combinations of the surrounding vehicle positions and motions can potentially impact the driving of the ego vehicle,which must be considered in the safety analysis.4.1.1.4.Resulting traffic disturbance scenarios As a result of the systematization process discussed thus far,a methodology for structuring scenarios as a combination of the road geometry,the behavior of the ego vehicle,and the position and motion of the surrounding vehicles is proposed herein.This structure consists of a matrix that contains 58 possible combinations in total(Figure 47).When limited to motorways as an example,there are three categories for the road geometry:“straight roads,”“merging zones,”and“branching zones;”two categories for the ego-vehicle behavior:“going straight”and“lane change;”and two categories each(total four)for the positions and motions of the surrounding vehicles:“going straight(acceleration/deceleration)”and“lane change(cut-in/cut-out).”The motorway scenarios consist of a matrix with 24 possible combinations that could occur in a real traffic flow(Figure 48).Based on the similar accident categories,the sufficiency of these 58 cases,which cover all the dangerous cases that can lead to an accident,can be evaluated(Annex D).This matrix deals with comprehensive coverage of traffic disturbances resulting from interactions between two vehicles.The scenarios described here as traffic disturbance scenarios(Figures 47 and 48)are representative and must be able to consider a combination of the surrounding vehicle positions and behaviors that could obstruct the ego vehicle(Figure 46).For example,Figure 49 presents the results of a scenario developed for Figure 48(Nos.5,32 6,7,and 8)where the road geometry consists of a single road,the ego vehicle behavior involves a lane change,and the motion of surrounding vehicles involves going straight and performing a lane change.To elaborate on No.5,when the ego vehicle makes a lane change,cases where the surrounding vehicle is in front,situations in which the surrounding vehicle is in the front,the rear,or the side(i.e.,the vehicle in the front or rear is beside the ego vehicle)must be considered.The routes that could lead to obstructions will differ when the number of lanes is different,even if the positions of the nearby vehicles remain the same.As a result,it is important to consider the positions of the surrounding vehicles and the number of lanes,as well as identify combinations of behaviors that could obstruct the ego vehicle.33 Figure 47.Traffic disturbance scenarios for general vehicles Road sectorOn comingOn comingOn comingGoing straight(Lane keep)No1No2No3No4No5No6No7No8Lane changeNo9No10No11No12No13No14No15No16Going straight(Lane keep)No17No18No19No20No21No22Lane changeNo23No24No25No26No27No28Going straight(Lane keep)No29No30No31No32No33No34Lane changeNo35No36No37No38No39No40Going straight(Lane keep)No41No42No43No44No45No46No47No48No49TurningNo50No51No52No53No54No55No56No57No58Surrounding traffic participants location and behaviourSubject-vehiclebehaviorGoing straightLane change/SwervingTurningSame/Crossed(from R/L)directionSame/Crossed(from R/L)directionSame/Crossed(from R/L)directionRoad sector and subject-vehicle behaviournon-intersectionMerge zoneBranch zoneIntersectionSubject vehicleSurrounding vehicleSurrounding vehicle( 1)34 Figure 48.Traffic disturbance scenarios for general vehicles on motorways 35 Figure 49.Scenarios with various combinations of positions of the surrounding vehicles and behaviors that could obstruct the ego vehicle 3636(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.4.1.2.Scenarios unique to motorcycles In general,the categories of aforementioned positions and motions of surrounding vehicles(Figure 44)are applied to both four-wheeled vehicles and motorcycles.However,there are situations where motorcycles may drive in the narrow space in the same lane as the ego vehicle,which requires additional safety evaluation scenarios.Because these scenarios only have the potential to occur in countries where such driving is legally allowed,an approach including detailed examples is shown in Annex B.4.1.3.Scenarios resulting from the combination of behaviours by several vehicles The proposed traffic disturbance scenario structure covers the relationship between the ego vehicle and one or two surrounding vehicles.However,in real traffic,multiple traffic participants take diverse actions at various moments.The current methodology covers these complex cases by extracting scenarios where the sudden motions by surrounding vehicles trigger the sequence of avoidance motions.By dividing these scenario types into a sequence of behaviours,multiple combinations of the positions and motions of the ego vehicle and the surrounding vehicles can be covered by safety analysis.Moreover,this can be realized by considering the influence of the road environment on the cut-in scenario by other vehicles that can potentially appear in this sequence.For instance,when the leading vehicle performs sudden deceleration(the first behaviour of the sequence),the avoidance motion by the ego vehicle occurs(the second behaviour)and the ego vehicle retreats into the surrounding avoidance area.The detail of the approach to the complex scenarios that include detailed examples is included in Annex C.3737(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.4.2.Perception disturbance scenarios Perception disturbance scenarios include blind spot scenarios and connectivity disturbance scenarios,in addition to perception disturbances(Figure 50).Figure 50.Categories of perception disturbance scenarios 4.2.1.Perception disturbance scenarios Perception disturbance refers to a negative effect on perception performance during a situation in which the automatic driving system detects objects.The perception disturbance scenario is generated by disturbance-triggering factors and based on the principle of the sensors where disturbance occurs.While the factors of disturbances are diverse,it is possible to select the scenario group that contains the perception disturbance overall by classifying the factors based on the generation principle and then selecting a representative factor among those in the same category.Moreover,by considering the necessary combinations based on the generation principle of each disturbance factor,it is possible to create a perception disturbance combination evaluation scenario.In this study,the disturbance scenarios of three types of sensors,namely,millimetre wave radar,LiDAR and camera(Figure 51).3838(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Figure 51.Scenario derivation process based on perception disturbance factors and sensor principle 4.2.1.1.Perception disturbance factors The factors of perception disturbance can be broadly classified into“vehicle/sensor,”“surrounding environment”and“perception target”in relation to the ego vehicle,which are then broken down and comprehensively classified at each layer to compose the perception disturbance factors system.Here,e.g.,a factor is broken down from the perspectives of structure,relative position and types,and continues to be categorized to layers such as colour,shape,material and behaviour.3939(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Figure 52.Broad categories of perception disturbance factors according to the positional relationship with the ego vehicle Figure 53.System diagram of perception disturbance factors 4040(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.4.2.1.1.1.Perception Disturbance Factors:Vehicle/Sensor The perception factors classified into“vehicle/sensor”are divided into three categories according to the positions of these factors,namely,“a.ego vehicle”,“b.sensor”and“c.in front of the sensor”.Figure 54.Vehicle/sensor categories Tables 35 show the details of the perception disturbance factors categorized into a,b and c.These tables describe the detailed categorization,impact on the perception performance,and the generation principle of perception disturbance of the perception disturbance factors for each sensor.Table 3.“a.Ego Vehicle”disturbance factors 4141(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 4.“b.Sensor”disturbance factors Table 5.“c.In front of sensor”disturbance factors 4.2.1.1.2.Perception disturbance factors:Surrounding environment The perception factors classified into“surrounding environment”are divided into three categories according to the characters of the objects existing around the ego vehicle,namely,“d.surrounding structure”,“e.space”and“f.surrounding moving objects”.“d.Surrounding structure”is further divided 4242(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.into the following three categories:“d-1.road surface”,“d-2.structure by the road”and“d-3.structure above the road”.Figure 55.Surrounding environment categories Tables 68 show detailed categorization,impact on the perception performance,and the generation principle of perception disturbance of the perception disturbance factors classified into d-1,d-2,d-3,e and f.4343(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 6.“d-1.Road surface”disturbance factors Table 7.“d-2.Structures by the road”disturbance factors 4444(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 8.“d-3.Structures above the road”disturbance factors Table 9.“e.Space”disturbance factors 4545(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 10.“f.Surrounding moving objects”disturbance factors 4.2.1.1.3.Perception Disturbance Factors:Perception Targets of Sensors The perception disturbance factors categorized as“perception targets of sensors”are broadly classified into“g.route”,“h.traffic information”,“j.obstacles”and“k.moving object”(Figure 56).Figure 56.Categories of perception targets of sensor “g.Route”is classified into“g-1.lane maker”,“g-2.structure with height”and road edge as per the object that indicates a given place is a driving route.Moreover,road edge is divided further into g-3 and g-4 depending on whether there is a level difference or not(Figure 57).4646(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Figure 57.Categories of“g.route”“h.Traffic information”is classified into“h-1.traffic light”,“h-2.traffic sign”and“h-3.road marking”as per their display style(Figure 58).Figure 58.Categories of“h.traffic information”“j.Obstacle”is classified into“j-1.falling object”,“j-2.animal”and“j-3.installed object”according to whether it moves or not and the degree of impact when colliding with the vehicle(Figure 59).Figure 59.Categories of“j.obstacle”4747(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.“k.Moving objects”are classified into“k-1.other vehicles”,“k-2.motorcycle”,“k-3.bicycle”and“k-4.pedestrian”as per the type of traffic participant(Figure 60).Figure 60.Categories of“k.moving objects”Tables 1114 show the detailed categorization,impact on the perception performance,and the generation principle of perception disturbance for the perception disturbance elements classified into g-1 to k-4,respectively.Table 11.“g-1.Lane marker”disturbance elements 4848(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 12.“g-2.Structure(with height)”disturbance elements Table 13.“g-3.Road edge without level difference”disturbance elements Table 14.“g-4.Road edge with a step”disturbance elements 4949(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 15.“h-1.Traffic lights”disturbance elements Table 16.“h-2.Traffic sign”disturbance elements Table 17.“h-3.Road marking”disturbance elements Table 18.“j-1.Falling object”disturbance elements 5050(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 19.“j-2.Animal”disturbance elements Table 20.“j-3.Installation object”disturbance elements Table 21.“k-1.Other vehicles”disturbance elements 5151(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 22.“k-2.Motorcycle”disturbance elements Table 23.“k-3.Bicycle”disturbance elements Table 24.“k-4.Pedestrian”disturbance elements 4.2.1.2.Generation principle of sensor perception disturbance The sensor can potentially experience perception disturbance when detecting objects because of the factors discussed in the preceding section.While the principle of perception disturbance generation is different for each sensor,they can be categorized as per the following common perspectives.5252(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.The sensor disturbance principles are classified into“those occurring due to perception processing”,“those occurring due to cognitive processing”and“others”.The disturbances occurring because of perception processing are classified into those related to the signal from the perception target(S)and those that hinder the signals from the perception target(noise N,unnecessary signal U).List the disturbances that can occur on signals individually related to S,N and U.The examples of categories of generation principles of perception disturbances that could occur on each sensor based on these perspectives are as follows.Generation principle of perception disturbance of millimetre-wave radar.The perception disturbances that occur on millimetre-wave radar includes those caused by the direction of the sensor,those occurring because of perception processing and those occurring because of cognitive processing(Figure 61).Figure 61.Categories of perception disturbances for millimetre-wave radar In particular,the physical quantities that characterize the signal S in perception processing of millimetre-wave radar are the following three:frequency,phase and strength(Figure 62).-Frequency:Problem with the signal frequency can be cited as a disturbance originating from the sensor itself.-Phase:There are cases where the direction the signal is arriving from changes and cases where the amount of propagation delay changes,and the changes in signal arrival direction are attributed to reflection and refraction.5353(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.-Signal strength:The conceivable situations include partial signal loss,a signal that is too strong,a large difference in signal strengths,and the signal being too weak.Furthermore,possible disturbances in regard to the noise N and the unnecessary signal S in perception processing include low S/N,low D/U(ratio of strength between the necessary signal D and unnecessary signal U)and increase of U.Figure 62.Generation principle of disturbance in millimetre-wave radar perception processing Generation principle of LiDAR perception disturbance The physical quantities that characterize the signal S in perception processing of LiDAR are the scan timing,strength,propagation direction and velocity.-Scan timing:The time difference because of the movement of the ego vehicle leads to positional shifts in the overall space;moreover,the time difference caused by the movement of the perception target leads to its positional shift.-Strength:Phenomena include saturation,attenuation and shielding.-Propagation direction change:There are those caused by reflection and those caused by refraction.-Velocity:While it affects the arrival time of signals,there are no corresponding items in perception disturbance of LiDAR.Furthermore,the noise N and unnecessary signal U include reflection and refraction from objects other than the perception target,in addition to DC noise,pulse-like noise and multiple reflections(Figure 63).5454(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Figure 63.Generation principle of disturbance at perception of LiDAR Generation principle of perception disturbance at the camera The physical quantities that characterize the signal S in perception processing of the camera are the strength,direction/range signal change and acquisition time.-Strength:There are cases where the signal is too weak,the signal is too strong,the difference in signal strength is large and the signal is partially lost.-Direction/range:There are changes caused by refraction and changes caused by reflection.-Changes in the signal S.-Acquisition time:The possible cases of disturbances caused by blinking of the perception target and changes in relative positions include flickering and image blur/deletion.5555(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Furthermore,the noise N and unnecessary signal U include low D/U and low S/N(Figure 64).Figure 64.Generation principle of disturbance in camera perception 5656(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Scenario selection through cross-checking of perception disturbance elements and generation principle The relationship between the elements of perception disturbance at each sensor and the generation principles can be represented in the matrixes shown in Tables 2527.These matrixes list the perception disturbance elements vertically and generation principles horizontally,which makes it possible to understand the elements(=line)that can potentially cause the generation principle(=column).The several disturbance elements that can be reported in the same column are generated by the same principle.However,from the perspective of a system safety evaluation,it is possible to select the elements whose degree of influence on the perception performance of each sensor and encounter probability in the market are high,as well as prioritize them as evaluation scenarios.When there are several elements that have the equal priority,one or several elements are selected while taking the reproducibility of the evaluation environment of that scenario into account and evaluating the same.Moreover,when there are disturbance elements that do not match the given sensor among the items represented in the vertical axis because of the specifications of the ADS under evaluation(such as ODD and perception target),exclude them and select the representative scenario among the remaining elements.5757(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 25.Perception disturbance elements and generation principle matrix of millimetre-wave radar Small impactMedium impactGreat impactReflection(indirect wave)RefractionAliasingHarmonicLow S/N(change ofangle)Low S/N(attenuation atthe sensorsurface)Low S/N(attenuation inspace)Low S/N(lowretroreflection)Low D/U(change ofangle)Low D/U(road surfacereflection)Low D/U(surroundingstructures)Low D/U(floatingobjects inspace)Low D/U(sensors onother cars)Low D/U(sensors onego cars)Increasing of U(change ofangle)Increasing of U(road surfacereflection)Increasing of U(surroundingstructures)Increasing of U(floatingobjects inspace)Increasing of U(sensors onother cars)Increasing of U(sensors onego cars)Lack of points to beprocessedLack of calculatingabilityFalse detection of undesiredsignalNo detection of requiredsignalUnexpected distribution of point cloudUnexpectedmovements(betweenframes)UnexpectedobjectsClassificationdiffuse reflectance,shape,positionrefraction range,misalignment,failure of sensoritselfpropagation delayrange,misalignment,failure of sensoritselfshape,positionretroreflectioncoefficient,targetposition,failure of sensoritselfretroreflectioncoefficient,targetposition,failure of sensoritselfretroreflectioncoeffieicent(RCS),3D shape,targetcombination,relative positionchange of angle,change of vehicleposture,roadgradient,misalignment,failure of sensortransmittivity,range,failure of sensoritseldattenuation rate inspaceretroreflectioncoeffieicent(RCS),3D shape,targetcombination,relative positionchange of angle,change of vehicleposture,roadgradient,misalignment,failure of sensorretroreflectioncoeffieicent,diffuse reflectanceretroreflectioncoefficient,targetpositionretroreflectioncoefficient,attenuation rate inspacetype of sensors onother vehicle,positiontype of sensors,mounting position,surroundingenvironmentchange of angle,change of vehicleposture,roadgradient,misalignment,failure of sensorretroreflectioncoeffieicenretroreflectioncoefficient,targetpositionretroreflectioncoeffieicentype of sensors onother vehicle,positiontype of sensors,mounting position,surroundingenvironmentcaused by vehicle situation(semiparmanent)lack of tire pressure,etc.false positive,false negative8caused by vehicle situation(tempoal)change of load distribution inside a carfalse positive,false negative8degradation of sensor surface(a level of fault detection failure)false positive,false negative6degradation of sensor itself(electric parts)(a level of fault detection failure)false positive,false negative6Lowering of electric perfoemance by exogeneous noise(a level of fault detection failure)false positive,false negative2misalignment(within adjustment range)(failure of misalignment detection)false positive,false negative5misalignment(out of adjustment range)(untill detection of misalignment)false positive,false negative5water x homogeneousfalse negative1water x SPOT(drop)false positive,false negative3ice x evenfalse negative1ice x SPOT(ice grain)false positive,false negative3snow x even(ex.after blizard)false negative1snow x SPOT(snow grain)false positive,false negative3dryclay/dirt x evenfalse negative1dryclay/dirt x SPOTfalse positive,false negative3wetclay/dirt x evenfalse negative1wetclay/dirt x SPOTfalse positive,false negative3car washing wax x evenfalse negative1car washing wax x SPOTfalse positive,false negative3foreign materials(bug,droppings)x SPOTsticking of uneven bugs on the surfacefalse positive,false negative3broken surface of the sensorcrack,etc.false positive,false negative3broken surface of the sensorstrainfalse positive,false negative3exchange of sensor surface material(variability after aiming)false positive,false negative3snow(a few)lowering of visibilityfalse positive,false negative3snow(a lot/blizard)bad visibilityfalse positive,false negative3snow(kicked up)partially low visibilityfalse positive,false negative3rain(a few)lowering of visibilityfalse positive,false negative3rain(a lot)bad visibilityfalse positive,false negative3rain(kicked up)partially low visibilityfalse positive,false negative3sand(a few)lowering of visibilityfalse negative1sand(a lot)bad visibilityfalse negative1sand(kicked up)partially low visibilityfalse positive,false negative3fog(a little)lowering of visibilityfalse negative1fog(dense)bad visibilityfalse negative1othersfloating of kinds of seedsfalse positive,false negative3bugs(floating)swarming overfalse positive,false negative3direct x other vehicleother vehicle ego vehiclefalse positive,false negative2diret x infrastructureOrbis,etc.0direct x naturethe sun,etc.0diffracted wave x ego vehiclediffraction of other sensors on the ego vehiclefalse positive,false negative2rising slopefalse positive,false negative3descending slopefalse positive,false negative3road with cantfalse positive,false negative3puddledifference of reflectance concave regionfalse positive,false negative2iced roaddifference of reflectance less bumpsfalse positive,false negative2fixed roadlineally,after fixing of convex regionfalse positive,false negative2rutconcave surface pararell to lane markersfalse positive,false negative2accumulated snowdifference of reflectance a lot bumpsfalse positive,false negative2asphaltdefault,less bumpsfalse positive,false negative2concretedifference of reflectance,middle level of bumpsfalse positive,false negative2ballastdifference of reflectance,a lot of bumpsfalse positive,false negative2sanddifference of reflectance,a lot of bumpsfalse positive,false negative2thin layerdifference of reflectance,less bumpsfalse positive,false negative2stone pavementdifference of reflectance,a lot of bumpsfalse positive,false negative2maintainance holedifference of reflectance,SPOTfalse positive,false negative2joint(metal)difference of reflectance,SPOTfalse positive,false negative2joint(asphalt)difference of reflectance,SPOTfalse positive,false negative2crash barrierfalse positive,false negative5buildingfalse positive,false negative5ridge railfalse positive,false negative5road signage boardfalse positive,false negative4noise barrierfalse positive,false negative5rubber polefalse positive,false negative2ropefalse positive,false negative2boardfalse positive,false negative5roadside treesfalse positive,false negative2low treesfalse positive,false negative2grassfalse positive,false negative2buildingfalse negative1wallfalse negative1othersfalse negative1bridgefalse positive,false negative2tunnelfalse positive,false negative2buildingfalse positive,false negative2road signage boardfalse positive,false negative2mirrorfalse positive,false negative2boardfalse positive,false negative2traffic lightfalse positive,false negative2traffic lightfalse negative1road signage boardfalse negative1information boardfalse negative1Reflectionfalse positive,false negative5color,materialfalse negative2large reflectionlarge signal intensityfalse positive,false negative3small reflectionsmall signal intensityfalse negative2dirtfalse negative2relative positionfalse negative2color,materialfalse negative2Shapefalse negative2dirtfalse negative2relative positionfalse negative2color,materialfalse negative2Shapefalse negative2dirtfalse negative2relative positionfalse negative2color,materialfalse negative2Shape,sizefalse negative2relative position,motionfalse negative2Shape,sizefalse negative2relative position,motionfalse negative2color,materialfalse negative2large reflectionlarge signal intensityfalse positive,false negative3small reflectionsmall signal intensityfalse negative2dirtfalse negative2relative positionfalse negative2color,materialfalse negative2large reflectionlarge signal intensityfalse positivefalse negative3small reflectionsmall signal intensityfalse negative2Sticking objectsfalse negative2relative position,motionfalse negative2color,materialfalse negative2Shape,sizefalse negative2Sticking objectsfalse negative2relative position,motionfalse negative2color,materialfalse negative2Shape,sizefalse negative2Sticking objectsfalse negative2relative position,motionfalse negative2color,materialfalse negative2Shape,sizefalse negative2relative position,motionfalse negative261314612123981713368141991181419911566118118118118number ofitemsSignal from perception target(S)Signal from othersProcessing abilityProcessing performancePhaseClassification(Identification of target)Change of DOAChange ofpropagationdelayHigh intensityLarge differnceof signalLow S/NDetection(Output of reflected point cloud of target)Clustering(grouping of reflected points)Tracking(tracking of target)Mounted place/statusIncreasing of UStrengthNoise(N)Undesired signal(U)Causal Factors of Perception DisturbancesPerception processVehicle motionEgo vehicleChange of vehiclepostureClassification of Causal FactorsLow D/UNo signal(partial)ReflectionRecognition processOverheadobjectFront surface ofthe sensorFront surface of thesensorSticking objectsChanges incharacteristicsPropagation ofradio wave inspaceSpaceSpatial obstaclesRadio wave andlight in spaceCar/SensorSurrounding environmentsRadarSensorFailure of sensoritselfPedestriansVariation inassenblyLaneReflectionScreenSurrounding movingobjectsStructurewith heightshapeRoad edgewithout stepRoad edgewith stepStructural objectsRoad surfaceShapeRoadsideobjectnumber of itemsRecognition targetsAnimalsInstallationobjectsShape,sizeOthervehiclesShape,sizeMotorbikesFallenobjectsEnvironment/TargetRoad conditionMaterialScreenObstruction on the laneMoving objectsBicyclesItemsVariableParameters 5858(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 26.Perception disturbance elements and generation principle matrix of LiDAR Small impactMedium impactS SpeedN factorClusteringTrackingClassificationGreat impactMisalignment ofoverall spatialpositionMisalignment ofposition ofrecognition targetSaturation of SAttenuation of SNo S due toocclusionReflectionRefractionArrival time of SNoiseMultiplereflectionsSignals not fromrecognition target(reflection)Signals not fromrecognition target(refraction)Insufficientnumber ofprocessing pointsInsufficientcomputingcapabilityIncorrectlydetects U(undesired signal)Fails to detect S(desired signal)Unexpecteddistributionof pointcloudbeing recognizedUnexpectedrecognitionbehavior(between frames)Unexpectedrecognition oftargetdue to vehicle condition(semi-permanent)misdetected/undetecteddue to vehicle condition(temporary)misdetected/undetectedaxial deviation(inside adjustment range)misdetected/undetectedaxial deviation(outside adjustment range)misdetected/undetecteddegradation of sensor surfaceundetecteddegradation of sensor itself(electronic components)undetecteddegradation of electrical performance due to external noisemisdetected/undetectedwaterundetectediceundetectedsnowundetectedmud/dustundetectedcar wash waxundetectedforeign matter（insects,bird droppings）x SPOTundetectedsensor surface damage(cracks)undetectedsensor surface damage(distortion)undetecteduphilldownhillroad cantpuddlemisdetectedfrozen road?misdetectedtraces of road repairrutsnow coverasphaltconcretegravelsandthin layer pavementcobblestone roadmanholeroad joint(metal joint)road joint(asphalt type joint)Reflectioncurve mirrormisdetectedOcclusionundetectedReflectioncurve mirrormisdetectedOcclusionundetectedsnowmisdetected/undetectedrainmisdetected/undetectedsandmisdetected/undetectedfogmisdetected/undetectedothers/floating in spacemisdetected/undetectedinsects/floating in spacemisdetected/undetecteddirect wave x other vehiclemisdetected/undetecteddirect wave x infra-structuremisdetected/undetecteddirect wave x nature worldmisdetected/undetectedReflectionmisdetectedColor/MaterialsundetectedShapesundetectedGrime/Thin spotundetectedRelative positionundetectedColor/MaterialsundetectedShapesundetectedGrimeundetectedRelative positionundetectedColor/MaterialsundetectedShapesundetectedGrimeundetectedRelative positionundetectedColor/MaterialsundetectedShapesundetectedGrimeundetectedRelative positionundetectedColor/Materialsmisdetected/undetectedShape/SizeundetectedRelative position/MotionColor/MaterialsundetectedShape/SizeundetectedRelative position/MotionColor/Materialmisdetected/undetectedShape/SizeundetectedGrimeundetectedRelative positionColor/Materialsmisdetected/undetectedShape/SizeundetectedSticking objectsundetectedRelative positionColor/Materialsmisdetected/undetectedShape/SizeundetectedSticking objectsundetectedRelative positionColor/Materialsmisdetected/undetectedShape/SizeundetectedSticking objectsundetectedRelative positionColor/Materialsmisdetected/undetectedShape/SizeundetectedRelative positionPerception ErrorRecognition ErrorSignals from recognition target(S)Signals not from recognition target(N,U)Processing capabilityProcessing performanceScan TimingS strengthS propagation directionU factorDetectionCauses of recognition errorvehicle,sensorEgo vehicleChange ofvehicle poseSensorVariation ofinstallationFailure ofsensor itselfSurface in frontof the sensorSticking objectschanges incharaceristicsEnvironmentShapeRoad conditionMaterialMotor bikesBicyclesPedestriansSpatial obstaclesRadiowave andlight in spaceOther movingSpaceRoadsideobjectsOverheadobjectsStructural objectsRoadSurfaceOther vehiclesRecognition targetstrackLinesStructural objectswith heightRoad edgeswithout astepObstactions on the laneFallen objectAnimalsTemporal installedobjectwith a stepMoving objects 5959(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 27.Perception disturbance elements and generation principle matrix of the camera(element:vehicle/sensor,surrounding environment)Small effectMedium effectScatteringAbsorptionChromaLarge effectDisturbance outline(Flare)(Randompattern)(Fixedpattern)(Flicker)ClippedwhitesColorsaturationTrackinglostTracking toanotherobjectDisturbanceCausal factor item(example)Refractionangle,area,position MinoreffectVignettingGhost(Lens)Reflection(WS)Amount ofnoiseColorvariationTransparencyvariationRelativepositionMotionFrequencyLateralmotionLongitudinal motionLightsourcebrightness,direction,colorReflectionratio andlight oftargetNot enoughbrightnessBrightnessin meteringzoneLightsourcevariationTargetcolorvariationHigh NLow SHigh ULow DCaused byvehicle sideCaused bytarget sideBlind areaToo nearto getfeatureOut ofFOVOutsidescope oftargetNot inlearningdataReflectionSimilarfeatureType errorPositionerrorPosition(vertical)(lateral)Orientation(yaw)(roll)(pitch)LateralpositionVerticalpositionLateralpositionLongitudinalpositionFalsedetection(gettingclose)Falsedetection(drawingaway)Negativeerrorof relativespeedPositiveerror ofrelativespeedTargetOut of targetfalse negativefalse positiveposition or velocity error-003-003-001-005-001-005Sensing-direction-Turn a curveTurning（especially small R like turning atintersection）1-002Sensing-direction-high speed straight aheadHigh speed straight ahead（especially with nearobject on the side of ego vehicle）1-001Ground height-SensingpositionReplacing tires-001Position-sensing positionImaging position shift（whole image shift）-001Direction-sensing directionImaging position shift（direction）-001Aging-lens transmittance(color change)Transparency variation of lens（yellow discoloration,etc.）-1000Operating environment-Temperature change-Degradation of CMOSsensor characteristicsSensor characteristics variation（temperature characteristics,etc.）1-100Operating environment-Temperature change-Degradation of lenscharacteristicsLens distortion variation（temperature characteristics,etc.）-1000Pixel Defective-DefectivepixelsSmall object over defective pixelsMalfunctionwithout fault detection in case ofbadly defection-100Lens characteristic-Intra-lens reflectionDegradation of true detection or recognition ratiounder reflection caused by very high brightnesslight source.1-100Lens characteristic-ShadingDegradation of true detection or recognition ratiounder dark condition.（Especially periphery ofimage）1-100Processing capacity limit-Image complexityFail to detect or recognize a port of objectsbecause of too many targets.-100Processing capacity limit-Operating environmentToo many target objects under high temperature-100Hidden(Image Cut Out)-mud,dust,etc.Sticking mud,dust,etc.（image loss）-100Hidden(Image Cut Out)-snow,ice,etc.Sticking snow,ice,etc.（image loss）-100Hidden(Image Cut Out)-water,etc.Sticking water,etc.（image loss）-100Hidden(Image Cut Out)-insects,bird droppings,etc.Sticking insects,bird droppings,etc.（image loss）-100Hidden(Image Cut Out)-Windshield wiperWiper operation（image loss）-100Noise-mud,dust,etc.Sticking mud,dust,etc.（false detection,false recognition）（as image noise）-100Noise-snow,ice,etc.Sticking snow,ice,etc.（false detection,false recognition）（as image noise）-100Moise-water,etc.Sticking water,etc.（false detection,false recognition）（as image noise）-100Noise-insects,birddroppings,etc.Sticking insects,bird droppings,etc.（false detection,false recognition）（as image noise）-100Noise-Windscreen wiperWiper operation（as noise on recognition target）-100RefractionWater drop（Rain drop,etc.）（as transparency object）1-100Aging-Transmittance(brightness variation)Transparency variation of windshield（include effect by stains）-1000Aging-Transmittance(colorvariation)Transparency variation of windshield（color spectrum variation）-1000Break-Crack-NoiseCrack on windshield,etc.-100Break-Crack-RefractionCurve variation of windshield1-002Product variation-Transmittance(brightnessvariation)Transparency variation of whole windshield-1000Product variation-Transmittance(colorvariation)Color variation of windshield-1000Product variation-RefractionCurve variation of windshield-10001-0101-100ShapeSlopeVariation of position and inclination of road surfaceas image-100Erased road line marker,Wheel track-011Shadow of guardrail,noise barrier,etc.-011Road mirage,icy pavement(wide area),waterscreen（when heavy rain）-011Road joints（bridge,material change ofpavement）-011Spot on road surface-ReflectionPlash,icy pavement(partially),debris like mirror-011Entire road surface-ColorObject detection on colored pavement or coloredmaterials of pavement-100Entire road surface-Particle sizeCoarse（stone path）Medium（tiles（pattern)Fine(asphalt or concrete）-100Spot on road surface-Installation objectFalse recognition caused by manhole cap,etc.-011Spot on road surface-Painted signFalse recognition as painted sign on road surface,etc.-011Mirror surfaceReflected image on traffic roadside mirror,etc.-011Non-mirror surfaceFalse recognition as different object like sign onroad side-011Non-transparent materialImage cut out by roadside trees,buildings,roadsidesigns,etc.-100Transparent materialBox created by transparency materials(telephone box,bus station,etc.)-011ColorMajor background color(by buildings,signs,trees,etc.)is analogous to detection or recognition target.-100ShapeInterference shape of recognition target with shapeof background objects.False recognition of background object as person orobstruction-011Mirror surfaceN/A273000Non-mirror surfaceFalse recognition of overhead object-011Non-transparent materialBranches and trees of tall tree.Bridge-100Transparent materialN/A273000ColorOverhead sign（Major color）-100ShapeInterference shape of recognition target with shapeof overhead sign.False recognition of object placed on down slopeahead of road-011Reflection-Mirror surfaceN/A273000Reflection-Non-mirrorsurfaceFalse recognition of reflective floating objects(likeice,aluminum foil)as obstacle object.False recognition of patterns on smoke caused bylighting condition-011Hidden(Image Cut Out)-Non-transparency（rain,snow,etc.）Rain,snow,or fog before recognition target-100Hidden(Image Cut Out)-Non-transparency（sandstoms,petals blizzard,etc.）Sandstorms or petals blizzard before recognitiontarget-100Hidden(Image Cut Out)-Non-transparency（largeflying objects）Large flying object before recognition target-100Hidden(Image Cut Out)-TransparencyFlying transparent plastic bag-011Background-ColorSnow or fog(as background of recognition target）-100Background-ShapeDistribution profile of snow or fog-010Visible-Light source(point)-ColorStreet lamp,suns light,headlight of ego vehicle-010Visible-Light source(point)-Forward lightStreet lamp,suns light,headlight of ego vehicle no effect273000Visible-Light source(point)-BacklightLate afternoon sunheadlight from oncoming vehicle1-100Visible-Light source(point)-Reflected lightReflected image on surface of like water fromstreet light,suns light,headlight from oncomingvehicle,etc.-011Visible-Light source(environment)-ColorScattering light or ego vehicles headlight withbiased spectrum(visible)1-100Visible-Light source(environment)-brightness(bright)Strong scattering light（visible）,Wildfire,under the searing sun1-100Visible-Light source(environment)-brightness(dark)Weak scattering light（visible）Ego vehicles headlight1-100Visible-Light source(environment)-brightness(bright dark)Strong scattering light（visible）and shadow（searing sun and shady area,etc.）1-100Invisible-Disturbance lightsource(point)Infrared light projector,suns light-011Invisible-Disturbance lightsource(environment)Scattering light（near-infrared light）-100Mirror surfaceFalse recognition of reflected image on specularsurface of vehicle(like tank truck)-011Non-mirror surfaceFalse recognition of reflected image of like light onpolished body-011Non-transparent materialParked vehicle,Roadside tree,Incoming flying object-100Transparent materialTransparent object（like glass case on loading platform）-011ColorFalse recognition because of similar target color tobackground color-100ShapeInterference shape of recognition target withbackground.(Impossible to separate recognition target frombackground because of the shape)-012Entire road surface-ReflectionMovingobjectsReflectionHidden(Image CutOut)Back-groundOverheadobjectsReflectionHidden(Image CutBack-groundSpaceSpatial obstaclesRadio wave andlightEnvironmentsStructural objectsRoadsurfaceRoadconditionEntire road surface-NoiseMaterialRoadsideobjectsReflectionHidden(Image CutOut)Back-groundUsing tire chainsSensorsVariationSensoritselfFront of sensorsSticking objects,disturbingobjectsCharacteristicsvariationReflection on windshieldReflected image of dashboard(include objects on dashboard)Ego vehicleRecognitionModelclassCausal factor groupEgo vehicle andsensorsChange of carpostureSensing-direction-Normal drivingAttitude modification by motion or load（includeimproper maintenance）Sensing-direction-Single vibrationBump overSensing-direction-Periodic vibrationTarget-position error(Edge detection error)size,lateral position,longitudinal position,ordirection errorDirection errorMagnitude errorPerception(Difficult to separatetarget fromcircumference)(Invisible)(Indetection)(False positivedetection)(Classification error)Self-position errorRolling shutter effectCrushed shadowsOut of appropriateexposureW/B deviation(Hard to see)Target position errorTracking errorVelocity error(Blur:Depth of field)(Position shift,Deformation)(Vignetting)(Flare)(Ghost)(Double image)(Reflection)(Diffraction spike)(Aging)(Motion blur)Low spatial frequencyLow contrastHiddenNo classificationDetection or classification errorBase-position errorTime rag for exposureOver exposureUnder exposureLack of GradationDisturbance causal factorPerception partRecognition partOthersNumber of applicable itemsOpticsImagerImage processingFeature extractionDetection and classificationBrightnessHuePositioningTrackingRefractionReflectionDiffractionNoiseColor filterExposure timeExposure periodCrushed shadows 6060(C)Copyright Japan Automobile(C)Copyright Japan Automobile ManufacturersManufacturers AssociationAssociation,Inc.,Inc.,All rights reserved.All rights reserved.Table 28.Perception disturbance elements and generation principle matrix of the camera(element:perception target route/traffic information/obstacle)Small effectMedium effectScatteringAbsorptionChromaLarge effectDisturbance outline(Flare)(Randompattern)(Fixedpattern)(Flicker)ClippedwhitesColorsaturationTrackinglostTracking toanotherobjectDisturbanceCausal factor item(example)Refractionangle,area,position MinoreffectVignettingGhost(Lens)Reflection(WS)Amount ofnoiseColorvariationTransparencyvariationRelativepositionMotionFrequencyLateralmotionLongitudinal motionLightsourcebrightness,direction,colorReflectionratio andlight oftargetNot enoughb
2024-12-05
279页
5星级
2025Cars:an eternal youth?An international survey carried out in 14 countriesAt LObservatoire Cetelem,we regularly take the pulse of industries,products,innovations and generations of consumers,to check whether their hearts are beating as strongly as ever.In 2011,we turned our focus on the under-30s,before they were even referred to as millennials.At the time,they were known as Generation Y.Some 15 years later,we turn our attention back to this age group,todays Gen Z,to examine their relationship with cars.Our goal is to determine whether this relationship has evolved and,if so,how.This at a time when electric vehicles are emerging as the future of the industry,not to say its salvation.Listening to what the under-30s are saying and thinking about cars is all the more crucial when we consider that they will be the lifeblood of tomorrows automotive market.Hence why this is a crucial subject for automakers.Should the lack of interest young people sometimes express ultimately translate into tangible choices,these firms will have cause for concern.And if that is not the case,then there is potential that brands are currently failing to harness completely or at all.Without revealing too many details about this latest edition of LObservatoire Cetelem,we can safely say that we were quite surprised by the views put forward by the under-30s surveyed.To put it simply and bluntly,they love cars and are neither ready nor willing to live without them.In fact,between 2011 and 2025,the proportion who believe the industry will go on to see better days has actually increased.Of course,this hinges on whether cars can be successfully integrated into a mobility ecosystem that makes more room for green forms of transport,particularly in major cities.Could the younger generation surprise us once again?When it comes to cars,our annual focus of attention,this could well be the case.Flavien Neuvy Head of LObservatoire CetelemEDITORIALTABLE OF CONTENTSPreamble 061 Typical profile of a young driver 071.A clear desire to drive 081.1 The young cant wait to get their driving licence1.2 Buying ones first car:a logical progression2.The financial burden remains high 102.1 The used option is the most common2.2.Price:the main obstacle to a purchase2.3 Purchasing intentions are far from electric3.A positive attitude to motoring 133.1 The joy of driving3.2 Cars are seeing their image improving3.3 Life without a car is unimaginable4.Mobility has got young people mobilised 144.1 Diversified mobility 4.2 Even those without a vehicle sometimes travel by car4.3 The young are not the biggest fans of walkingKey data 17LObservatoire Cetelem 20252Why are we so attached to our cars?181.A sentimental relationship 19 1.1 A strong attachment to cars1.2 Cars help create future memories2.Maintaining perspective 212.1 Essential for the day to day2.2 Rational purchasing criteria2.3 Safety,convenience and freedom:a common mantra2.4 Shared criticisms3.Contrasting relationships with brands 233.1 An extension of ones personality3.2 Valued advice3.3 On the right trackKey data 243The future is electric 251.Doubts over the green credentials of cars 261.1 Cars have a great deal to answer for when it comes to the environment.1.2 And their presence is not always welcome2.Electric cars are synonymous with progress 282.1 Electric cars:at the crossroads between innovation and progress2.2 Electricity,the source of a better future3.Cars,EVs especially,will have an even stronger presence tomorrow 293.1 The future is automotive 3.2 The reign of electric cars is nighKey data 30Conclusion 31A glance at BNP Paribass economic research 32Market data 33LObservatoire Cetelem 202506There is an assumption that is always made about young people.It states that this generation has a relatively limited appetite for cars,instead preferring more responsible and sustainable forms of ecomobility that are in keeping with the times.Back in 2011,when its editorial was still referring to“clean cars”,i.e.,not combustion powered,LObservatoire Cetelem was already wondering whether young people still liked cars or whether they would choose to do without them for good.Nearly 15 years on,with electric powertrains set to become the new norm in the automotive sector,we wanted to find out whether young people were still potentially interested in cars.As we did in 2011,we will define young people,admittedly a loose concept,as being those aged under 30.Similarly,the“seniors”category will be considered to include anyone over the age of 50.PREAMBLE06Are young people disconnected from the automotive world?Not at all,on the contrary.As soon as they are legally able to do so,they cant wait to get behind the wheel and they do so with unabashed joy,albeit with varying degrees of financial ease.Cars are seen as the centrepiece of their mobility mix and essential to their daily lives,both now and in the future.Typical profile of a young driver1LObservatoire Cetelem 2025LObservatoire Cetelem 20250708A clear desire to driveTHE YOUNG CANT WAIT TO GET THEIR DRIVING LICENCEGiven their cost and size,cars are rarely considered as products whose purchase alone can bring total satisfaction.Buying a car is great,but using it is even better.However,this is dependent on whether one holds the golden ticket to motoring freedom:a driving licence.Thus,future drivers tend not to wait until they are no longer young to pass their test.85%of this population do so before the age of 25.The Chinese are the most likely to fall into the“late adopters”category,with 4 out of 10 passing their test after turning 25.At the other end of the scale,the British,and even more so the Americans,race to pass their driving test as early as possible.Indeed,more than half of US drivers obtain their licence before the age of 18(Fig.1).Fig.1At what age did you obtain your driving licence?To those who have a licence.Under-18s 18-year-olds Ages 19-20 Ages 21-25 Over-25sGermany 1243211311Belgium 303125122China4193641Spain38272312United States56181088France 39331792Italy5232106Japan33535198Norway432519112Netherlands430332112Poland330222421Portugal31282615United Kingdom1921192219Turkey152635231EUROPE436272013OVERALL731262115Source:LObservatoire Cetelem de lAutomobile 2025.08LObservatoire Cetelem 202509BUYING ONES FIRST CAR:A LOGICAL PROGRESSIONObviously,the earlier people pass their driving test,the sooner they tend to buy their first car and the keener they are to get behind the wheel quickly.Around 7 out of 10 Americans acquire their first vehicle between the ages of 16 and 20.The same is true for 1 in 2 French,German and Italian motorists.In contrast,1 in 3 Japanese and Chinese motorists dont buy a car until they have turned 25.While being in a relationship is not a determining factor on the whole,geographical location has an altogether greater influence.1 in 2 under-20s who live in towns of fewer than 20,000 inhabitants have already bought a vehicle.These results are not down to differences in behaviour or expectations linked to socio-cultural characteristics,but primarily to the legislation in place in each country.Americans are the most likely to take their driving test early,since they are able to do so from the age of 15.In China and Turkey,two countries that will repeatedly stand out over the course of the survey,the minimum age is 18.In France,the opportunity to drive under supervision from the age of 16 is taken up by only 2%of motorists.Minimum driving age INSIGHT Fig.2Source:.Germany 17Belgium 17China18Spain18United States15France 16Italy17Japan18Norway18Netherlands17Poland18Portugal17United Kingdom16Turkey18AVERAGE17There also seems to be something of a correlation between the average age of women when their first child is born and the age at which they buy their first car.The United States posts the highest scores for these two items.A correlation can also be observed in France and the Netherlands.Average age of women when their first child is born INSIGHT Fig.3Source:various institutions referenced by wikipedia.org.Germany 31.1Belgium 30.8China31.2Spain32.1United States28.8France 30.6Italy32Japan29.6Norway29.6Netherlands29Poland31.5Portugal32.2United Kingdom30.6Turkey31.4AVERAGE30.709LObservatoire Cetelem 202510But the financial burden remains highTHE USED OPTION IS THE MOST COMMONOverall,young people seem to be split between buying their first car new or used,whereas in 2011 they were more likely to go for the second-hand option(63%vs.51%this year).Seniors,on the other hand,are more inclined to buy a new car(59%)(Fig.4).However,stark differences can be observed between the countries.In China,9 out of 10 young people opt for new vehicles.The figure for Japan is 8 out of 10.The Italians and Spanish complete the top four.The bias towards new cars in the Asian and Mediterranean markets is a long-established trend.This edition of LObservatoire Cetelem confirms that young people are not immune to it.It is also worth noting that the second-hand market in China is very underdeveloped.One must go to Poland,Portugal and France to find the biggest fans of used cars.With its highly-developed second-hand market,the situation in France is very different to that in China.Fig.4Did you buy this car.?To young people(under-30s)who have at least one car in their household.New UsedGermany 4456Belgium 4258China928Spain5644United States5050France 3268Italy5941Japan7723Norway3565Netherlands4258Poland2575Portugal3268United Kingdom4456Turkey5545EUROPE4159OVERALL4951Source:LObservatoire Cetelem de lAutomobile 2025.10LObservatoire Cetelem 202511An analysis of young peoples incomes,in comparison to those of the population as a whole,sheds further light on the decision to buy new or second-hand.In China and Japan,where the preference is for new vehicles,young people earn more on average than their elders and are therefore more likely to have the resources to fulfil their aspirations.Paradoxically,the low incomes of young people in Italy do not appear to curb their enthusiasm for buying new cars.The average price young people pay for a car varies greatly from one country to the next.The figures for China and Italy reflect their preference for new vehicles,despite their low average incomes.How much did you pay for this vehicle?In euros(average)To young people(under-30s)who have at least one car in their household.INSIGHT Fig.5Source:LObservatoire Cetelem de lAutomobile 2025.INSIGHT Fig.6Average gross annual income of under-30s in eurosGermany 16,659Belgium 14,499China21,518Spain15,625United States19,360France 12,290Italy14,952Japan13,459Norway18,552Netherlands14,622Poland3,381Portugal14,271United Kingdom14,999Turkey14,143EUROPE13,985OVERALL14,881Source:National statistical institutesGermany 36,14447,700Belgium 32,13644,808China15,53711,885Spain25,24737,000United States41,97670,123France 22,80041,592Italy38,20014,000Japan34,57031,908Norway32,73787,864Netherlands34,30052,824Poland23,00413,788Portugal18,50412,451United Kingdom41,67644,979Turkey9,744EUROPE26,52843,647OVERALL27,48940,010 Gross annual income of under-30s Gross annual income of the population as a whole11LObservatoire Cetelem 202512PRICE:THE MAIN OBSTACLE TO A PURCHASEFinancial constraints are the main hurdle for young people who have a driving licence,but have not yet acquired a vehicle.6 out of 10 think cars cost too much,a significantly higher score than for seniors.This is a constraint that the Americans,Turks and Portuguese feel particularly keenly,while it is seen as less of a problem in Japan.The second most frequently mentioned factor is not having use for a car,with seniors most likely to make this point(4 out of 10 state that they can live without a vehicle).A much smaller proportion of young people with a licence but no car say that they dont need a vehicle.Only just over a quarter make this argument(Fig.7).PURCHASING INTENTIONS ARE FAR FROM ELECTRICYoung peoples short-term purchase intentions still reveal a preference for second-hand cars in a good half of cases.When it comes to choosing an energy source,EVs occupy the number two spot,behind petrol,but ahead of diesel,which remains the top choice in the 30-49 age group.The fact that the electric vehicle market is still relatively small partly explains this result.And once again,price is not the main barrier preventing drivers from going electric.Young people are the first to mention the potential difficulties involved in charging an EV(32%vs.31%).This is seen as a factor that could hinder their freedom to travel,which they consider precious and is a topic we will return to later.Vehicle range comes third in the list of constraints.Seniors place more emphasis on price(50%),without neglecting the other two factors.Fig.7What is your main reason for not having a car?Select one answer only.To those who have a licence,but no car.Source:LObservatoire Cetelem de lAutomobile 2025.It costs too much595347You dont need one273040They cause too much pollution441You wouldnt know where to park it652You dont like driving4810 Ages 18-29 Ages 30-49 Over-50s12LObservatoire Cetelem 202513A positive attitude to motoringTHE JOY OF DRIVINGThe practical aspects of cars in no way detract from the pleasure of driving them.Quite the opposite,in fact.7 out of 10 young people confirm this point,while just 2 out of 10 view driving as a chore(Fig.8).And this enjoyment has stood the test of time,since 8 out of 10 young people surveyed in 2011 had declared their fondness for driving.The Chinese and Turks are the most enthusiastic,in contrast to the Japanese,whose enjoyment is less apparent.Men,inhabitants of big cities,couples with children and EV drivers all seem to share this passion for motoring.CARS ARE SEEING THEIR IMAGE IMPROVEAs we have just ascertained,cars are a source of pleasure,but they also enjoy a positive image overall.One of the most surprising findings of this survey is that,despite the received wisdom regarding cars and young people,1 in 2 under-30s believe that the image they have of cars has improved over the last five years.Only 14%report that it has worsened.This is in stark contrast to the views expressed by seniors,more than half of whom have not changed their opinion(Fig.9).Another finding that may seem surprising is that this image boost is more apparent in cities than in rural areas,no doubt due to the growing presence of electric and hybrid vehicles,not to mention traffic restrictions.Looking at the geographical breakdown,the Chinese and Turks once again express the most enthusiasm,while the French are among the most reserved on this point.Fig.8For you,driving is:To those who have a driving licenceSource:LObservatoire Cetelem de lAutomobile 2025.Ages 18-29171370Ages 30-49181765Over-50s142363 Mostly a pleasure Mostly a chore You are indifferent about drivingFig.9Over the last 5 years,would you say that the image you have of cars.?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-294634614Ages 30-493546613Over-50s2459512 Has worsened Has improved Has not changed I dont know13LObservatoire Cetelem 202514LIFE WITHOUT A CAR IS UNIMAGINABLESo how about living without a car?Most young people struggle to see how they could.6 in 10 dont see it as a possibility.However,it should be noted that this proportion has fallen significantly since 2011.It is also slightly lower than the figure for seniors(Fig.10).The French and Americans are the most resistant to the idea.Paradoxically,the Chinese and Turks,but also the Poles,are somewhat less reticent.Not surprisingly,the prospect of a car-free life is more appealing to urban dwellers than to those based in rural areas.Mobility has got young people mobilisedDIVERSIFIED MOBILITY But cars are not the be-all and end-all.Young people are well aware that there is more than one way to travel.Cycling tops the list,having been embraced by 7 out of 10 young people(Fig.11).Its popularity in no way depends on where people live,with inhabitants of towns and cities of all sizes taking it up with equal enthusiasm.Having children provides an even greater incentive to cycle.The increasing use of electric bicycles to take children to school,especially in urban areas,is undoubtedly a factor.If we look at the different countries,the Netherlands,where the bicycle is king,and,more surprisingly,Poland are the two most cycling-friendly nations.Its detractors include Portugal,the United States and the United Kingdom.Could it be something to do with the climate?Ride sharing comes second in the ranking of alternative forms of transport,being cited by over 50%of young people,double the proportion of seniors.If we compare this to the figures reported in 2011,this is a particularly striking result,given that only 30%of young people said they had taken up cycling at the time.The Japanese and Italians are by far the least likely to get on a bike.The Chinese and Turks are once again among the most committed in this area.Its worth highlighting that car and bicycle hire receive very similar scores,with around 1 in 3 young people choosing to use these services.Fig.10Could you imagine never using a car again?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-296238Ages 30-496337Over-50s6634 Yes No14LObservatoire Cetelem 202515EVEN THOSE WITHOUT A VEHICLE SOMETIMES TRAVEL BY CARHowever,not owning a vehicle doesnt mean giving up on cars entirely.Once more,young people without their own wheels are taking advantage of ride sharing.This is the only item,along with car sharing,where the difference between this generation and seniors is so pronounced(Fig.12).Rental,a more traditional solution,and subscription servic-es are the two most popular options for around 1 in 2 young people and seniors.Fig.11Do you ever.To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Rent a car from a short-term rental company353627Use self-service car sharing342712Rent a car from a private individual262310Use ride sharing(as a passenger)564223Travel by bicycle696552Rent a bicycle322512 Ages 18-29 Ages 30-49 Over-50sFig.12If you didnt have a car,what other solutions would you choose?To those who have at least one car in their household.Ages 18-29 Ages 30-49 Over-50sSource:LObservatoire Cetelem de lAutomobile 2025.Short-term rental (car rental on an occasional basis)525354Self-service car sharing464333Ride sharing554530A subscription service that would give you access to a car when you needed it49494615LObservatoire Cetelem 20251652393888520221913141074157 57646913Public transportMotorcycle/mopedNon-electric bicycleElectric bicycleScooter,one-wheeler,etc.WalkingNoneWALKING LAGS SLIGHTLY BEHIND AMONG THE YOUNGWhen not driving,young people choose public transport for their daily travel requirements,especially if they live in a city.For their part,seniors prefer to walk,possibly because they are keen to stay in shape,although young people are not averse to this healthy choice either(Fig.13).Fig.13Other than your car,what are the main forms of transport you use for your daily travel needs?Select up to two answers.To those who have at least one car in their household.Ages 18-29 Ages 30-49 Over-50sSource:LObservatoire Cetelem de lAutomobile 2025.16LObservatoire Cetelem 20251785%of young people pass their driving test before the age of 251 in 2 buy their car second-hand7 out of 10 enjoy driving1 in 2 feel that cars have enjoyed an image boost over the last 5 years4%of young people who dont have a car believe that they cause too much pollution1 in 2 cant imagine life without a carKEY DATA1718Movies like Christine,Crash,Titane and Rebel Without a Cause have taught us that human beings can develop a close and unique relationship with their car,whose status is sometimes elevated to that of a living,breathing being.Without taking things quite so far,young people are of the view that this is not a consumer product like any other.Conveying values and emotions,while conjuring memories and a sense of freedom,cars inhabit a world in which reason and feelings are engaged in continuous dialogue,with brands acting as key advisors and confidants.Why are we so attached to our cars?218LObservatoire Cetelem 202519A sentimental relationship A STRONG ATTACHMENT TO CARSAlthough cars can be viewed as simple consumer products,what sets them apart is the relationship their owners have with them.This relationship almost equips them with a personality of their own.In turn,this can generate a special attachment.Within the youngest demographic,this is true in 8 out of 10 cases(Fig.14).In China,what we see is a veritable love affair,with a colossal 97%of young people saying they are attached to their car.The Turks,Poles and Italians are almost as enthusiastic,while in the land of cycling,the Dutch are relatively more measured in their feelings(70%).Inhabitants of big cities also harbour a passion for motoring,as do couples with children.Germany 8416Belgium 8317China973Spain8713United States7525France 8614Italy8614Japan6832Norway7624Netherlands7525Poland8911Portugal8614United Kingdom7921Turkey8911EUROPE8317OVERALL8317Fig.14Are you attached to your car?To young people(under-30s)who have at least one car in their household.Yes NoSource:LObservatoire Cetelem de lAutomobile 2025.19LObservatoire Cetelem 202520CARS HELP CREATE FUTURE MEMORIESHowever,this attachment is not just sentimental.For 45%of young people,the feeling stems primarily from the utility of cars,a viewpoint most commonly held by rationally-minded French motorists(58%),in contrast to the more romantic Portuguese(32%).Cars also appeal to peoples materialistic side,with 33%of young people regarding them as valuable items.The Portuguese and Americans are the most likely to be in this camp(48%and 42%),while the Japanese are overwhelmingly unmoved in this respect(12%).Weve known since Back to the Future that cars can be wonderful time machines.The NextGen are unlikely to mock boomers for their views on the subject.30%of them believe they are the perfect tool for forging memories,which suggests that cars have a bright future.These are memories created by holidays,excursions with family or friends,and outings with ones first child.The Germans and,once again,the Portuguese are eagerly looking ahead to these automotive memories.In last place when it comes to sources of attachment is the ability of cars to generate fresh encounters and interactions with others(25%)(Fig.15).Fig.15Why are you so attached to your car?To young people(under-30s)who are attached to their car.Select one or more answers.It is useful It generates encounters and interactions with others It is a valuable item It harbours many memoriesGermany 42333040Belgium 55153321China35313035Spain35352621United States42274226France 58223628Italy45232425Japan47131226Norway47363230Netherlands55183824Poland46312635Portugal32244838United Kingdom40313628Turkey47113735EUROPE45273329OVERALL45253330Source:LObservatoire Cetelem de lAutomobile 2025.20LObservatoire Cetelem 202521Maintaining perspectiveESSENTIAL FOR THE DAY TO DAYWhile those who are car-free doubt their utility,those who do own a vehicle feel the very opposite.Nearly 8 out of 10 young people say their car is indispensable on a daily basis,significantly higher than the score for seniors.One has to go to Norway or the UK to find more nuanced opinions,while utilitarianism is the order of the day in Asia.While there is little to separate the views of urbanites and rural dwellers on this question,couples with children are more likely to state that cars are an essential part of their daily lives.When it comes to taking children to school or to their extra-curricular activities,not to mention food shopping,cars are a long way from being superseded by cargo bikes(Fig.16).RATIONAL PURCHASING CRITERIAPeoples purchasing criteria are also rooted in rationality.As successive editions of LObservatoire Cetelem have reminded us,price is the number one consideration when buying any type of good.And when young people acquire a vehicle,this is invariably what they think about first.However,it is less important in their eyes than in those of seniors,who score this criterion almost 10 points higher.Once again,the Chinese and Turks are by far the least sensitive to this factor,while for residents of towns with fewer than 20,000 inhabitants it is a crucial one.Again,both generations are in agreement on safety,which they put forward as their second most important purchasing criterion,with seniors placing slightly more emphasis on the issue.However,while mileage comes third for young people(given their tendency to opt for second-hand vehicles),running costs occupy this position for seniors(Fig.17).Fig.16Is your car essential to your daily life?To those who have at least one car in their household.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-292377Ages 30-491783Over-50s3070 Yes NoFig.17Which of the following criteria do you take most into account when buying a car?Select up to three answers.To those who have at least one car in their household.Source:LObservatoire Cetelem de lAutomobile 2025.Price454854Safety293234Miles on the clock222225 Ages 18-29 Ages 30-49 Over-50s21LObservatoire Cetelem 202522SAFETY,CONVENIENCE AND FREEDOM:A COMMON MANTRAIf we must get caught up in metaphor and compare cars to people,then it makes sense to talk about their qualities and shortcomings.When it comes to the former,three in particular stand apart from the rest:safety,convenience and freedom.These qualities are highlighted by young people and seniors alike,but to varying degrees.For instance,30%of young people believe that safety is a cars most important attribute,compared with 43%of seniors.The gap begins to narrow when the topic is convenience,which comes in second place.This quality is mentioned by 27%of young people and 38%of seniors.In third place is freedom,a topic on which the views of young people and seniors are more similar,with scores of 27%and 32%respectively(Fig.18).It is worth noting that,outside of this top three,speed and pleasure are the qualities most commonly mentioned by young people,while seniors rarely mention the former.SHARED CRITICISMSAs for the“shortcomings”of cars,young people and seniors agree once again when it comes to their top three,but with even greater convergence of opinion.The stress caused by cars is the number one issue and is cited by 3 in 10 people in both age categories.A similar proportion see them as a constraint(23%of young people and 22%of seniors).The third“flaw”is somewhat less obvious,in that it relates to a form of pollution that receives less publicity than CO2 emissions,but which is particularly noticeable in urban environments.The issue here is noise,which is decried primarily by young people,with a quarter of them citing this problem(Fig.19).Fig.18Which of the following characteristics best apply to cars?Select up to three answers.To those who have at least one car in their household.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-29302727Ages 30-49343031Over-50s433832 Freedom Safety ConvenienceFig.19Which of the following characteristics apply to cars the least?Select up to three answers.To those who have at least one car in their household.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-29292623Ages 30-49292422Over-50s312222 Constraint Stress Noise22LObservatoire Cetelem 202523Contrasting relationships with brandsAN EXTENSION OF ONES PERSONALITYExamining peoples relationship with cars in terms of image,which is strongly linked to the brands that produce them,reveals generational differences.When it comes to the factors that influence their choice of vehicle,young people focus on style,design and power.This is a generation who like their cars to have character.On the flip side,the brand and especially the country of manufacture are much less important to young people than they are to seniors.Are brands losing their sparkle and their power to influence?The reality is more complex.VALUED ADVICEIndeed,when young people are looking to buy a car,they prefer to acquire them from brands,rather than trusting dealerships.Similarly,after a test drive,the information provided by brands is the most important factor in their decision,with almost 9 out of 10 young people prioritising these criteria.It is interesting to note that the web is not the primary source of information for this generation,as one might have expected(Fig.20).ON THE RIGHT TRACKFar from vilifying brands,young people seem to be fairly satisfied with what they offer.More surprisingly,this is also the case when it comes to environmental matters.Around 1 in 2 young people feel that manufacturers are doing enough to produce eco-friendly vehicles.This result can probably be explained by the ever-growing number of electric vehicles being produced,but also by the effectiveness of marketing that focuses on the virtues carmakers seek to present in this day and age.Note also that in all the countries surveyed,the total number of“yes”answers exceeds the total number of“no”answers.Fig.20If you were about to buy a vehicle,who would you trust most to advise you regarding your purchase?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-2925181344Ages 30-4925211539Over-50s23261932 The brands that design and manufacture the cars The dealerships that sell them to you Neither I dont know23LObservatoire Cetelem 2025248 out of 10 young peopleare attached to their car3 in 10 see it as a source of memories8 out of 10 believe it is essential for the day to day45%look at the price first and foremost before they buy9 out of 10 take notice of the information provided by brands before buyingKEY DATA24Its difficult to imagine what the world will look like in 30 years time.Difficult,but not impossible,or so young people tell us.According to them,cars will be as important,if not more important,than they are today.In their electric form,they are even seen as a symbol of progress through innovation.3The future is electricLObservatoire Cetelem 2025LObservatoire Cetelem 20252526Doubts over the green credentials of carsCARS HAVE A GREAT DEAL TO ANSWER FOR WHEN IT COMES TO THE ENVIRONMENT.Mentioning the environment inevitably leads us to place cars in the dock.So,guilty or not guilty?On this point,young people are less forgiving than their elders.Almost half believe that they are the leading cause of global warming,a view shared by only 3 in 10 seniors.It should be stated that across all age groups,those who think that cars are the main cause of global warming are never in the majority.This is a question that reveals major differences between China,Japan and Turkey,where cars are seen as the main culprit by around 60%of respondents,and every other country surveyed.City dwellers are also more likely to express this view.Moreover,young people in urban areas are more vocal in singling out cars as the main source of pollution,although the gap here is less pronounced.Indeed,64%are of this opinion,compared with just 58%of seniors.What these results undoubtedly point to is the greater environmental awareness of young people,who tend to be better informed than their elders and feel very strongly that this is an issue that affects their future(Fig.21).Fig.21Would you say that cars are.?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-296444Ages 30-496138Over-50s5830 The main cause of global warming The main cause of urban pollution26LObservatoire Cetelem 202527AND THEIR PRESENCE IS NOT ALWAYS WELCOMEDifferences of opinion between the generations are again evident when it comes to the question of banning the sale of combustion-powered cars.Once more,regardless of age,there is no majority in favour of such a policy.Only 39%of young people are opposed to it,compared with 46%of seniors.There are twice as many opponents in cities as there are in rural areas,and a similar proportion in most European countries.Young people are also slightly stricter when it comes to the environmental regulations imposed on cars.However,only 24lieve them to be inadequate,with just 21%of seniors agreeing.1 in 2 are of the view that current regulations are sufficient.As one might expect,criticism is more likely to be encountered in cities.Once again,the environmental“literacy”of young people,which is founded on higher-quality information,may account for this result(Fig.22).Fig.22In your opinion,are the environmental regulations imposed on cars and on their use.?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Ages 18-2952131124Ages 30-4950171221Over-50s46191421 Insufficient Sufficient Excessive I dont know27LObservatoire Cetelem 202528Electric cars are synonymous with progressELECTRIC CARS:AT THE CROSSROADS BETWEEN INNOVATION AND PROGRESSSome of the results from last years Observatoire Cetelem shed further light on the topic.What they highlight,for instance,is that 84%of young people believe that technological advances will improve the environmental performance of cars.This opinion is held by all generations(Fig.23).However,young people are more likely than their elders to believe that electric cars are the very embodiment of progressive innovation(Fig.24).ELECTRICITY,THE SOURCE OF A BETTER FUTUREElectric vehicles are considered to display even more virtues than their combustion-engined cousins.1 in 2 young people say that they are more environmentally friendly,compared with only 4 in 10 seniors.The differences in the opinions of urbanites and rural dwellers are striking:the former are twice as likely as the latter to believe that EVs have a positive impact.The largest numbers of doubters can be found in Germany and France.Fig.23Do you believe that technological advances will reduce the environmental impact of cars?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2024.Yes NoAges 18-291684Ages 30-491783Over-50s1783Fig.24Do you think that electric cars can embody this technological progress?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2024.Yes NoAges 18-292575Ages 30-493070Over-50s406028LObservatoire Cetelem 202529Cars,EVs especially,will have an even stronger presence tomorrowTHE FUTURE IS AUTOMOTIVE The idea of a future powered by a strong electric current makes young people feel particularly optimistic about the evolving role of cars.In 2011,29%of young people surveyed felt that cars would play a more important role in society in 30 years time,while 45lieved that their status would remain unchanged.In the space of 13 years,there has been a dramatic shift,with the two scores having been more or less reversed.47%expect cars to play a more important role and the score for this item has risen in every country(33%think its status will be identical).This enthusiasm is all the more striking when compared with the more measured responses of seniors.Indeed,the older generation are most likely to state that the status quo will be maintained(the proportion who believe that cars will play more or less of a role is 30%,in both cases)(Fig.25).THE REIGN OF ELECTRIC CARS IS NIGHNaturally,if cars are to take on an even more important role in society,they will rely on electric motors to propel them into the future.On this issue,young people once again appear to have stronger convictions than seniors.6 out of 10 believe that EVs will replace combustion-powered cars,while half of the older generation are of this opinion.These results should make brands feel more confident in their decision to go headlong down this road(Fig.26).Fig.26Do you believe that electric vehicles will eventually completely replace combustion-powered cars?To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.Yes NoAges 18-293763Ages 30-494159Over-50s5347Fig.25In your opinion,in 30 years time,the role cars will play in our society will be:To all respondents.Source:LObservatoire Cetelem de lAutomobile 2025.More important than currently Neither more nor less important than currently Less important than currentlyAges 18-29332047Ages 30-49402238Over-50s40303029LObservatoire Cetelem 2025301 in 2 young people believe cars are the main cause of global warming1 in 2 believe that current restrictions are sufficient1 in 2 believe that EVs are more eco-friendly than combustion powered cars1 in 2 believe cars will play a greater role in 30 years time6 out of 10 can see electric cars replacing their combustion-powered equivalents in the futureKEY DATA30LObservatoire Cetelem 202531Seniors are yesterdays young people.In other words,young people are the seniors of tomorrow.This biological inevitability confers them with crucial economic importance.Indeed,in one or two generations time they will have a higher income and more assets.Putting them in a positive frame of mind today increases the chances that this will translate into hard cash in the future.To put it bluntly,young people are a prime investment,one of the most promising there is.Brands and retailers should be truly delighted with the findings of this latest Observatoire Cetelem survey devoted to the under-30s.Somewhat counterintuitively,this age group displays a strong affinity with cars,while also predicting,and even hoping,that they have a bright future ahead of them.Ultimately,they love cars and will continue to do so for a long time to come.In keeping with their generations expectations,which are also tinged with a degree of anxiety,they like to picture themselves in a car that is environmentally friendly.In such a context,thanks to the relatively high level of credibility they command among young people,as this survey shows,brands have many strong cards to play.It is up to them not to waste them.Their future success will rely on constant,transparent dialogue,a firm and genuine commitment to the environment,smooth integration into a multi-faceted transport mix and,above all,prices that will make cars accessible to a generation who simply want to get behind the wheel and create an irreplaceable scrapbook of memories.CONCLUSION31LObservatoire Cetelem 202532A glance at BNP Paribass economic researchHouseholds continue to save more and to buy fewer carsEuropean households are saving,a lot.Perhaps less so than in 2020,when their spending on transport,eating out and leisure was artificially reduced.But still much more than in 2019,when the savings rate was almost 3 points lower than it is now.Spending power,which was a concern at the height of the inflation crisis,is now bouncing back as inflation recedes.However,not only are households not spending this extra disposable income,or not yet at least,they are not investing in their accommodation either(the market for existing property and new builds remains at a low ebb).Most of this extra household income is therefore channelled into financial savings products,which together with other investments account for almost half of total household savings in both France and Germany.Indeed,the sums pumped into financial savings products have now reached an unprecedented level(lockdown period aside).Saving helps to finance certain needs and can therefore be seen as a way of preparing for the future(the glass half-full view).However,it can also be interpreted as being the postponement of a purchase(the glass half-empty view).One could even consider that a part of these efforts to save is structural,particularly when we consider the reduction over the last 5 years in the proportion of disposable income devoted to purchases of all kinds,be it food,energy,non-food products(textiles,toiletries,etc.),household goods and transport(including cars).A certain proportion of these spending reductions(nearly a third in France)has gone into the purchase of services(which has partially replaced the consumption of goods,e.g.,food services rather than in-store purchases),but most have gone into bolstering peoples savings.According to the latest household economic surveys,these behaviours are set to persist,therefore most of the spending reductions in question will be long term.While the lowering of interest rates,which is set to continue,should encourage households to spend a little more,savings rates are likely to remain almost 2 points above the 2019 level at the end of 2025,limiting the prospects of a pick-up in demand.Stphane ColliacSource:Eurostat,Insee.Savings rate as a%of gross disposable income201220132014201520162017201820192020202120222024302520015105GermanyFranceEuro ZoneSpainItaly32LObservatoire Cetelem 202533Market data33LObservatoire Cetelem 202534The new passenger car(NPC)market*Estimates and forecasts from LObservatoire de lAutomobile 2025 Sources:LObservatoire de lAutomobile 2025,OICA,ACEA,C-Ways.Global light vehicle(LV)marketScope:every country in the world.*Estimates and forecasts from LObservatoire Cetelem de lAutomobile LMC Automotive,C-Ways forecasts.Light vehicles(LV)=passenger cars(PC) light commercial vehicles(LCV).*Estimates and forecasts from LObservatoire Cetelem de lAutomobile.20202021202220232024*20252024/2023 variation2025/2024 variationGlobal LV sales in millions of units77.880.785.38789922.3%3.4 2120222023Variation 2023 vs.20222023 (7 months)2024 (7 months)Growth rate over 7 months 2024/20232024pVariation 2024 vs.20232025pVariation 2025 vs.2024Germany2,622,1322,651,3572,844,6097%1,641,504 1,709,900 4.2%3,000,000 5%3,100,000 3.3lgium383,123366,578476,67530)9,144 295,559-1.2G5,000 0H0,000 1.1%China21,481,53723,563,28726,013,00010,368,000 13,974,000 4.5&,000,000 0,000,000 3.8%Spain859,476813,396949,36017X6,626 619,224 5.6%1,010,000 6%1,050,000 4.0%United States14,946,97113,754,30014,297,7554%9,029,236 9,169,070 1.5,600,000 2,000,000 2.7%France1,659,0051,529,1851,774,77216%1,018,722 1,040,924 2.2%1,800,000 1%1,800,000 0.0%Italy1,456,6741,316,7001,598,787210,765 1,011,259 5.3%1,690,000 6%1,700,000 0.6%Japan3,675,6983,448,2984,436,86629%2,740,721 2,443,627-10.8%4,100,000-8%4,100,000 0.0%Norway176,276174,329126,950-27b,165 67,718 8.90,000 105,000 3.6%Netherlands324,336312,129371,972199,200 220,168-3.960,000-370,000 2.8%Poland446,647419,765475,033135,062 320,099 16.4R0,000 9R0,000 0.0%Portugal149,740156,304186,447196,229 130,967 3.85,000 5 0,000 2.6%United Kingdom1,647,1811,614,0631,903,05418%1,093,641 1,154,280 5.5%2,000,000 5%2,100,000 5.0%Turkey561,853592,660961,33962Q8,788 536,351 3.40,000 10,000 0.0-COUNTRY TOTAL50,390,64950,712,35156,416,619111,949,803 32,693,146 2.3V,860,0001X,535,0002.94LObservatoire Cetelem 2025354%3lgiumNetherlands12%7%4%ItalySpainPoland15%United Kingdom22%GermanyFranceEurope total*12,840,281 New passenger car registrations in Europe*in 2023Household penetration in 5 countriesThe calculation is strictly based on car registrations for private use only*EU 26(excl.Malta) UK,Norway,Switzerland and Iceland.Sources:ACEA.Sources:National Statistical Institutes,Manufacturers Federations,C-Ways.18%1%OthersNorwayPrivate registrations in 2023,in thousands Total new passenger car registrations in 2023,in thousandsPrivate individualsCompaniesNumber of households in millions(2021)Household penetrationGermany9332,84533gA.22.3%Spain44894947S.82.4%France8281,77547S0.42.7%Italy9571,59960%.83.7%United Kingdom8911,90347S).53.0%TOTAL 4,0579,07145U5.72.85LObservatoire Cetelem 202536Leading brands in EuropeAnnual sales in Europe in 2023,change vs.2022 In unitsSources:ACEA.Volkswagen1,149,741( 11.8%)Toyota686,705( 8%)Renault629,093( 16.1%)BMW589,682( 16.8%)Mercedes570,591( 7.8%)The leading groups in EuropeAnnual sales in Europe in 2023,change vs.2022 In unitsSources:ACEA.Volkswagen Group2,753,053( 18%)Stellantis(PSA-FCA)1,880,083( 2.9%)Renault Group1,152,230( 16.9%)Hyundai-Kia885,626( 4.2%)Toyota Group728,727( 9.9%)Sources:IAE,ACEA&Marklines.Share of new cars registered that are electric vehicles In%The new-car market in FranceIn number of registrationsSources:C-Ways based on SIV data201420152016201720182019202020212022202320242025NPC New passenger car1,795,885 1,917,226 2,015,177 2,110,748 2,173,518 2,214,428 1,650,1181,659,146 1,529,185 1,774,772 1,800,000 1,800,000 LCV Light commercial vehicle372,074 379,424 397,085 438,645 459,038 479,769 401,124 430,787 346,946 377,878 400,000 420,000 2015201920222023Germany133118Belgium132620China152924Spain0195United States12812France132117Italy0194Japan1132Norway22568882Netherlands10153531Poland0164Portugal162218United Kingdom132317Turkey001036LObservatoire Cetelem 202537Structure of the new passenger car market in FranceSources:Observatoire Cetelem de lAutomobile,CCFA,C-Ways based on SIV data34f%CompaniesPrivate individuals200957C%CompaniesPrivate individuals202120248 months55E%CompaniesPrivate individuals202353G%CompaniesPrivate individuals54F%CompaniesPrivate individuals202237LObservatoire Cetelem 20253868.5%Used cars over 5 years old5.54%Used cars less than 1 year old26%Used cars 1 to 5 years oldMarket share of French brands*in the new passenger car market in FranceThe used passenger car market in France in 2024First 8 months of 2024*French brands:Citroen,Peugeot,DS,Alpine and Renault.Sources:Observatoire Cetelem de lAutomobile,CCFA,C-Ways based on SIV dataSources:C-Ways based on SIV data20122013201420152016201720182019202020212022202348.2H.3I.6I.1H.0G.7G.6G.5H.6D.7A.57.88The economic and marketing analyses,as well as the forecasts,were performed in conjunction with the survey and consulting firm C-Ways,specialists in Anticipation Marketing.Quantitative consumer interviews were conducted by Harris Interactive between 25 June and 9 July 2024 in 14 countries:Belgium,China,France,Germany,Italy,Japan,Netherlands,Norway,Poland,Portugal,Spain,United Kingdom,United States and Turkey.In total,16,000 people were interviewed online(CAWI method).These individuals,aged 18 to 65,were drawn from national samples representative of each country.The quota method was employed to ensure that the sample was representative(gender and age).3,000 interviews were conducted in France and 1,000 in each of the other countries.METHODOLOGY:Survey Manager:Flavien NeuvyCo-authored by:Luc Charbonnier and C-WaysDesign:Altavia DiskoIllustrations:Altavia Disko,Adobe Stock Follow all the latest news from LObservatoire Cetelem at:obs_cetelem
2024-12-05
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An international survey carried out in 16 countries2024MOTORISTS ARE IN A FOGRegulations,energy sources,pricingEDITORIALFor years,almost since its very inception,the automotive sector developed with little or nothing to hinder its growth and success.Any adversity,such as the oil crisis of the early 1970s,was overcome relatively smoothly.The succession of innovations that saw automobiles evolve from the Ford Model T to the SUV did not,however,reduced their cost,making them the only“mass-market”product to distinguish themselves by becoming ever more expensive.Even so,price remained the main criterion that swayed the purchasing decisions of consumers.Various constraints,not least those of an environmental nature in the broadest sense of the term,then gained more weight.Then the powers that be decided that electricity would be the sole energy source used in the cars of the future.And then,fnancial,economic and geopolitical crises came one after the other in what seemed like the blink of an eye.As car sales faltered,the automotive sector as a whole was thrown into doubt and came under unprecedented pressure.This pressure has resulted in a plethora of new regulations being introduced over a very short space of time.As part of our ongoing mission to make sense of the latest trends and identify the direction in which the automotive sector is heading,we thought it would be useful to look at the underlying reasons for what is undoubtedly a pivotal moment for the industry.Today,motorists are losing their points of reference and are no longer really sure which brand to go for,as they weigh up the value of switching to electric cars.Our use of the term“fog”is also a very topical metaphor for what is happening to our climate.This Observatoire Cetelem 2024 once again reveals contrasting viewpoints,some surprising and some concerning.These will no doubt prompt a response among all automotive stakeholders,particularly the carmakers themselves.But if there is one thing that everyone will surely agree on,it is the need for this fog to clear as quickly as possible,so as not to be detrimental to us all.Flavien Neuvy Head of LObservatoire CetelemLObservatoire Cetelem 202403LOBSERVATOIRE CETELEMFlavien Neuvy,Head of LObservatoire Cetelem: 33(0)6 47 59 35 54 favien.neuvybnpparibas- Patricia Bosc,Managing Editor:07 62 78 73 48 patricia.boscbnpparibas-Founded in 1985 and headed by Flavien Neuvy,LObservatoire Cetelem is an economic research and intelligence unit of BNP Paribas Personal Finance.Its mission is to observe,highlight and interpret shifts in consumption patterns in France and abroad.To fulfl this ambition,LObservatoire Cetelem has set up a range of tools that rely on diverse and complementary content,including:-The Observatoires:Two highly respected annual surveys conducted internationally:a worldwide survey on the automotive market(16 countries)and a European survey on consumer trends(15 countries).-The zOOm reports,which focus on lifestyles and explore major themes(“The French and their fnances”,“Food at a time of tough fnancial choices”,etc.)in three stages,by seeking the opinion of French consumers via three-wave surveys.CONTACTS04TABLE OF CONTENTSA SHIFTING CONTEXT THAT IS DIFFICULT TO GRASP 07Price,frst and foremost 08Energy costs,but thats not all 09A future marked by price hikes 11Buying a car:a difcult decision 131A BLURRING OF THE LINES 17Vague information is hampering decision making 18Motorists face diverse and complex regulations 22LEZs:an overarching sense of injustice 27Technical regulations that are indeed very technical 342BUYING A CAR CAN WAIT 41Faith in the future and innovation 42Electric cars are taking centre stage.but raise new questions 48Motorists would like support to switch to electric vehicles 56China versus the rest of the world 62The time to buy.or not 703EPILOGUE 78THE COUNTRIES OF LOBSERVATOIRE CETELEM 77MARKET FIGURES 9505LObservatoire Cetelem 202406Like all consumer goods,car sales are heavily dependent on price,which is the main factor that future buyers take into account.As we are all aware,this is a criterion that has become even more salient and crucial in these highly infationary times.Against this backdrop of economic and fnancial uncertainty,the diffculty involved in making a purchasing decision cannot be reduced to economic factors alone,and this is ultimately not a choice that can be made lightly.A SHIFTING CONTEXT THAT IS DIFFICULT TO GRASP107LObservatoire Cetelem 2024Price,frst and foremostAUTOMOBILE MY DEARIn the previous Observatoire Cetelem,entitled “Cars:whatever it takes”,we took a detailed look at the impact of price on the automotive market.Here,price was described by many as a glass ceiling,and its impact was felt both when buying and using a vehicle.As a reminder,6 out of 10 people said that the cost of vehicles,when it came to both their purchase and their use,was too high.After energy,vehicle maintenance is the expense hit hardest by infation.BRANDS HAVE CAPITALISEDThis sense that prices were too high refected the fact that most brands had gambled on achieving high margins,to the detriment of sales volumes,which allowed them to make record profts.Today,the price war seems to have resumed.Ever the disruptor,Tesla recently lowered the prices of its cars by several thousand euros overnight.Chinese manufacturers,including MG and BYD,are gearing up to launch entry-level models that will compete directly with the most popular European offerings.With their war chests now bolstered,some manufacturers say they are relatively confdent about the upcoming battle.In the frst half of the year,Stellantis posted profts of 10.9 billion,up 37%on 2022,with an operating margin of 14.4%,higher than Teslas and the highest of all the carmakers.08Energy costs,but thats not allCOST INCREASES ACROSS THE BOARDTo make matters worse,infation is still high in most countries,sitting above the acceptable level set by central banks.This has negatively impacted the economic perceptions of motorists,particularly with regard to energy costs.Almost 9 out of 10 motorists point to a rise in the price of petrol,diesel and electricity(Fig.1).The Turks and Italians are the most vocal on this issue,while the Chinese are more measured.There is also a sense that running a vehicle is becoming more and more expensive,more so even than buying one.Indeed,after energy,vehicle maintenance is the expense hit hardest by infation.3 out of 4 respondents make this point,with the Turks and Mexicans again topping the list,while the Japanese and Norwegians are at the other end of the scale.The rising cost of new cars comes fourth in this ranking,only just ahead of the price of used cars,with 7 out of 10 people underlining this factor.Source:LObservatoire Cetelem de lAutomobile 2024.Fig.1 Have you noticed an increase in the price of the following goods and services over the last 12 months?Share of respondents who answered“Yes,a signifcant increase”or“Yes,a moderate increase”.To all respondents.In%.Petrol,diesel 86 86Electricity 87 85Car maintenance 75 75New cars 69 71Car insurance 69 69Public transport 64 64Used cars 62 63Car taxes 62 63Car rental 44 4816-country average Europe average09LObservatoire Cetelem 2024ENERGY:A MAJOR EXPENSEOne of the consequences of the war in Ukraine has been the soaring price of all forms of energy,something that cannot be overlooked.The volatility of fuel itself is matched only by that of its cost,which fuctuates by its very nature,exacerbating the uncertainty felt by motorists.From one country to the next and from one year to the next,it is hard to know what to expect and therefore how to budget for fuel expenses(Fig.2).Whats more,consumers are more likely to see prices at the pump rise than to see them fall.The measures put in place to rein in costs,including in France,are often short lived and quickly fall into a state of consumer limbo,before disappearing from the economic landscape.In addition,deliberate production cuts in Saudi Arabia and Russia are pushing prices back up.Fig.2/ContextPrice of a litre of petrol at the pump.In dollars.HY1 2023 2022 2018Germany 1.72 1.93 1.98Austria 1.49 1.83 1.78Belgium 1.73 2.02 1.97Spain 1.53 1.92 1.77France 1.81 1.99 2.11Italy 1.97 2.00 2.10Norway 1.90 2.26 2.05Netherlands 2.01 2.28 1.93Poland 1.35 1.50 1.56Portugal 1.86 1.94 1.82United Kingdom 1.67 2.05 1.71China 0.86 0.99 0.93United States 0.73 0.98 0.92Japan 1.36 1.29 1.24Mexico 0.94 1.08 1.22Turkey 1.33 1.22 1.14Sources:Trading Economics,Europe Energy Portal,National Bureau of Statistics of China,Turkiye Petrolleri,Direccao geral de energia e geologia,Statistics Norway,RAC Motoring Services UK,US Energy Information Administration,Agency for Natural Resources and Energy,Statistics Belgium.10Price rises are not just an issue today,as these look set to continue in the future.For consumers,there is little hope of the situation improving over the next few years as far as motoring costs are concerned.However,a slight shift in opinion can be noted,with car maintenance becoming the expense about which they are most concerned when it comes to price rises.8 out of 10 people are of this view,with the Turks and Mexicans once again being the most fearful of this possibility,while the Chinese A future marked by price hikesremain the most relaxed.It is quite paradoxical to see maintenance at the top of this list,given that we will be looking at an entirely electric automotive world in the not-too-distant future.Indeed,electric vehicles are said to have inherently lower maintenance costs.Either motorists are not fully aware of this,or this electric future does not seem to them to be quite so close(see part 3).In any case,there appears to be a certain amount of confusion on this issue.11LObservatoire Cetelem 2024Lastly,we should note that the rise in the price of used cars sits at the bottom of the ranking(Fig.3).However,on this question,the French share the concerns of the Turks and Mexicans,albeit to a more moderate degree.Having been struck by recent price increases across the board,three-quarters of motorists place rising car prices as their second biggest worry.Consumers in Turkey and Mexico are again the most likely to express concern in this area,while the Chinese once more demonstrate the greatest degree of serenity.A similar proportion of people also expect an increase in the cost of fuel,with the Netherlands joining the traditionally more pessimistic countries in this respect.Fig.3Do you believe that the following goods and services will see their prices rise,fall or remain stable over the next fve years?Share of respondents who answered“Yes,a signifcant increase”or“Yes,a moderate increase”.To all respondents.In%.Source:LObservatoire Cetelem de lAutomobile 2024.Car maintenance78New cars76Petrol,diesel76Car insurance74Electricity74Car taxes73Public transport70Car rental69Used cars6512Buying a car:a difcult decisionAgainst this backdrop of economic and fnancial instability,the question of whether or not to buy a car is not an easy one to answer.Nearly 6 out of 10 people say that it is a diffcult or very diffcult decision(Fig.4).This view is held particularly strongly in Turkey,where almost 8 out of 10 people are in a state of uncertainty.The Portuguese and Belgians are the next most likely to fnd themselves in the same quandary.For 6 out of 10 people the decision to buy a car is a diffcult one.Conversely,the Chinese are by far the least likely to be wracked by doubt on this matter,with three-quarters of motorists believing that making the decision to buy a car is easy.A majority of people in the USA,Norway and the UK also share this belief.Yet in many countries,this decision is not an easy one to make.Beyond the issue of price,which remains the main factor when deciding to make a purchase,this latest edition of the LObservatoire Cetelem looks at the reasons why motorists may be unsure,hesitant or even sceptical about the merits of buying a new car.13LObservatoire Cetelem 2024Fig.4Today,do you feel that buying a car is an easy or a diffcult decision?To all respondents.In%.Source:LObservatoire Cetelem de lAutomobile 2024.Diffcult EasyGermany 4753Austria4159Belgium 3169Spain3565France 3664Italy4060Norway5347Netherlands3862Poland3664Portugal2773United Kingdom5248China7426United States5842Japan3268Mexico4258Turkey237716-COUNTRY AVERAGE 42X%EUROPE AVERAGE 40%THE ESSENTIAL144 OUT OF 10 MOTORISTS BELIEVE THAT THE POTENTIAL FOR ENERGY COSTS TO RISE IS A BARRIER TO MAKING A PURCHASE6 OUT OF 10 PEOPLEbelieve that it is diffcult to buy a car8 OUT OF 10 PEOPLE fear that car maintenance costs will rise in the future76%OF MOTORISTS EXPECT NEW-CAR PRICES TO RISE IN THE FUTURE THE ESSENTIAL15LObservatoire Cetelem 20241516The fog in which we fnd ourselves is materialised not just by a total lack of visibility regarding the future,but also by our struggle to comprehend what we are presented with.This is starkly refected in the opinions of those surveyed as part of this latest Observatoire Cetelem.Whether it be information about the automotive industry,restricted traffc zones or engine regulations,their views highlight the lack of clarity,the complexity and the volatility surrounding these issues.The result is the emergence from this general haze of a strong sense of injustice.2A BLURRING OF THE LINES17LObservatoire Cetelem 2024Vague information is hampering decision makingPRICES,REGULATIONS AND BRANDS:THREE TOPICS ON WHICH INFORMATION IS LACKINGA glittering symbol of the American way of life,an iconic product in Europes more established nations and an indicator of development in Asian countries,China in particular,the automobile is a topic of huge importance in social and economic spheres.Whether we are“pro”or“anti”,everyone has an opinion on cars,a topic that seems to trigger contrasting emotions like no other.However,the certainty that cars will remain omnipotent and omnipresent partially masks a relative dearth of information,making it diffcult for motorists to make informed choices.Paradoxically,information does not appear to circulate best where one would expect it to.Generally speaking,Europeans display a lack of knowledge on most topics.Japan,in particular,suffers from a far more opaque information environment than all the other countries in this Observatoire Cetelem,with scores that consistently exceed 70%.Also worth noting is that women,seniors and those on the lowest incomes are more likely to declare that they are poorly informed.More specifcally,1 in 2 people cite a lack of information regarding new regulations on engine types and traffc restrictions.This confusion is particularly acute in Japan,of course,but also in Norway.Conversely,the Italians,as well as the Chinese and the Spanish,believe they are well informed on this issue.18In second place,information about the newest brands is inadequate in the eyes of 48%of respondents.Japan once again,but also Norway,Poland and Austria,all post above-average results.Once more,the Italians,together with the Americans,Mexicans,Turks and Chinese believe themselves to be more erudite on such matters.An almost equal proportion of motorists feel that they do not have all the information they need regarding price trends(45%).The usual quartet comprising the Americans,Chinese,Turks and Mexicans express this view most vehemently,contrary to the Japanese,Norwegians,Poles and French.If we had to illustrate the fog in which motorists currently fnd themselves,we would put forward their level of awareness of regulations,brands and prices as tangible evidence.We will be broaching each of these topics in greater detail later on.While still somewhat vague,information regarding technology as a whole seems to be communicated more effectively.Only 4 out of 10 people consider themselves to be poorly informed on this topic.There are as many Japanese consumers who are of this view as there are Chinese and Mexicans who believe the opposite(Fig.5).19LObservatoire Cetelem 2024 Price trends New brands New regulations(bans on internal combustion vehicles in some regions of the world and traffc restrictions)New technologies(energy sources,connected vehicles)Germany 44 49 44 40Austria 49 52 52 46Belgium 47 50 49 44Spain 45 45 42 36France 49 45 51 44Italy 30 35 31 25Norway 53 59 60 45Netherlands 44 46 47 40Poland 50 52 45 48Portugal 45 43 52 34United Kingdom 47 47 51 41China 35 40 42 29United States 34 35 48 31Japan 74 75 77 72Mexico 39 36 53 29Turkey 36 38 50 35Source:LObservatoire Cetelem de lAutomobile 2024.Fig.5How well informed are you on each of the following automotive topics?Share of respondents who replied“Not suffciently well informed”.To all respondents.In%.EUROPE AVERAGE 45HH-COUNTRY AVERAGE 45GP Source:MFig.6/ContextBreakdown of global annual sales of passenger cars by energy source2010 50 million vehicles2022 58 million vehicles Petrol-diesel98.38%Standard electric0.01%Hybrid vehicle1.61%Petrol-diesel74.35%Standard electric12.44%Hybrid vehicle5.38%Plug-in hybrid4.48%Mild hybrid3.34%Hydrogen vehicle0.01%A GROWING VARIETY OF POWERTRAINSThere was a time when the automotive world was simple and split into two camps,with petrol fans on one side and diesel fans on the other.In 2010,these two engine types accounted for 90%of sales.Thirteen years on,with overall sales having increased by almost 20%,everything has become more complicated.With electric,fully hybrid and plug-in hybrid vehicles,not to mention biofuel and hydrogen power,whose presence is current limited but which could emerge in the long term,the variety of powertrains has expanded to the point that it is now much more diffcult for motorists to make the right choice(Fig.6).21LObservatoire Cetelem 2024Motorists face diverse and complex regulationsLEZS:CONFUSION REIGNSWith ZFEs in France(Zone Faibles missions),ZTLs in Italy(Zona Traffco Limitato),LEZs(Low Emission Zones)and ULEZs(Ultra Low Emission Zones)in the UK,or even ZEZs(Zero Emission Zones),all kinds of acronyms are now fghting it out to describe the same reality.These are urban areas to which access is granted only to the least polluting vehicles,according to criteria defned by the government,in the aim of improving air quality and public health.Regardless of the name they are given,they differ from RTZs(Restricted Traffc Zones),which are not contingent on pollutant emissions.Sweden was a pioneer in this feld in the late 1990s and other European countries later followed suit.With the introduction of these LEZs,motorists are now faced with a shifting reality,a kind of regulatory chameleon.22LEZS,FOLLOW THE GUIDE!NORWAY:three zones,in Bergen,Kristiansand and Oslo.Toll rates are calculated based on each vehicles pollutant emissions.NETHERLANDS:low-emission zones target diesel vehicles only.The rules are enforced by cameras and by the police.PORTUGAL:the Lisbon area is divided into two zones,one where the minimum requirement is Euro 2 and the other where it is Euro 3.UNITED KINGDOM:22 low-emission zones in the United Kingdom,with varying requirements and timetables.GERMANY:82 environmental zones in Germany,with different rules and timetables.SPAIN:the“Distintivo Ambiental”environmental badge must be affxed to the windscreens of Spanish and foreign vehicles if they wish to enter such zones.FRANCE:a CritAir sticker,of which there are six different categories,is required for French or foreign vehicles to enter LEZs.ITALY:there are several zones in Italy,with requirements and timetables that differ from region to region,and even from one city to the next.BELGIUM:Antwerp and Brussels city centres are designated environmental zones.JAPAN:fve prefectures have introduced a low-emissions policy,resulting in a ban on high-polluting diesel lorries and buses entering certain zones.With the introduction of these LEZs,motorists are now faced with a shifting reality,a kind of regulatory chameleon that is constantly adapting to its environment.The underlying principles and implementation of LEZs vary greatly from country to country.Whats more,regulations within a country can differ from one city to the next and at any time.Out of all the countries covered by this survey,only four have not yet set up LEZs:China(only applicable to heavy goods vehicles),the United States(one such zone is being trialled in Santa Monica,California),Turkey and Mexico(where projects are under discussion).23LObservatoire Cetelem 2024TECHNICAL REGULATIONS:AN EU MEASURE THAT HAS CREATED A FOGWhen it comes to engine regulations,a strong technical background is needed to keep up with all the subtleties.While these requirements have naturally evolved in step with scientifc knowledge,manufacturers have also applied as much pressure as possible to delay their implementation or steer them in their preferred direction,as illustrated by the so-called Ferrari EUROS VISION,NAME THAT TUNE!Euro 1:vehicles are only tested for hydrocarbons,nitrogen oxides and particulates in the case of diesel engines.Switch to unleaded petrol.Euro 2:reduction of carbon monoxide and the unburnt hydrocarbons nitrogen oxide combination.Catalytic converters mandatory on diesel engines.Euro 3:warm-up period removed from the test procedure.Splits hydrocarbon and nitrogen oxide limits.Applies NOx limits to diesels for the frst time.Euro 5:diesel vehicles are subject to a new limit on particulate emissions.Emission of the equivalent of one grain of sand per kilometre travelled.Introduction of particle flters for new diesel vehicles.Euro 6:exhaust gas recirculation.A portion of these gases is mixed with the intake air to lower the combustion temperature.Euro 6a/6b:limits on NOx gas emissions.Selective catalytic reduction,in which a liquid reducing agent is injected through a catalyst into the exhaust of a diesel vehicle.Euro 7:vehicles are required to remain compliant for longer.Brakes and tyres are taken into account in limiting particulate emissions from combustion and electric vehicles.amendment*to EU regulations,which was recently adopted.Others have chosen to bend the rules,or even circumnavigate them entirely in the case of Volkswagen.A quick glance at these European examples is enough to realise the complexity facing motorists.*This amendment passed by the European Parliament gives manufacturers of ultra-luxury cars additional time to go all-electric and reduce their CO2 emissions24MOTORISTS APPARENTLY UNDERSTAND THIS WELLFaced with this regulatory jungle,the clear-sightedness of motorists can only be applauded.6 out of 10 respondents consider them to be a decent solution to current problems.The Turks,Mexicans and Chinese are once again the most likely to display this level of understanding,along with the Spanish,Portuguese and Italians(around 80%).Conversely,the Japanese sharply disagree on this point(72%do not understand).In fact,Japan is the only country,along with Norway,where negative views outweigh positive opinion.In France,the“yes”camp achieves a slim majority.An almost identical proportion of motorists also feel that they understand what is prohibited and what is permitted.On this question,a largely similar geographical split is apparent,although the Portuguese seem slightly less convinced.Once again,the Japanese are by far the most likely to express confusion(75%).Above all,however,just over 7 out of 10 respondents understand the reasons behind these regulations,with the Mexicans and Turks again emerging as the undisputed champions of regulatory intelligence while the Japanese remain stubbornly entrenched at the foot of the ranking.It should be noted here that Japan is the only country where a majority of people claim not to understand anything(Fig.7).Rural dwellers are also less convinced than urbanites when it comes to the effectiveness of these measures in solving environmental problems.So,is a comprehensive understanding of these complex measures relating to traffc and engine types enough for them to be accepted wholesale?Not especially,because the reasons behind the concerns and worries of motorists are not confned to the regulatory framework they inhabit.25LObservatoire Cetelem 2024Fig.7Do you feel that you understand these regulations well (restricted zones set up to improve air quality,LEZs/bans on the sale of internal combustion vehicles)?Share of respondents who answered“YES”.To all respondents.In%.Source:LObservatoire Cetelem de lAutomobile 2024.Germany 63 60 74Austria 61 57 71Belgium 55 52 67Spain 71 72 78France 58 53 66Italy 68 68 81Norway 47 47 59Netherlands 54 53 72Poland 65 62 69Portugal 63 68 79United Kingdom 54 55 70China 76 71 80United States 56 62 73Japan 25 28 40Mexico 77 79 87Turkey 78 80 84 What is prohibited and what is permitted under these regulationsHow do these regulations help to address current problems?The reasons behind these regulationsEUROPE AVERAGE 60Yq-COUNTRY AVERAGE 61r&LEZs:an overarching sense of injusticeINFORMATION IS OFTEN POORLY UNDERSTOODIndeed,the reality of peoples level of understanding is more complex and offers contrasting lessons when studied in detail.On the subject of LEZs,while more than 7 out of 10 people are aware of their existence,only a third know exactly what they are.Thats almost the same as the proportion of people who are completely ignorant of their meaning.This split into three almost equal blocs underlines the uncertainty that surrounds these regulations,with their shifting names and defnitions.LEZ is a term full of signifcance.but what does it actually mean?Well,thats precisely the problem.An examination of the geographical breakdown of the opinions gathered reveals a relative reversal of the trends that had prevailed up until now.Today,most of the European countries surveyed,particularly those where LEZs are in place,rank highly when it comes to the proportion of motorists with specifc awareness of their existence.This is particularly true for Germany,Belgium,Italy and France,which post scores of 50%or close to it.Meanwhile,in Mexico and Turkey(which are not affected by these measures),but also in the Netherlands and Austria,the level of knowledge regarding LEZs is low.For instance,only 14%of Mexicans claim to understand what they entail.Once again,Japan stands out.Only 10%of Japanese respondents have precise knowledge of these zones,while more than half plead complete ignorance,making them the only population for which this is the case(Fig.8).When it comes to LEZs,only 1 in 3 people know exactly what they are.27LObservatoire Cetelem 2024Fig.8Were you aware of the existence of these regulations around the world(LEZs)?To all respondents.In%.No Yes,but you dont know exactly what they entail Yes,and you know exactly what they entail16-COUNTRY AVERAGE 2794%EUROPE AVERAGE 2389%Source:LObservatoire Cetelem de lAutomobile 2024.145135205030282547184438234829124840332938364321144046334027224434223642423028523810315514292546Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeyNEGATIVE RESPONSES However,an individuals relative familiarity with LEZs does not mean that they will agree with them in practice.It is true that 66%of those surveyed believe them to be a positive measure.But the countries in which LEZs are widespread and have been established the longest are home to the highest proportion of naysayers,which include more than half of French and Belgian respondents.Conversely,almost half of the Turks and Mexicans surveyed strongly agree with the concept,whereas the smallest proportion of individuals who have a clear opinion on the topic can also be found in Turkey and Mexico,a sign of the level of interest in these measures in two countries where LEZs do not yet exist.28So,are these measures viewed positively?Not especially,if we are to believe a set of results that cast LEZs in a highly negative light and refect suspicion,if not a complete rejection.First and foremost,8 out of 10 people consider such measures to be unfair to low-income households,once again underlining the importance of fnancial aspects when it comes to motoring.As if to echo the Yellow Vests crisis,which was born out of a political decision that affected peoples cars and wallets alike,the French are the most likely to condemn the fnancial impact of LEZs(85%).The second biggest source of criticism is the speed with which such measures are implemented.7 out of 10 people feel that the timetable is too strict.On this topic,the Belgians and the French are the most critical.Paradoxically,while LEZs are considered fair from a conceptual perspective,they are also deemed insuffcient.Once again,we fnd the Turks at the top of the ranking(85%),followed most closely by the Chinese and Italians.In the neighbouring countries of the Netherlands and Belgium,this opinion is only half as common.The measures are considered insuffcient and therefore ineffective in fghting pollution.Nearly 6 out of 10 people are of this belief.Once again,the European countries surveyed,led by Germany and France,stand as one in sharing this opinion,while China and Japan are also united for once,with a majority believing that LEZs are effective.Source:LObservatoire Cetelem de lAutomobile 2024.Fig.9 Do you agree or disagree with each of the following statements regarding the restricted zones set up to improve air quality(LEZs)?Share of respondents who answered“Strongly agree”or“Somewhat agree”.In%.Its unfair on low-income households,because they wont be able to afford the latest vehicles that can be used in these zones.82 80The timetable is too strict 71 70Its a good and necessary measure 62 66Its an effective way of combatting pollution 61 58Its unrealistic and these regulations will either never come into force or be cancelled 56 57The measure is insuffcient 54 5916-country average Europe averageFinally,almost 6 out of 10 people go as far as to say that LEZs are unrealistic and that they hope they will never see the light of day.This is a viewpoint held by a majority of respondents in all countries,even those in which they have been a reality for some time now(Fig.9).29LObservatoire Cetelem 2024LEZS,A MATTER FOR THE PRESENT OR THE FUTURE?But do motorists think that these LEZs actually exist?Here again,motorists are slightly mystifed.Only 4 out of 10 respondents say that they are in place in their country.But a sense of reason prevails.The highest scores can be observed in Germany,Belgium,the United Kingdom and France,all of which have introduced LEZs or are planning to do so.And where do negative answers account for the majority?In Japan,of course(Fig.10).Things are even more opaque when it comes to predicting the future.1 in 2 motorists do not know whether LEZs will be put in place in their country.In half the countries surveyed,the proportion of people who admit that they do not know actually exceeds 50%,with the Norwegians,the Austrians and,once more,the Japanese pleading ignorance regarding future LEZs.Much like previously,the more established European countries are home to the highest proportions of respondents who state that the future of LEZs is written(Fig.11).Source:LObservatoire Cetelem de lAutomobile 2024.Fig.10Do you believe that your country currently has zones of this type(LEZs)?To all respondents.In%.Yes No You dont know23671040204023698355873059113146235118314615393739244884428591337422147312249351649292250222816-COUNTRY AVERAGE 39 A%EUROPE AVERAGE 36G%Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey30Both of these points only serve to highlight the genuine scepticism of motorists,who sometimes firt with reality denial by refusing to believe in the possibility of implementing measures that are already in place in their country.Alternatively,this could be viewed as a blinkered and selfsh stance:“they dont exist because they dont affect me”.Fig.11Do you know whether your country has any plans for such zones(LEZs)in the near future?To all respondents.In%.No,you dont knowYes,you know that these wont be put in place in the near future Yes,you know that some cities will be introducing LEZs in the near future.Source:LObservatoire Cetelem de lAutomobile 2024.395386125143655937501313355114632895663845421354937385393941205335127791456152955271816-COUNTRY AVERAGE 48%EUROPE AVERAGE 45D057Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey1 in 2 motorists do not know whether LEZs will be put in place in their country.31LObservatoire Cetelem 2024DRIVING IN LEZS IS POSSIBLEWhether or not LEZs are in place,a narrow majority of respondents(55%)are confdent that their vehicle will be able to enter these zones.But on this topic,the blocs of opinion formed previously fragment.For once,China and the USA are united in stating this most confdently,followed by Belgium and Germany.Surprisingly,in the highly electrifed country of Norway,6 out of 10 respondents believe that their vehicle will be excluded from LEZs.This score is head and shoulders above the rest.More astonishing still,10%of those who own an electric vehicle do not know whether they will be able to drive it in LEZs(Fig.12).Fig.12As far as you know,will your current vehicle be allowed into these zones(LEZs)in the near future?To those who have at least one car in their household and whose country has,as far as they know,introduced(or is going to introduce)LEZs.In%.Yes,it will be allowed No,it wont be allowed You dont knowSource:LObservatoire Cetelem de lAutomobile 2024.2264142539361165241456301446401328591721622134451937442057231271179761527264715256017632016-COUNTRY AVERAGE 16)U%EUROPE AVERAGE 162Rt647Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey32THE BIGGER,THE BETTERIts dimensions are gargantuan:4.90 m long,1.93 m wide,over 2 m high.Its 6-cylinder engine produces 285 bhp in its petrol version and 249 bhp in its diesel version.It consumes 14 litres of fuel per 100 km and emits 336 grams of CO2 per kilometre.And yet it will be able to enter Frances LEZs,with a CritAir 1 sticker for the petrol version and a CritAir 2 sticker for the diesel.We are talking about the Ineos Grenadier 4x4.Source:LObservatoire Cetelem de lAutomobile 2024.Fig.13If such zones were introduced near you,which would be your preferred solutions?To those who think that their vehicle will not be allowed in LEZs or do not know.Select one or more answers.In%.You will acquire a vehicle that is permitted to use these zones 22 27 54You will avoid entering these zones 45 42 38You will use a different form of transport(bus,bicycle,etc.)27 29 51You will continue to use your car even if it is prohibited 14 13 13You havent thought about this yet 19 17 7China 16-country average Europe averageA CAPACITY TO ADAPTFaced with the possibility that they will not be able to drive in these zones,motorists are organising themselves in a very pragmatic and fexible way.In China,the emphasis is on fnding strategies to avoid or bypass LEZs,both literally and fguratively.More than 1 in 2 Chinese respondents would buy an authorised vehicle or switch to soft mobility.On average,around 30%of those surveyed are in favour of these two solutions.The Turks and Mexicans,and to a lesser extent the Italians,also favour the former.The latter is most popular in Mexico,but also in Japan.Both options are preferred by a majority of women and seniors.The French spirit of opposition(and resistance)is alive and well.1 in 2 will continue to drive their banned vehicle in LEZs.This rebellious attitude is shared by the Germans.It should also be noted that only a quarter of those surveyed would consider replacing their vehicle(Fig.13).33LObservatoire Cetelem 2024LACK OF KNOWLEDGE IS GEOGRAPHICALLY DEPENDENTAs we have already seen,confusion and scepticism reign on the topic of LEZs,regarding both their existence and their implications.The same is true of engine regulations and possibly even more so.Opinion is split almost equally between those who say they are aware of the ban on the sale of combustion engine vehicles as of 2035 and those who are not.European countries,where manufacturers have lobbied hard against these regulations,are home to the largest number of motorists who have knowledge of these measures.Germany tops the list,with the highest proportion of individuals who bemoan such regulations.The level of knowledge is lowest in Mexico and Japan,where 7 out of 10 people are unaware of these measures.Turkey,the United States,China and France rank somewhere in the middle(Fig.14).Technical regulations that are indeed very technicalOpinion is split between those who say they are aware of the ban on the sale of internal combustion vehicles and those who are not.34Fig.14In some countries,there are regulations that will ban the sale of internal combustion vehicles(petrol,diesel,hybrid)within the next 10 to 15 years,so as to combat air pollution.Do you know whether such regulations are in place in your country?To all respondents.In%.No,you dont know whether such regulations are in place in your country Yes,you know that such regulations are in place in your countrySource:LObservatoire Cetelem de lAutomobile 2024.66346040554553473763574344564159366462385347514929712773495116-COUNTRY AVERAGE 51I%EUROPE AVERAGE 48Rb38Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey35LObservatoire Cetelem 2024A REJECTION OF ENGINE REGULATIONSIn keeping with their contrasting opinions on LEZs,motorists express similarly contradictory views when it comes to regulations for internal combustion vehicles.More than 6 out of 10 people believe that these measures are sound,but 1 in 2 consider them insuffcient.Like in the case of LEZs,the Turks,Mexicans and Chinese,but also the Portuguese,say that they are justifed.Even a signifcant majority of Americans extol the virtues of such regulations.A large bloc of European countries albeit one that excludes Spain,Portugal and Italy disapprove of them,spearheaded by France.As with LEZs,the main criticism is that the regulations will not affect everyone in equal measure,but will have a greater impact on certain individuals and families.8 out of 10 people state that households would be the frst to suffer if they were unable to sell their internal combustion vehicle,which would make it impossible for them to get around.Once again,it is in France,but also in Belgium,that this sense of injustice is most keenly felt.Although the most coercive measures,at least in Europe,are not set to come into force until 2035,7 out of 10 motorists feel that the timetable for their implementation is too tight.The French and Belgians,once again,criticise the brevity of this timeframe,with the Spanish being similarly disparaging(Fig.15).ZFE36Source:LObservatoire Cetelem de lAutomobile 2024.Fig.15In some countries,there are regulations that will ban the sale of internal combustion vehicles(petrol,diesel,hybrid)within the next 10 to 15 years,so as to combat air pollution.Do you agree or disagree with each of the following statements regarding the ban on the sale of internal combustion vehicles?Share of respondents who answered“Strongly agree”or“Somewhat agree”.To all respondents.In%.It is unfair on households that would struggle to sell their internal combustion vehicle.80 78 The timetable for implementation is too short 71 70 Its unrealistic and this regulation will either never come into force or be cancelled 62 61 Its a good and necessary measure 57 63 Its an effective way of combatting pollution 58 57 The measure is insuffcient 51 55 16-country average Europe average37LObservatoire Cetelem 2024Source:C-Ways.Fig.16/ContextMaximum CO2 emissions per kilometre permitted for new cars In grammes of CO2 per kilometre.120-15%-55%-1000800604020202120222023202420252026202720282029203020312032203320342035114g/kmThese attitudes are emerging in a context where some European governments,and not just carmakers,are calling for a postponement of the zero-CO2 emissions deadline.This does nothing but add to peoples hesitation and thicken the prevailing fog.Similarly,6 out of 10 respondents point to both the unrealistic nature of engine regulations and their ineffectiveness in combatting pollution.As ever,the French and Belgians are the most likely to express this view,but the Poles are equally as vehement.One sign that not everything is clear in the minds of motorists,however,is the fact that half of them feel that this type of measure is insuffcient,with the Turks,Chinese and Italians in particular stating this opinion.Naturally,the Belgians are not particularly concerned about this,much like their Dutch neighbours(Fig.16).THE ESSENTIAL381 IN 2 PEOPLE ARE AWARE OF THE BAN ON THE SALE OF INTERNAL COMBUSTION VEHICLES AS OF 203557%8 OUT OF 10 PEOPLEbelieve that these regulations are unfair to the lowest-income households,because they will not be able to replace their vehicle7 OUT OF 10 PEOPLE are aware of the existence of LEZs,of which 1/3 know exactly what they areBELIEVE THAT ITS AN EFFECTIVE WAY OF COMBATTING POLLUTION 27%OF EUROPEANS ARE PREPARED TO SWITCH TO A DIFFERENT MODE OF TRANSPORT TO ACCESS LEZSTHE ESSENTIAL39LObservatoire Cetelem 202439?40The rise of the electric vehicle seems inevitable.And yet the idea still arouses a degree of suspicion.The energy crisis,particularly as it relates to electricity,has raised doubts as to whether this alternative to internal combustion vehicles will be a complete success,since the raw material needed to power these cars could one day be in short supply.And once again,the price factor prompts fears of a short circuit.People are not against going electric,as long as they receive support.They must also mull over the question of whether to choose a more expensive traditional brand or a cheap Chinese brand with which they are unfamiliar.So,buying electric is something to consider,but perhaps not just yet.This stance is creating even more uncertainty in the market.3BUYING A CAR CAN WAIT41LObservatoire Cetelem 2024Faith in the future and innovation42THE FUTURE OF CARS IS ASSUREDDespite a tough economic climate and a tightening of regulations,most people cannot imagine a world without cars.Only 1 in 5 people expect them to play a less important role in the future than they do today,an opinion expressed most strongly in Europe,particularly by the French(29%).Those who believe in the resilience and omnipresence of cars are represented chiefy by the usual quartet of China,the United States,Mexico and Turkey,the only countries in which more than 50%of respondents expect cars to have a greater presence in the future(Fig.17).Fig.17In fve years time,how important a role do you think cars will play in your country?To all respondents.In%.More important than currently Neither more nor less important than currently Less important than currentlySource:LObservatoire Cetelem de lAutomobile 2024.25245120255523245317295430224824195726561827235030541628205261152454113532541462251366132116-COUNTRY AVERAGE 35E %EUROPE AVERAGE 26R73825Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey43LObservatoire Cetelem 2024A SOURCE OF PROGRESSIn the minds of motorists,the omnipotent automobile is not confned to a glorious,ancient past,but also possesses virtues that make it a natural part of the future,despite the environmental challenges we face.More than 8 out of 10 respondents think that technological advances will result in greener cars.This fnding must be music to the ears of manufacturers,who argue that the solution is rooted in innovation,rather than restrictive regulations.This faith in technological progress is particularly prevalent in China,Mexico and Turkey,as well as in Portugal(Fig.18).Fig.18Do you believe that technological advances will reduce the environmental impact of cars?To all respondents.In%.Yes NoSource:LObservatoire Cetelem de lAutomobile 2024.2575227826742872148618821981208089220807931486158579399116-COUNTRY AVERAGE 17%EUROPE AVERAGE 1986Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey44THE ELECTRIC CAR,A SYMBOL OF INNOVATIONAnd what better way to beneft from virtuous advances while enjoying guaranteed access to all roads than by driving an electric car?Nearly 7 out of 10 people view this type of vehicle as the epitome of technological progress.However,this overall score conceals pronounced differences between the countries,to an extent rarely seen before in this survey,underlining the fact that electric vehicles are far from a self-evident solution in everyones eyes.It is hardly surprising that the two countries in which electric cars have been the most widely adopted are among the closest aligned with this statement,with 88%sharing this view in China and Norway.But the enthusiastic Turks are even further ahead,with 91%fnding themselves in agreement.In contrast to this pro-electric movement,several European countries are reluctant to believe that these vehicles are the embodiment of progress.The proportion of respondents who back this statement in Austria and France is half that of the aforementioned countries(Fig.19).Fig.19Do you believe that electric cars can embody this technological progress?To all respondents.In%.Yes No4852633747535941366436643664247634661288257533671288991307016-COUNTRY AVERAGE 33g%EUROPE AVERAGE 40169Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeySource:LObservatoire Cetelem de lAutomobile 2024.45LObservatoire Cetelem 2024BUT THIS IS BY NO MEANS CLEAR CUTThis“resistance”to electricity in certain countries is confrmed when motorists are asked to project themselves into a totally electric automotive future,which once more produces wide disparities.Again the Austrians and the French are cautious on this matter,with fewer than 4 out of 10 people considering making the switch.Generally speaking,European respondents are not entirely convinced,whereas those in“emerging”countries such as Turkey,Mexico and China tend to be seriously considering this option(Fig.20).Will the development of battery gigafactories,not least in Europe,have any impact on the situation?Fig.20Do you believe that electric vehicles will eventually completely replace combustion-powered cars?To all respondents.In%.Yes NoSource:LObservatoire Cetelem de lAutomobile 2024.51496535554562384654455546545149465443573565386254462971227816-COUNTRY AVERAGE 46T%EUROPE AVERAGE 50PC57Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey46Fig.21In what timeframe do you believe electric cars will completely replace internal combustion engine cars in your country?To those who believe that electric cars will eventually completely replace combustion-powered cars.In%.Within 5 years Within 6 to 15 years Within more than 15 yearsSource:LObservatoire Cetelem de lAutomobile 2024.16-COUNTRY AVERAGE 41B%EUROPE AVERAGE 47922384218403919424512434694554361051123749381343164116176726373743451243381938224042391960319THE CONQUEST COULD BE DELAYEDInternal combustion engine cars still appear to have a few good years ahead of them.Only 2 out of 10 people surveyed expect electric vehicles to completely replace them within the next fve years.4 out of 10 motorists cannot see this happening for another 15 years,which is the timeframe set by the European Union(Fig.21).This is another way for them to express genuine scepticism on the issue,while also highlighting their clear-sightedness and ability to take the long view of the automotive sector,both in terms of innovation and range renewal.Although the differences between the countries are less pronounced in this instance,the segmentation observed for the previous two items is broadly the same.Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey47LObservatoire Cetelem 2024ELECTRIC LEADS THE WAYLObservatoire Cetelem has long paid close attention to electric vehicles,and was among the frst to announce their advent.However,this edition should be seen as something of a milestone,since this type of powertrain now tops the list of purchasing intentions for the very frst time.This is a signifcant breakthrough for electric cars,but combustion engine vehicles are putting up a good fght.1 in 3 people will opt to buy an electric car(Fig.22).If we add to this fgure the number of respondents who state their intention to buy a hybrid car(plug-in or other),it is safe to say that there has been a real shift in the market.The Chinese and,to a lesser extent,the Norwegians consolidate their lead on matters electric,with purchasing intentions of 65%and 43%respectively.At the other end of the scale,France,Belgium,Austria and Poland are again the countries in which these intentions are the least pronounced,at around 20%.Electric cars are taking centre stage.but raise new questionsSource:LObservatoire Cetelem de lAutomobile 2024.Fig.22What type of car are you thinking of buying?To those who wish to buy a car.Select one or more answers.In%.An electric car 27 32 A petrol car 26 30 A plug-in hybrid car 25 25 A non-plug-in hybrid car 14 16 A diesel car 15 14 A hydrogen car 9 9 I dont know 15 12 16-country average Europe average48Fig.23/ContextChange in the number of electric vehicles sold as a share of total new passenger car salesIn%.2010201120122013201420152016201720182019202020212022SpainGermanyNetherlandsUnited KingdomNorwayAustriaBelgiumItalyJapanChinaFranceUnited StatesPolandMexicoTurkeySource:M60805070400302010Portugal49LObservatoire Cetelem 2024THE PROBLEM IS(STILL)THE PRICEHowever,the world of electric cars is not exactly a utopia towards which motorists are blissfully careering.Because if there is one thing that hasnt changed,its all the negative factors that prompt potential buyers to put on the brakes.As always,the main obstacle is fnancial.Almost half of those surveyed believe that the price of electric vehicles is too high,with the Dutch and French the most likely to stress this point.This is a view held by only 13%of respondents in China,which is home to many long-standing converts.There is also reticence due to potential charging diffculties and range limitations.Both of these issues are a worry for around 3 in 10 people.Surprisingly,these issues are of greatest concern in China,in contrast to Mexico where they are seen as less of a problem.It should be noted that vehicle range is also a major concern in France.However,one result will be a source of great reassurance for manufacturers.Barely 10%of motorists fear that they will struggle to resell an electric vehicle.This suggests that there is a real opportunity for electric cars to become a permanent fxture on the automotive landscape(Fig.24).Source:LObservatoire Cetelem de lAutomobile 2024.Fig.24Why dont you want to buy an electric vehicle?To those who do not want to buy an electric vehicle.Select up to three answers.In%.The purchase price is too high 51 48 You fear that you may fnd it diffcult to charge your vehicle 35 36 The range is too short for your needs 33 31 You fear that this type of car will cost too much to charge 27 28 You think that this technology also poses environmental problems 26 22 Youre not sure how reliable it is 18 18 Youre worried that it might be diffcult to sell on 8 9 A different reason 5 5 16-country average Europe average50BATTERIES:A TRICKY CHOICEMotorists are not the only ones who are in a fog.Uncertainty also reigns among manufacturers when it comes to choosing which batteries will equip their cars.Currently,the two options are LPF(lithium-iron-phosphate)batteries and NMC(nickel-manganese-cobalt)batteries.The former are relatively cheap and allow the cost of vehicles to be reduced,but they are diffcult to recycle.The latter are more expensive,but better integrated into the circular economy.They will also be able to use sodium and solid-state batteries within the next few years(Fig.25).What to choose?That is the question.Fig.25/ContextRetail price comparison of the electric and combustion engine versions of three modelsIn euros.30,00040,000 25,00035,00020,000015,00010,0005,000Peugeot 208Renault MganeVolkswagen GolfSource:Manufacturer websites.Electric Combustion engine25,50017,70038,00031,300 212,395 219,350 29%On average 44QLObservatoire Cetelem 2024Germany 74179Austria78175Belgium 78139Spain79156France 77149Italy77176Norway612514Netherlands692011Poland761113Portugal76204United Kingdom75169China67294United States77158Japan652015Mexico83134Turkey622810THE COST OF USE COULD POTENTIALLY BE HIGHThe cost issue is not just confned to the initial purchase of an electric vehicle,but also extends to its day-to-day use.Having witnessed the recent rises in electricity prices and with the potential for more in the future,motorists are in a quandary.Three quarters of motorists believe they will be more expensive to run than a vehicle with a conventional engine.In European countries,particularly Spain,this fear is very real(Fig.26).Fig.26Do you think that the rising price of electricity could make using an electric car too expensive when compared with petrol or diesel cars?To all respondents.In%.Yes No I dont know16-COUNTRY AVERAGE 8t%EUROPE AVERAGE 9t%Source:LObservatoire Cetelem de lAutomobile 2024.52A FUTURE LACKING IN ENERGYNot only could electricity become more expensive,there are also question marks over its supply.Indeed,more even than the planned pre-eminence of electric vehicles,motorists question their very use,as they suspect that power generation will be inadequate in the future.Three-quarters of respondents take this view,no doubt infuenced by the recent energy crises.This seems to exceed the boundaries of mere scepticism.But if we look at the detail,opinions are again extremely variable.The Chinese,and to a lesser extent the Turks,are in very little doubt about the availability of electricity to power their cars.In Europe meanwhile,the concern is palpable,particularly in Austria and Belgium,with the Spanish and their Portuguese neighbours occupying the middle ground.The energy crisis triggered by the war in Ukraine has clearly left its mark(Fig.27).Fig.27Do you believe we will be able to produce enough electricity to meet the requirements of all electric cars?To all respondents.In%.Yes NoSource:LObservatoire Cetelem de lAutomobile 2024.62387327752571295842604063375941514960401783425871294357336716-COUNTRY AVERAGE 55E%EUROPE AVERAGE 628I51Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey53LObservatoire Cetelem 2024Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeySource:OICA,MFig.28/ContextNumber of public charging points and kW per electric light vehicle In 2022.352515540030201026722111310132020241512842034In many countries,charging points are being rolled out at an ever faster pace.In France,the milestone of 100,000 charging points has recently been reached.The fact remains that,in the minds of many motorists,the ability to easily charge an electric vehicle remains an issue that makes it hard for them to decide(Fig.28 and 29).Motorists are today questioning the use of EVs,because they fear that energy generation may be inadequate.54Motorists would like support to switch to electric vehicles55LObservatoire Cetelem 2024GOVERNMENT SUPPORT IS CALLED FOR ACROSS THE BOARDThe desire is there,but there are also obstacles.All that is missing is the nudge that could make all the difference.Almost 3 in 4 of those surveyed would like this nudge to take the form of government subsidies to help them switch from internal combustion engines to electric vehicles.The countries most enthusiastic about electric vehicles are those that are the keenest to receive such support,with Turkey leading the way thanks to an almost unanimous response from its citizens.Even in the United States,a land known for its spirit of free enterprise,such subsidies would be welcomed.Might the Biden plan*have something to do with it?In Austria,and to a lesser extent in Norway and Belgium,demand for measures of this kind is less acute(Fig.30).*The Biden plan provides for$370 billion in funding to reduce greenhouse gas emissions by 40tween now and 2030.Fig.30Do you think the government should provide subsidies to motorists who want to replace their combustion-powered car with an electric car?To all respondents.In%.Source:LObservatoire Cetelem de lAutomobile 2024.Yes No16-COUNTRY AVERAGE 24v%EUROPE AVERAGE 27s36743573367316915853565267429711585257517832179326811897931783Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey56Sources:OICA,MGermany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkey1,2001,400 1,800 1,600 1,0001,3008000600400200Fig.29/ContextNumber of charging points in the country In thousands.2015 2019 202257LObservatoire Cetelem 2024Fig.31Do you know whether government subsidies are available in your country to help motorists replace their combustion-powered car with an electric vehicle?To all respondents.In%.Yes No16-COUNTRY AVERAGE 54F%EUROPE AVERAGE 54F862475370303466485271294951663451497228267455455347732759414654Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeyKNOWLEDGE ABOUT SUBSIDIES IS LACKINGAs we saw previously on the question of cars in general,there is also quite a clear lack of awareness when it comes to the existence of local subsidies.Just over half of the motorists surveyed have no idea whether any are available in their country.Individuals in the leading European Union countries,with the exception of Belgium,tend to be well informed,unlike in Mexico,Norway and the United Kingdom,where subsidies have been available since 2011(Fig.31).Just over half of the motorists surveyed have no idea whether government subsidies are available in their country.Source:LObservatoire Cetelem de lAutomobile 2024.58ESSENTIAL AND COMPLEXThe necessity of these subsidies is unquestionable.8 out of 10 people consider them essential.The Chinese,Turks,French,Spanish and Americans are their most vocal supporters.But the fog returns to render the detail behind these measures opaque,once again leaving motorists with doubts and questions.More than 7 out of 10 respondents fnd them too confusing.The French and Poles are the most likely to bemoan this complexity,which is often of an administrative nature.They are seen in equal measure as confusing and marred by inadequate communication that hinders awareness.This time,a majority of Turks and Mexicans voice their dissatisfaction on these points.The fact that this support is only accessible to a limited number of motorists generates a similarly high level of disapproval,the sense being that only the rich beneft,since they alone can afford to buy electric vehicles,which are more expensive than average.This result echoes the feeling of injustice prompted by LEZs,which are seen as penalising low-income households frst and foremost.This is a stance that is particularly prevalent in Mexico,the UK,Italy,France and Poland.Setting aside the factors that cause the fog to thicken,the issue of price is the dominant one in most peoples minds.Lastly,55em the subsidies to be high enough in value.45%go so far as to say that they are too high(Fig.32).Fig.32Regarding these government subsidies,would you say that.?To those who believe that there are government subsidies in their country to help them replace their combustion engine vehicle with an electric one.In%.They are essential to help motorists 76 79They are complicated and confusing 75 72 They only cover a few special cases and are not aimed at enough motorists.74 73 People are not suffciently familiar with them,there is not enough communication 72 73 The sums offered meet the needs of motorists 46 55 There are too many 45 49 16-country average Europe averageSource:LObservatoire Cetelem de lAutomobile 2024.59LObservatoire Cetelem 2024SUBSIDIES BY COUNTRYFRANCE:under the Bonus/Penalty system,vehicles that emit less than 20g/km of CO2 beneft from a one-off bonus of 7,000.For vehicles between 21 and 50 g/km,the bonus is 5,000.UNITED KINGDOM:Since 2011,motorists who buy a new electric car(BEV or PHEV emitting less than 75g CO2/km,or a fuel cell vehicle)receive a one-off bonus worth 25%of the price of their car,up to a maximum of 5,000(around 5,800).SWEDEN:Since 2012,cars that emit 50g/km of CO2 or less receive a one-off bonus of SEK 40,000(around 4,500).The programme will run until 2014 and will be available to a maximum of 5,000 cars.U.S.A.:the average incentive offered to buyers of PHEVs and BEVs in the United States is less than$1,000 per vehicle.States such as Colorado,Illinois,Louisiana and California offer between$2,000 and$6,000 per vehicle.Fig.33In the future,do you believe that the government subsidies available to help motorists replace their combustion engine car with an electric vehicle.?To those who think that government subsidies are available in their country to help them replace their combustion engine car with an electric vehicle.In%.Will stop Will continue16-COUNTRY AVERAGE 646%EUROPE AVERAGE 58BQ49505056445743752542584654762450506832811984165446821881197129Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeySource:LObservatoire Cetelem de lAutomobile 2024.60Fig.34Do you believe that the government subsidies available to help motorists replace their combustion engine car with an electric vehicle.?To those who think the subsidies will remain in place.In%.Will increase Will stay the same Will decrease Source:LObservatoire Cetelem de lAutomobile 2024.3027432527482025551840423526392249291636481942391535507504320493127492411533612484010533716-COUNTRY AVERAGE 18E7%EUROPE AVERAGE 20G3 4733Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeyLETS HOPE IT LASTSThese subsidies will be just as useful in the future as they are today Just 1 in 5 of those who believe they will remain in force think that they will be reduced.Twice as many are hopeful that they will increase.This hope is expressed by 1 in 2 respondents in China,the United States and Turkey.45lieve that their value will remain the same,with France,Spain and Mexico being the only countries where this is the majority view(Fig.33 and 34).61LObservatoire Cetelem 2024ELECTRICITY IS MAKING ITS MARK,THANKS TO CHINAWith the switch to an electric world now in full swing,motorists will no longer be able to rely on their usual points of reference and the trust they have traditionally placed in historic brands.The energy transition is impacting the automotive industry like no other innovation before it.What they now have in front of them is a contrasting and shifting automotive market.But this is only the beginning.The exponential growth of the Chinese market and its brands is striking proof of this transformation.In just over two decades,more than 20 new brands have seen the light of day(Fig.35).Most of these brands are developing electric vehicles.And thats without counting the brands that were already present on the market which,as in the case of MG and even more so BYD,a premium all-electric China versus the rest of the worldA number of brands are intent on shaking up the market and winning over motorists with low-cost electric vehicles.62brand,intend to shake things up and appeal to motorists with low-cost electric vehicles(until now an oxymoron)sold at prices comparable to those of combustion engine vehicles.Their potential and likely success is so concerning for historic brands and governments alike that on 13 September the European Union launched an investigation to determine whether Chinese brands beneft from public subsidies that distort competition and enable them to offer vehicles at irresistible prices.Fig.35/ContextChinese manufacturers listed on Wikidata by launch dateSource:wikidata.org19992002200520092013201620182000200320072010201420172020Rising AutoGAC AionAiwayseGT New Energy AutomotiveNioCowin AutoChangan AutomobileQorosGonowJonway AutomobileGuangzhou Automobile Industry GroupChina South Industries GroupZX AutoYueda KiaBeijing BenzKarryHunan Leopaard MotorsBytonSiTechAvatr Technology63LObservatoire Cetelem 2024ELECTRICITY:A CRUCIAL DEVELOPMENTThe frst Tesla Model S was launched in 2012.A crazy gamble by Elon Musk,par for the course in his case,which has turned into a stunning success story.A little over a decade later,in the frst half of 2023,the Tesla Model Y electric SUV became the best-selling passenger car in Europe across all categories,ahead of its philosophical and technological antithesis,the Dacia Sandero.This success owes a great deal to a drastic reduction in its price.Electric mobility seems to exert such appeal that it is even generating interest in nations where car manufacturing is non-existent.Thus,as part of its Vision 2030 plan,Saudi Arabia plans to launch electric car production,notably with the creation of the Ceer brand,in conjunction with Foxconn,and a joint venture with the Chinese start-up Human Horizons,whose HiPhi brand will soon be landing in Europe.Public Investment Fund,the Saudi sovereign wealth fund,has also invested in Tesla and Lucid,in which it holds a 61%stake.Lucid is now planning to build a factory in the country(Fig.36).Fig.36/ContextNew OEMs(car manufacturers listed on Wikidata)launched since 2010121080642Source:W2011201220132014201520162017201820192020202120222023GermanyMexicoAustriaTurkeyChinaFranceUnited StatesNetherlandsUnited Kingdom64A STILL FRAGILE IMAGEOf all the factors that can infuence a brands success,image is one of the most crucial.And when we ask motorists,it is clear that this is not one of the strengths they associate with Chinese brands.Meanwhile,European carmakers beneft from an impressive reputation,not least due to their longstanding presence in all markets.Indeed,their image is positive in the minds of 9 out of 10 respondents.On this point,the differences between the countries are naturally less pronounced,even if the Americans,Chinese and Japanese are somewhat more measured in their praise,given that their industries are in competition with these European players.Not to be too outdone by this overwhelming score,Japanese brands come out very well,securing a positive opinion in 82%of cases.Naturally,it is in Japan that motorists are the most enthusiastic about the countrys brands,but they are just as popular in Mexico,Poland and Portugal.In China,geopolitical logic dictates that positive opinions barely reach 70%.American brands come third in the ranking with a score of 73%.American nationalism shines through here,with 9 out of 10 people expressing a positive opinion,a fgure that is just as high in neighbouring Mexico,where motorists are big fans of US-made pick-ups and saloon cars.This enthusiasm is much more subdued in two other neighbouring countries,Germany and Austria,which award a modest score of 60%.One must cross the Pacifc to fnd the country that sits in fourth place,with Korea achieving a score of 63%.Local rivalries are clearly apparent here,with only 34%of Japanese and 50%of Chinese respondents viewing Korean brands positively.Conversely,they are popular among almost 8 out of 10 people in Mexico,Poland and Portugal.65LObservatoire Cetelem 2024Fig.37Do you have a positive or negative opinion of carmakers based in.?Share of respondents whose opinion is positive.To all respondents.In%.Japan Europe Korea China USASource:LObservatoire Cetelem de lAutomobile 2024.16-COUNTRY AVERAGE 73Hc%EUROPE AVERAGE 70De%Germany 60 41 64 90 79Austria 60 41 59 92 78Belgium 65 41 59 87 74Spain 76 50 70 94 85France 68 39 62 90 76Italy 76 44 67 92 89Norway 63 42 58 89 79Netherlands 71 47 67 92 82Poland 87 45 75 92 90Portugal 79 50 73 96 90United Kingdom 65 45 64 87 80China 65 93 50 83 68United States 90 48 67 81 83Japan 73 18 34 83 90Mexico 89 68 77 93 90Turkey 78 56 70 89 8266Bottom of the pile is the worlds top carmaking nation,China,whose achievements in the electric sector are impressive,not to say preoccupying.With just under 1 in 2 people expressing a favourable opinion of them,one might think that the countrys brands still have a lot of work to do in terms of image and recognition.One could also argue that this score is quite honourable for what are relatively new brands that are yet to build up a strong presence in many markets,and which have not benefted from word-of-mouth communication developed over a period of many years.This result provides a solid basis for growth,particularly in view of the efforts they have made to improve the quality of their vehicles and meet the expectations of Western customers.It is no surprise to see that the Chinese are totally on board and that the Japanese are very much at the other end of the scale,with scores of 93%and 18%respectively.In between these two extremes,most European countries score below the overall average,highlighting a certain mistrust of Chinese brands.It should be noted that young people and higher earners have a more positive view of carmakers than average,regardless of the brands country of origin(Fig.37).A FAVOURABLE QUALITY-PRICE RATIO MIGHT ELIMINATE ANY HESITATIONAside from its geographical origin,on what does a brands reputation hinge?When it comes to European brands,the factors of quality,aesthetics,safety and performance win the day.It goes without saying that Europeans are the keenest on these qualities.The Japanese express less enthusiasm about each of these factors,barring the aesthetic appeal of the vehicles,which they do acknowledge.Brands from Japan are naturally the most likely to appeal to the nations consumers.Indeed,their reliability,safety,performance and value for money are widely recognised(Fig.38).Fig.38In your opinion,do cars from each of the following regions offer good value for money?To all respondents.In%who answered“Yes”.Source:LObservatoire Cetelem de lAutomobile 2024.38Japan36Korea34China30Europe 21USA67LObservatoire Cetelem 2024PURCHASING DESIRES REMAIN TO BE CONVERTEDNow that we have established the respective reputations and qualities of the worlds brands,the main question is whether motorists are prepared to buy a vehicle.The responses gathered do not upset the established order,with the same brands securing peoples preferences in descending order.Just over 8 out of 10 respondents express a preference for buying European brands,while the Japanese remain frmly opposed to the idea(and generally to anything that isnt“Made in Japan”).Then come the Japanese,American and Korean brands,in that order.The Chinese brands again bring up the rear,with only 4 out of 10 people being prepared to buy one of their vehicles.There are two ways of looking at this result.This score could either be considered low,or it could be viewed as encouraging,considering the lack of penetration these brands sometimes suffer from outside their country of origin.Once they have achieved greater success outside their borders,this score is likely to change rapidly.And the sales volumes generated will be great enough to trigger a knock-on effect that will be harder to counter(Fig.39).On that fnal crucial point remember the enduring importance of price when buying a car the Korean and Chinese brands hold their own against the Japanese.As for Chinese brands,this is by far the most frequently cited criterion and the main attraction they hold for motorists,even if they still have a long way to go before people are convinced of their performance,aesthetics and safety.None of these criteria obtain a score of more than 20%.When it comes to value for money,American brands score the lowest,with the European brands not far ahead,outstripped by all the Asian brands.More than 8 out of 10 respondents express a preference for European brands68Fig.39 Would you be prepared to buy a car from a brand based in.?Share of respondents who answered“Yes”.In%.Japan Europe Korea China USASource:LObservatoire Cetelem de lAutomobile 2024.16-COUNTRY AVERAGE 588Rr%EUROPE AVERAGE 544Sp%Germany 46 31 50 89 64Austria 45 31 47 92 66Belgium 47 31 47 87 61Spain 66 42 59 93 77France 45 28 43 85 56Italy 66 38 60 94 80Norway 56 34 51 86 72Netherlands 49 31 53 87 66Poland 70 31 64 88 78Portugal 59 36 58 90 74United Kingdom 49 34 52 83 68China 63 91 47 76 63United States 88 39 55 68 74Japan 17 7 8 28 83Mexico 90 62 68 89 87Turkey 80 45 65 90 8269LObservatoire Cetelem 2024PURCHASING INTENTIONS VARY IN THEIR TIMEFRAMESHaving an idea of the brands one might buy does not necessarily mean that this will translate into an actual purchase.The pervading uncertainty is refected in motorists purchasing intentions,if the overall results are anything to go by.Only 1 in 4 respondents plan to succumb to temptation in the next 12 months,a decidedly tepid score that nevertheless represents a substantial number of new cars.In roughly equal proportions,around 4 in 10 respondents do not intend to buy a new vehicle at all,or not for at least a year(Fig.40).Source:LObservatoire Cetelem de lAutomobile 2024.Fig.40Do you intend to buy a car?To all respondents.In%.Yes,in the next 12 months Yes,but not in the next 12 months No34254144144238214127294450123840431743154241421737234021364328383449411019473423354233422516-COUNTRY AVERAGE 36A#%EUROPE AVERAGE 39BB4216Germany AustriaBelgium SpainFrance ItalyNorwayNetherlandsPolandPortugalUnited KingdomChinaUnited StatesJapanMexicoTurkeyThe time to buy.or not 70Based on the previous results,one might have expected infationary pressures to have generated a degree of timidity in the countries that were most vocal about the issue.The reality is more complex While the highest proportions of motorists who intend to replace their vehicle can be found in the worlds largest markets,China and the United States(around 4 out of 10 respondents),a comparable number can be found in Turkey and Mexico.The leading European countries,including France,fall within the overall average.Norway and Japan trail behind,with motorists remaining hesitant,not to say reluctant.ENERGY IS COSTLY AND MONEY IS SCARCEThere are several reasons why consumers might be wary of making a purchase today,with the main ones relating to the current economic climate.4 out of 10 people are hesitant because of the cost of energy,while almost a third are worried that their purchasing power will fall,a sign that infation is taking its toll.With regard to both of these items,the French express the most concern,in direct contrast to the Americans.Maintenance costs also weigh heavily on motorists willingness to buy a new vehicle,particularly in Japan and Mexico.Because they are not yet in full effect or particularly widespread,only a quarter of those questioned are concerned about traffc restrictions(Fig.41).Fig.41If you had to buy a car today,what would be your main reasons to hesitate?The fact that the car you might buy.To all respondents.Select up to three answers.In%.Source:LObservatoire Cetelem de lAutomobile 2024.May cost you too much to run,be it petrol powered or electric 39 40May be too expensive to buy because your purchasing power is liable to fall 34 34 May be too expensive for you to maintain 34 35 May cost you too much because taxes could increase 30 30 May be banned from certain zones in the future 24 23 May be impossible to sell on in the future 19 18 16-country average Europe average71LObservatoire Cetelem 2024NOT EVERYONE FEELS THAT OWNING A CAR IS A NECESSITYAlmost half of those who do not want to buy a new car,be it today or in the future,put one main reason forward:they simply do not need one.This is particularly true in the UK and Austria.In Turkey,only 22%state that they can do without a car.However,this is also the country in which the lack of fnancial resources to buy a car is most acute.7 out of 10 Turks who do not intend to buy a vehicle mention this factor,whereas the overall average for this item is less than 40%.Once again,the Mexicans agree with them on this point.Conversely,the Chinese,and even more so the Belgians,Germans and Austrians,are less concerned about potential fnancial struggles.Uncertainty over regulations,engine types and energy costs is cited by 1 in 5 people(Fig.42).NOW IS THE TIME TO WAITThose who are playing a waiting game give similar reasons for not making a purchase in the near future.Once again,the fact that they have no particular need for a car is the main reason put forward by nearly 4 out of 10 people,a view shared by a majority of respondents in Japan(58%).A current lack of fnancial resources to buy a car is cited by almost a third of motorists.True to form,the Turks and Mexicans also highlight these fnancial diffculties,followed closely by the Portuguese,but also the Norwegians,two populations that mention this factor in almost identical proportions.Despite leading the world in the adoption of electric vehicles,along with the Chinese,the Norwegians also seem fearful of the high cost of these cars compared with other types of powertrain(Fig.43).Fig.42Why dont you want to buy a car?To those who do not want to buy a car.Select up to two answers.In%.Source:LObservatoire Cetelem de lAutomobile 2024.You dont need one 48 46 You cant afford to buy one 35 38 There is too much uncertainty around future regulations.There is too much uncertainty around future energy prices.You dont know what type of motor to choose 18 18 You dont know what brand of car to buy 2 2 A different reason 17 16 16-country average Europe average72PRICE OVER PROGRESSProgress is all very well,but we should not ignore a reality that is more prosaic.And no particular insight is needed to highlight once again what is most important in the minds of motorists:price.As underlined at the start of this report,this is peoples number one preoccupation year after year,particularly in Poland and France,where this issue scores over 50%.The fact that electric vehicles cost more than internal combustion vehicles does little to reassure motorists or offer them a clearer picture,much like the price increases applied by carmakers in recent years.The price war predicted will likely plunge them further into uncertainty and exacerbate their hesitation.Aware of the uncertainty surrounding future energy supplies,they are also looking for guarantees that the energy source their vehicle uses will remain available.This is a view expressed most strongly in Mexico and Germany,but with relatively little vigour in Japan.Motorists are also keen to receive guarantees in terms of vehicle safety and road access.While manufacturers are not entirely responsible for the latter of the two,this indicates that motorists would like the model ranges on offer to invariably comply with the regulations.This is a topic that is particularly close to the hearts of Germans and Austrians(Fig.44).Fig.43For what reasons are you waiting to buy a car?To those who want to buy a car,but not in the next 12 months.Select up to two answers.In%.Source:LObservatoire Cetelem de lAutomobile 2024.You dont need to buy a car soon 39 37You dont currently have the fnancial resources 31 33You are waiting for prices to fall 19 20You dont know what car to buy yet 17 17 You are waiting until you no longer have a choice 13 12 You are waiting for new technologies to come onto the market 12 13 You are waiting to see what new regulations will be introduced 11 13 A different reason 5 5 16-country average Europe average73LObservatoire Cetelem 2024THE CAR MARKET IS STILL ON TENTERHOOKSSince its inception,the car industry has enjoyed a sense of long-term confdence and certainty,which has translated into reasonably predictable sales volumes.The last few years have seen the waters muddied somewhat,with trends becoming more erratic across all regions.After sales peaked in 2017,the Covid-19 crisis revealed an economic and market situation that was less buoyant than it had previously appeared.Europe is still not quite sure where it stands,despite the possibility of a slight upturn in 2023.Over the last two years,China has experienced an identical pattern,illustrated by a marked downturn in sales.In response to this faltering market,most brands have opted to focus on proft margins and premium segments,to the detriment of sales volumes,achieving record profts in the process.But this will have been merely an interlude,since the price war has now resumed.Fig.44Do you think that the car industry should be doing more to.To all respondents.Select up to two answers.In%.Source:LObservatoire Cetelem de lAutomobile 2024.Offer cheaper vehicles 46 42Guarantee that the energy sources required for the vehicles sold will be available in the future 31 31 Guarantee the safety levels of the cars sold 25 28 Guarantee that the cars sold will be able to access all zones in the future 27 24 Offer technological innovations 20 22 Offer vehicles with better performance 12 16 16-country average Europe averageTHE ESSENTIAL744 OUT OF 10 PEOPLE believe that electric cars will not replace combustion engine cars1 IN 4 PEOPLESAY THAT THEIR NEXT CAR WILL BE FULLY ELECTRIC1/2 OF THE PEOPLE SURVEYEDbelieve that the electricity generated will not be enough to power all electric vehicles8 OUT OF 10 PEOPLE believe that subsidies are essential if people are to buy electric vehicles9 OUT OF 10 PEOPLE have a good image of European brands,compared with just under 1 in 2 in the case of Chinese brands4 OUT OF 10 PEOPLE are prepared to buy a car from a Chinese brand23%PLAN TO BUY A CAR IN THE NEXT 12 MONTHS50%OF RESPONDENTS WHO DO NOT WANT TO GO ELECTRIC BELIEVE THAT THE PRICE OF THESE VEHICLES IS TOO HIGH THE ESSENTIAL75LObservatoire Cetelem 202475EPILOGUEMajor technological breakthroughs often occur in times of turmoil and when hitherto unknown horizons are discovered.They prompt questions,hesitation and doubt.They force us to trust our imaginations rather than our reasoning.This was the case for printing technologies.The same can be said for the emergence of electricity in the automotive world,although we should not forget that this form of energy was already in use in the early days of the automobile,only to be subsequently neglected for decades.This latest edition of LObservatoire Cetelem reveals that,in many respects,motorists have adopted a wait-and-see approach,which in some cases veers into suspicion and scepticism.The fog we refer to in this editions title is far from exaggerated,and it is also clear that it is not infuencing all concerned parties in the same way,whether they be motorists or manufacturers.The uncertainty expressed by motorists,6 out of 10 of whom believe it is diffcult to be in a position to buy a vehicle,has a varying impact on manufacturers depending on the country in which they are based.Many of them will need to clarify their industrial and commercial strategies,as well as their communication,if they are to avoid being permanently left behind by competitors who are often one step ahead when it comes to electric vehicles.Similarly,it is up to governments to adopt a clear and stable course,one unencumbered by complacency,so as to facilitate the automotive industrys energy transition.Lastly,and this is even more crucial given the planned dominance of electric cars in the future,the price variable must not be ignored since it remains the automotive industrys key driver,something that Chinese brands have clearly taken on board.We shall see over the coming years whether the fog lifts and once more allows the sun to shine on the automotive world in a durable way.76COUNTRY FACT SHEETSAUSTRIABELGIUMCHINAFRANCEGERMANYITALYJAPANMEXICONETHERLANDSNORWAYPOLANDPORTUGALSPAINTURKEYUNITED KINGDOMUNITED STATES77LObservatoire Cetelem 2024The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.781 ACEA&OICA.2 IEA&Marklines.3 IAE.4 GlobalEconomy.5 OICA,Marklines&C-Ways.AustriaThe passenger car situationCar ownership rate per 1,000 inhabitants1 2022Price of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)Level of knowledgeImplementation of LEZsThe new regulations are poorly understoodLow-income households are penalisedA decision deemed“diffcult”Government subsidies are essentialThe Asian offensiveShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who believe that buying a car is diffcult Share of respondents who view them as“essential”Buying a car.can wait A transition to electric under certain conditionsTop 3 reasons to wait before buying a carTo those who want to buy a car but not in the next 12 monthsThe Austrians fnd themselves in a real fog when it comes to regulations.A majority do not know exactly what these entail.When it comes to assessing the different carmakers,they are very positive about the value for money that they perceive is offered by Asian brands,whether Chinese,Japanese or Korean.SUMMARYShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themAUSTRIA VS.WORLDAUSTRIA VS.16-COUNTRY AVERAGEEPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 2022You dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall Share of respondents who associate the brands with good value for money$1.83 ( 22%vs.2018)$1.64 ( 10%vs.2018)AustriaWorld2022 0.22 2023 0.25( 14%)2024 0.27( 10%)JapanKoreaChinaEuropeUSA46EA$-country average38640!73342 03702852006200820102012201420162018202020222024 1.7 0.3575vehicles(vs.550 in 2015)147vehicles(vs.128 in 2015)AustriaWorld22%( 19 pts vs.2019)14%( 11 pts vs.2019)GermanyWorld27!HPIayYX%4%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.79LObservatoire Cetelem 2024BelgiumPrice of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)Buying a car is not a decision that Belgians take lightly.In fact,this is the country where this attitude is the most prevalent.But the diffculty in making such a decision is not contingent on a possible fall in prices,something that they are the least likely to anticipate.Regarding every kind of regulation,the Belgians appear very clear sighted,with a large proportion claiming to see exactly what these measures entail.SUMMARYBELGIUM VS.WORLDBELGIUM VS.16-COUNTRY AVERAGEThe passenger car situationCar ownership rate per 1,000 inhabitants1 2022Level of knowledgeImplementation of LEZsThe new regulations are poorly understoodLow-income households are penalisedA decision deemed “diffcult”Government subsidies are essentialThe Asian offensiveShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who believe that buying a car is diffcult Share of respondents who view them as“essential”Buying a car.can wait A transition to electric under certain conditionsTop 3 reasons to wait before buying a carTo those who want to buy a car but not in the next 12 monthsShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themEPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 2022You dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall Share of respondents who associate the brands with good value for money28 22 0.37 2023 0.5( 35%)2024 0.52( 4%)506vehicles(vs.497 in 2015)147vehicles(vs.128 in 2015)BelgiumWorld17%KoreaJapanChinaEuropeUSA344)-country average36840!505804652006200820102012201420162018202020222024 2.1 0.3$2.02 ( 17%vs.2018)$1.64 ( 10%vs.2018)BelgiumWorld26%( 23 pts vs.2019)14%( 11 pts vs.2019)BelgiumWorld373342 qyiXQPUIP4%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.801 ACEA&OICA.2 IEA&Marklines.3 IAE.4 GlobalEconomy.5 OICA,Marklines&C-Ways.ChinaThe passenger car situationPrice of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)The Chinese claim to be well informed about cars,to know exactly what the relevant regulations entail,and to know whether or not they are in place in their country.Whilst they believe that subsidies to help people switch to electric vehicles are essential,they do not feel that the way in which they are allocated is unfair.Setting aside the Chinese carmakers,no other region of origin stands out in their eyes in terms of the value for money offered by its brands.They also differ from the rest in thinking that the decision to buy a vehicle is not a diffcult one.SUMMARYCHINA VS.WORLDCHINA VS.16-COUNTRY AVERAGECar ownership rate per 1,000 inhabitants1 2022EPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 202224#%A transition to electric under certain conditionsThe new regulations are poorly understoodLevel of knowledgeImplementation of LEZsShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themLow-income households are penalisedGovernment subsidies are essentialShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who view them as“essential”The Asian offensiveShare of respondents who associate the brands with good value for moneyA decision deemed“diffcult”Share of respondents who believe that buying a car is diffcult Buying a car.can wait Top 3 reasons to wait before buying a carTo those who want to buy a car but not in the next 12 monthsYou dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall 2022 23.56 2023 25( 6%)2024 25( 0%)208vehicles(vs.139 in 2015)147vehicles(vs.128 in 2015)ChinaWorldChinaJapanEuropeKoreaUSA632)%!-country average34806!7 3273%5,00025,00015,0002006200820102012201420162018202020222024 1.2 0.3$0.99 ( 15%vs.2018)$1.64 ( 10%vs.2018)ChinaWorld29%( 24 pts vs.2019)14%( 11 pts vs.2019)ChinaWorld 53Ity&XXP64%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.81LObservatoire Cetelem 2024FrancePrice of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)The French fnd it diffcult to decide to buy a car.They claim to have good knowledge of the regulations on internal combustion engines and traffc restrictions.But they are particularly critical of such measures and believe them to be unfair,especially on low-income households.They also highlight the necessity of subsidies to enable them to go electric.As far as brands are concerned,they are among the least likely to laud American and Japanese carmakers for their value for money.SUMMARYFRANCE VS.WORLDFRANCE VS.16-COUNTRY AVERAGEThe passenger car situationCar ownership rate per 1,000 inhabitants1 2022Level of knowledgeImplementation of LEZsThe new regulations are poorly understoodLow-income households are penalisedA decision deemed “diffcult”Government subsidies are essentialThe Asian offensiveShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who believe that buying a car is diffcult Share of respondents who view them as“essential”Buying a car.can wait A transition to electric under certain conditionsTop 3 reasons to wait before buying a carTo those who want to buy a car but not in the next 12 monthsShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themEPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 2022You dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall Share of respondents who associate the brands with good value for money2022 1.53 2023 1.8( 18%)2024 1.8( 0%)573vehicles(vs.557 in 2015)147vehicles(vs.128 in 2015)FranceWorld$1.99 ( 10%vs.2018)$1.64 ( 10%vs.2018)FranceWorld21%( 18 pts vs.2019)14%( 11 pts vs.2019)FranceWorld1,5002,3001,9002006200820102012201420162018202020222024 1.3 0.330 %KoreaChinaJapanEuropeUSA3420(-country average36480!73338 IPSIydXH4%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.821 ACEA&OICA.2 IEA&Marklines.3 IAE.4 GlobalEconomy.5 OICA,Marklines&C-Ways.GermanyPrice of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)The majority of Germans feel suffciently well informed about the latest vehicle regulations,which they believe unfairly penalise lower-income households.Although the second most common reason for delaying a purchase is a lack of fnancial resources,the Germans are less likely than other populations to consider government subsidies essential.They believe that Korean,Japanese and Chinese brands offer better value for money.On average,they fnd it easier to make the decision to buy a car than those in other countries.SUMMARYGERMANY VS.WORLDGERMANY VS.16-COUNTRY AVERAGEThe passenger car situationCar ownership rate per 1,000 inhabitants1 2022EPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 2022A transition to electric under certain conditionsThe new regulations are poorly understoodLevel of knowledgeImplementation of LEZsShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themLow-income households are penalisedGovernment subsidies are essentialShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who view them as“essential”The Asian offensiveShare of respondents who associate the brands with good value for moneyA decision deemed“diffcult”Share of respondents who believe that buying a car is diffcult Buying a car.can wait Top 3 reasons to wait before buying a carTo those who want to buy a car but not in the next 12 monthsYou dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall 2022 2.65 2023 3.08( 16%)2024 3.15( 2%)KoreaJapanChinaEuropeUSA46C7$-country average36840!73340 %2,6003,8003,2002006200820102012201420162018202020222024 0.9 0.3584vehicles(vs.551 in 2015)147vehicles(vs.128 in 2015)GermanyWorld$1.93 ( 13%vs.2018)$1.64 ( 10%vs.2018)GermanyWorld31%( 28 pts vs.2019)14%( 11 pts vs.2019)GermanyWorld28VPfIpySXQ4%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.83LObservatoire Cetelem 2024ItalyThe passenger car situationCar ownership rate per 1,000 inhabitants1 2022Price of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)Level of knowledgeImplementation of LEZsThe new regulations are poorly understoodLow-income households are penalisedGovernment subsidies are essentialShare of respondents who believe the measure requiring combustion-powered cars to be replaced is unfair Share of respondents who believe that buying a car is diffcult Share of respondents who view them as “essential”Buying a car.can wait A transition to electric under certain conditionsTo those who want to buy a car but not in the next 12 monthsNot only are the Italians aware of the existence of regulations on engine types and traffc restrictions,they also claim to know exactly what they entail.More generally,they feel suffciently well informed about motoring issues.They award high scores to Chinese and Korean brands,which they feel offer good value for money.Despite Italy having a high level of car ownership,it has one of the lowest levels of electric vehicle ownership in Europe.SUMMARYShare of respondents who feel suffciently informedShare of respondents who know exactly what they areA future ban on combustion-powered vehiclesShare of respondents who are aware of themITALY VS.WORLDITALY VS.16-COUNTRY AVERAGEEPC market share2Electric or plug-in hybrid 2022Number of charging points per 1,000 inhabitants3 2022Share of respondents who associate the brands with good value for moneyThe Asian offensiveA decision deemed “diffcult”Top 3 reasons to wait before buying a carYou dont currently have the fnancial resourcesYou dont need to buy a car soonYou are waiting for prices to fall 2022 1.32 2023 1.58( 20%)2024 1.68( 6%)672vehicles(vs.612 in 2015)147vehicles(vs.128 in 2015)ItalyWorld$2.00 ( 1%vs.2018)$1.64 ( 10%vs.2018)ItalyWorld9%( 8 pts vs.2019)14%( 11 pts vs.2019)ItalyWorldKoreaChinaJapanEuropeUSA48A61 -country average36480!%1,3002,5001,9002006200820102012201420162018202020222024 0.6 0.3373332 ($iPWIwwyXH4%The catch-up process still in effect in 2023,after the supply chain issues of the Covid years,is likely to gradually run out of steam in 2024.Moreover,it looks set to be further impacted by persistently high prices and interest rates.841 ACEA&OICA.2 IEA&Marklines.3 IAE.4 GlobalEconomy.5 OICA,Marklines&C-Ways.JapanPrice of petrol4 2022Market forecasts5(In millions of new cars)Annual variation of the NPC market5(In thousands of vehicles)Although Japan boasts the highest car ownership rate in the survey,it also has the lowest proportion of electric vehicles,with sales of the latter only growing very slowly.The Japanese are not well informed on the topic of regulations.They tend not to know what they entail and are unaware of their existence in their country.In their opinion,not all foreign brands offer good value for money,especially those based in China.If they are holding off on buying a vehicle,thats because they don
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POCKET GUIDE 2024/2025 EMPLOYMENT 7 PRODUCTION 14 REGISTRATIONS 22 TRADE 36 VEHICLES ON ROADS 46 ROAD SAFETY 52 ENVIRONMENT 57 INNOVATION 66 TAXATION 70 ABOUT ACEA 81ACEAs Pocket Guide is the must-have resource for intelligence on the automotive industry and market,updated annually.Putting the focus on the data that matters most,weve slimmed down where relevant,while adding new chapters on electric vehicles(EVs).The picture painted by this new edition is revealing as uncertainties and global competition mount.While there are positive takeaways from this years update,the challenges our industry faces are monumental as we undergo the most significant transformation in over a century.Some of the highlights:our industry continues to lead the way in R&D investment,with a sizeable 73 billion spent in 2023.Not only is that 14 billion more than the preceding year,but its also double the amount invested by the next biggest sectoral investor.EU car production jumped in 2023 nearing 15 million vehicles nearly two million more than the previous year.Commercial vehicle production also rebounded,climbing by a notable 20%.Although volumes for all vehicle categories remain lower than pre-pandemic levels,this marks the fastest growth in the past decade.Global car sales experienced a notable 10%rise last year with Europes market share rising by a percentage point to reach 21%.EU car sales climbed for the first time since 2019 with battery-electric models nearly tripling their market share.Commercial vehicle sales performed even better with electric van and truck registrations almost quadrupling.Electric buses were not far behind,more than doubling their share in the same period.While electric vehicle sales last year moved in the right direction,the share of vehicles on Europes roads with a plug remains markedly low,underscoring the need for more robust measures to stimulate the market and replace older vehicles.And while most EU governments offer some form of incentive or tax scheme for EV buyers,charging infrastructure incentives are only available in a mere five member states.Trade figures were promising despite the unpredictable context last year.The value of EU vehicle exports 3THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/2025outweighed imports,culminating in a healthy 5%trade surplus growth compared to 2022.Bus exports posted an outstanding increase,climbing by 286%.The US and the UK remain the top two destinations in both units and value,underscoring the importance of safeguarding smooth trade in our sector.Trkiye is also becoming an increasingly important trade partner,not only for imports but also as an attractive export market.The EU also continues to lead in global road safety,with fatalities slashed by 9%with drops recorded in 21 member states.Our continual investment in vehicle automation and safety will bring further road safety benefits as newer models take the road.Our environmental footprint also continued its downward trajectory.CO2 production emissions per vehicle hit new lows and have now fallen by a significant 60%since 2005.Production water usage per vehicle also sank,having now fallen by nearly 60%in the same period.The ACEA Pocket Guide underlies why it is so important to ensure critical industries like ours are allowed to thrive by investing and trading freely.A holistic and coordinated industrial strategy that exceeds other regions ambitions and puts in place the right conditions for competitiveness matters.Sigrid de VriesACEA Director GeneralWhether its trade,investment,road safety,employment and beyond,our industry touches so many facets of our everyday lives allowing businesses to grow and keep society on the move.We intend our Pocket Guide to continue acting as a valuable resource in guiding both law makers and industry on the road to a more competitive and sustainable shared future.The ACEA Pocket Guide underlies why it is so important to ensure critical industries like ours are allowed to thrive by investing and trading freely.A holistic and coordinated industrial strategy that exceeds other regions ambitions and puts in place the right conditions for competitiveness matters4 EMPLOYMENTMotor vehicle manufacturing(EU)2.4 million jobs=8.1%of EU manufacturing employment2022Total(EU manufacturing,services,and construction)13.2 million jobs=6.8%of EU employment 2022 PRODUCTIONMotor vehicles(global)93.9 million units2023Motor vehicles(EU)14.8 million units=15.8%of global vehicle production2023Passenger cars(global)75.9 million units2023Passenger cars(EU)12.2 million units=16%of global car production2023 REGISTRATIONSMotor vehicles(global)90.1 million units2023Motor vehicles(EU)12.4 million units=13.8%of global vehicle registrations2023Passenger cars(global)72.8 million units2023Passenger cars(EU)10.5 million units=14.5%of global car registrations2023New cars by fuel(EU)battery electric 14.6%,petrol 35.3%market share2023New vans by fuel(EU)electric 7.4%,diesel 82.6%market share2023New trucks by fuel(EU)electric 1.5%,diesel 95.7%market share2023New buses by fuel(EU)electric 15.9%,diesel 62.3%market share2023 TRADEMotor vehicle exports(extra-EU)195.1 billion2023Motor vehicle imports(extra-EU)88.4 billion2023Trade balance(extra-EU)106.7 billion20235 VEHICLES ON ROADSMotor vehicles(EU)289.6 million units2022Passenger cars(EU)252.2 million units2022Motorisation rate(EU)659 vehicles per 1,000 inhabitants2022Average age of cars(EU)12.3 years2022Average age of vans(EU)12.5 years2022Average age of trucks(EU)13.9 years2022Average age of buses(EU)12.5 years2022 ROAD SAFETYRoad fatalities per million inhabitants(EU)46 people 2022Road fatalities(EU)-28%since 20112022 ENVIRONMENTAverage CO2 emissions from new cars(EU)107.8g CO2/km2023CO2 emissions from car production-53.4%since 20052023 INNOVATIONAutomobiles and parts sector(EU)72.8 billion=33%of the EUs total R&D spending2022 TAXATIONFiscal income from motor vehicles (EU major markets)383.7 billion20236THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/20257SOURCE:EUROSTATEU AUTOMOTIVE SECTOR:DIRECT AND INDIRECT EMPLOYMENT In thousands,202213.1m manufacturing jobs10.8m indirect jobs2.4m direct jobs13.2m jobs10.1m non-manufacturing jobsINDIRECT MANUFACTURING674Computers and peripheral equipment57 Electric motors,generators,and transformers617DIRECT MANUFACTURING 2,401 Motor vehicles 1,067 Bodies(coachwork),trailers,and semi-trailers 163 Parts and accessories1,170 2.4m jobs0.7m jobsAUTOMOBILE USE4,077Sale of vehicles 1,415 Maintenance and repair of vehicles 1,413Sale of vehicle parts and accessories642 Retail sale of automotive fuel in specialised stores409 Renting and leasing of vehicles198 TRANSPORT5,204 Other passenger land transport1,759Freight transport by road3,445CONSTRUCTION858 Roads,bridges and tunnels28584.1m jobs5.2m jobs0.9m jobs8EMPLOYMENTThe EU auto sector employs more than 13 million across the value chain1.Provisional2.Including railwaysEMPLOYMENT9SOURCE:EUROSTATThe EU auto sector accounts for around 7%of the blocs employmentEU AUTOMOTIVE SECTOR EMPLOYMENT In million jobs,201820221 Direct manufacturing Indirect manufacturing Automobile use Transport Construction1.Provisional data for 2022.Historical data can be subject to revision in case of updates from Eurostat0246810121420182019202020212022 1.9%-2.0% 1.0% 0.6EMPLOYMENTThe EU automotive sector accounts for over 10%of EU manufacturing jobsAUTOMOTIVE SHARE OF EU MANUFACTURING JOBS%share,20221SOURCE:EUROSTAT1.ProvisionalIndirect automotiveNon-automotive 2.3%0.7m2.4m26.7m3.1m89.7%Direct automotive8.1.3%Automotive11EMPLOYMENTThe EU auto industry accounts for over 10%of manufacturing jobs in six member states1.ProvisionalEU DIRECT AUTOMOTIVE EMPLOYMENT Share of total manufacturing by country,20221SOURCE:EUROSTAT018%8%6%4%2%SlovakiaSwedenRomaniaCzechiaHungaryGermanyEUROPEAN UNIONPolandSloveniaSpainFranceBelgiumPortugalAustriaBulgariaItalyEstoniaNetherlandsLithuaniaFinlandLatviaIrelandDenmarkCroatiaLuxembourgCyprusGreece15.5.6.5.4.4.9%7.2%7.0%6.8%6.8%6.7%5.6%5.1%5.1%4.3%3.2%2.9%2.7%2.6%2.0%1.2%1.2%0.9%0.7%0.5%0.5%8.1EMPLOYMENTEU auto makers directly employ around 2.4 million Europeans in automotive manufacturingDIRECT EU AUTOMOTIVE MANUFACTURING EMPLOYMENT 202211.ProvisionalSOURCE:EUROSTAT8,333FINLAND142,288SPAIN872,446GERMANY172,012CZECHIA75,721SLOVAKIA97,306HUNGARY159,293ROMANIA25,262BULGARIA209,396POLAND3,578ESTONIA2,432LATVIA6,442LITHUANIA41,525PORTUGAL85,274SWEDEN214,904FRANCE165,218ITALY184CYPRUS0MALTA1,683GREECE36,715AUSTRIA15,738SLOVENIA2,368CROATIA34,076BELGIUM21,488NETHERLANDS3,136IRELAND3,713DENMARK256LUXEMBOURG2,400,787EU13EMPLOYMENTEach EU automotive manufacturing worker produces an average of five vehicles annuallyVEHICLE PRODUCTION PER DIRECT AUTOMOTIVE MANUFACTURING EMPLOYEE By country,20221SOURCE:EUROSTAT,S&P GLOBAL MOBILITY1.Based on employment most recent data available018161412108642SpainSlovakiaFinlandBelgiumPortugalNetherlandsCzechiaFranceItalyHungarySloveniaGermanySwedenAustriaRomaniaPolandLithuania15.512.88.88.37.77.67.16.74.74.74.34.23.43.23.22.20.01EUROPEAN UNION5.4THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/202514SOURCE:S&P GLOBAL MOBILITYGLOBAL VEHICLE PRODUCTION In million units,%share,20082023 Greater China Europe North America Japan&South Korea South Asia South America Middle East&Africa15PRODUCTIONChina is the worlds top vehicle producer,manufacturing nearly one-third of vehicles globally200820132018202305101520253035141!%8%6%3%#%5%2)2# %4%3%3%2PRODUCTIONSOURCE:S&P GLOBAL MOBILITYGlobal car production surged by around 11%in 2023,the highest year-on-year percentage increase since 2015GLOBAL CAR PRODUCTION In million units,%change,%share,20142023 Greater China Europe Japan&South Korea North America South Asia South America Middle East&Africa90807060504030201020142015201620172018201920202021202220230 2.1% 2.6% 5.7%-16.7% 10.6%-6.2% 8.5%-1.6% 2.83.8.8.5.5.2%2.8%2.4PRODUCTIONGlobal commercial vehicle production increased by over 7%in 2023GLOBAL COMMERCIAL VEHICLE PRODUCTION 1 In million units,%change,%share,201420231.Includes busesSOURCE:S&P GLOBAL MOBILITY22201816141210864202014201520162017201820192020202120222023 2.9% 1.1%-11.7% 7.1%-2.5% 5.8%-2.5% 2.3%-4.3%.7$.9.7.9%6.9%5.0%2.8%North America Greater China Europe South Asia Japan&South Korea South America Middle East&Africa18PRODUCTIONAbout 15 million vehicles were made in the EU in 2023,nearly 2 million more compared to 2022EU VEHICLE PRODUCTION By country,2023SOURCE:S&P GLOBAL MOBILITY53FINLAND30,1421,80339,720SWEDEN288,010LITHUANIA326,925AUSTRIA104,20014SLOVENIA60,8421,35363,167261,031ITALY545,5821,859,085552,8051,33544,218SPAIN970,183537,6212,69082,882FRANCE220,10092,3402094,321PORTUGAL508,7341,093HUNGARY506,099ROMANIASLOVAKIA1,397,6315,2341,432CZECHIA233,182317,7269,12855,079POLAND4,406178,773253,727GERMANY3,957,010284,07838149,629BELGIUM120,23544277,238NETHERLANDS51,075,3796,951CARSTRUCKS2BUSESVANS1EU12,160,4922,022,201603,43728,1251.Light commercial vehicles up to 3.5 tonnes2.Medium and heavy commercial vehicles over 3.5 tonnes19PRODUCTIONEU car production grew at its fastest rate in the last decadeEU CAR PRODUCTION In million units,%change,20122023SOURCE:S&P GLOBAL MOBILITY4812162012201320142015201620172018201920202021202220230 2% 1.2% 7.6%-6.7%-23.5% 5.1%-3.7% 11.6% 0.4%-1.9% 8.4 PRODUCTIONEU commercial vehicle production surged by 20%in 20231.Light commercial vehicles up to 3.5t2.Medium and heavy commercial vehicles over 3.5tEU COMMERCIAL VEHICLE PRODUCTION In million units,%change,20122023SOURCE:S&P GLOBAL MOBILITY2.52.01.51.00.502012201320142015201620172018201920202021202220233.0 3.8% 8.4% 8.5% 3.4% 10.3%-20.9% 2.6%-1.8% 4%-1.6% 20.3%Vans1 Trucks2 Buses21PRODUCTION255 automotive plants operate in the EUAUTOMOBILE ASSEMBLY,BATTERY,AND ENGINE PLANTS 20241.Battery-electric vehicleSOURCE:S&P GLOBAL MOBILITYFINLAND42SWEDEN713FRANCE348ITALY241CROATIA11SLOVENIA22AUSTRIA573ROMANIA52PORTUGAL1911SPAIN72HUNGARY5SLOVAKIA84CZECHIA5126GERMANY199POLAND4BELGIUM74NETHERLANDS94216UNITED KINGDOMCARSVANSTRUCKSBUSESENGINESBATTERIESTOTALEU UK983032445665255 All plants BEV1 productionTHE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/202522SOURCE:S&P GLOBAL MOBILITYGLOBAL NEW VEHICLE REGISTRATIONS In million units,%share,2008202323REGISTRATIONSEurope accounts for a fifth of global vehicle sales,down from a third in 2008 Greater China North America Europe South Asia Japan&South Korea Middle East&Africa South America200820132018202305101520253014$2%8%9%7%7!%8%6%700!%7%7%5%5%5%5$REGISTRATIONSEurope accounts for more than 21%of global car sales,up from 20%in 2022SOURCE:S&P GLOBAL MOBILITYGLOBAL NEW CAR REGISTRATIONS In million units,%change,%share,20142023 Greater China Europe South Asia Japan&South Korea North America Middle East&Africa South America2014201520162017201820192020202120222023 3% 5.2%-15.2% 10.1%-4.9% 4%-0.21.3!.4 .2.7%7.5%4.9%3.902030405060708090 2.5%-0.9%REGISTRATIONSEurope accounts for more than 17%of global commercial vehicles salesSOURCE:S&P GLOBAL MOBILITYGLOBAL NEW COMMERCIAL VEHICLE 1 REGISTRATIONS In million units,%change,%share,201420231.Includes buses 1051015202014201520162017201820192020202120222023 1.4% 1.4%-7.6% 9.0%-1.0% 4.3%-10.4&.6$.8.3.4%7.6%5.9%4.4%-1.7% 1.8%North America Greater China Europe South Asia South America Japan&South Korea Middle East&Africa26REGISTRATIONSAuto makers sold over 12 million new vehicles in the EU in 2023,1.5 million more than in 2022SOURCE:ACEA,S&P GLOBAL MOBILITYNEW EU VEHICLE REGISTRATIONS 1 By country,in thousand units,202315FINLAND8852SWEDEN29040AUSTRIA2397LUXEMBOURG4910CROATIA5811GREECE1341MALTA7229ITALY 1,5652CYPRUS1578BELGIUM477434FRANCE 1,77510SLOVENIA49385BULGARIA14526ROMANIA20036PORTUGAL949179SPAIN10828HUNGARY8814SLOVAKIA22134CZECHIA2,845360GERMANY475102POLAND37086NETHERLANDS12232IRELAND17331DENMARK235ESTONIA195LATVIA2814LITHUANIAPC2CV&BC3EU10,5481,8471.Data for Malta not available2.Passenger cars3.Commercial vehicles,and buses and coaches27REGISTRATIONSSOURCE:ACEA,DG ECFIN,S&P GLOBAL MOBILITYVehicle sales largely mirror economic trendsNEW VEHICLE REGISTRATIONS AND GDP IN THE EU 20162025 New EU vehicle registrations(million units)EU GDP(annual%change)2016201720182019202020212022202320242025-8%-6%-4%-2%0%2%4%6%81011121314151628REGISTRATIONSSOURCE:ACEAEU car sales climbed for the first time since 2019NEW EU CAR REGISTRATIONS In million units,%change,201220234812162012201320142015201620172018201920202021202220230 7.8% 5.4% 1.6% 1.9%-4.5%-3.9% 10%-2.4% 4.8%-23.7% 13.9)REGISTRATIONSEU commercial vehicle sales rose by 15%in 2023SOURCE:ACEANEW EU COMMERCIAL VEHICLE REGISTRATIONS In million units,%change,20122023 Vans1 Trucks2 Buses3 2.52.01.51.00.52012201320142015201620172018201920202021202220230 11.4% 14.3% 5.1% 4.2% 2.4%-8.6% 6.9%-18.9% 9.6%-14.6% 15%1.Light commercial vehicles up to 3.5 tonnes2.Commercial vehicles over 3.5 tonnes3.Buses and coaches over 3.5 tonnes 30REGISTRATIONSOne car is sold for every 50 persons in the EU annuallyNEW CARS PER 1,000 INHABITANTS By country,in units,2023SOURCE:ACEA,EUROSTATSloveniaCzechiaSpainPortugalEstoniaSlovakiaCyprusFinlandCroatiaMaltaPolandGreeceHungaryLatviaLithuaniaRomaniaBulgaria232321202019171616161513131311101086020406080NetherlandsIrelandLuxembourgBelgiumGermanyDenmarkSwedenItalyAustriaFrance7441342928272626EUROPEAN UNION2431REGISTRATIONSSmall and medium cars make up around 42%of EU salesSOURCE:S&P GLOBAL MOBILITYNEW CARS IN THE EU BY SEGMENT In million units,%share,20122023 Small(A B)Lower medium(C)Upper medium(D)Luxury(E F)MPV1 SUV205101551%4%2%6! 22202320212020201920182017201620152014201320121.Multi-purpose vehicles2.Sport utility vehicles 32REGISTRATIONSThe EU market share of battery-electric cars has surged around three-fold in four yearsSOURCE:ACEA1.Includes extendedrange electric vehicle2.Includes full and mild hybrids3.Includes natural gas,LPG,ethanol and fuel cell electric vehiclesNEW EU CAR SALES BY POWER SOURCE Market share,20202023 Petrol Diesel Battery electric Plug-in hybrid1 Hybrid electric2 Alternative fuels3 Total alternatively powered vehicles20202.1%5.1%5.4.9G.5.9 233.0%7.7.6.65.3%.8 2120222.8%3.0%8.9%9.4%9.1.1.6.49.96.4.8.7$.5.6G.3Q.13REGISTRATIONSSOURCE:ACEAThe EU market share of electrically chargeable vans has almost quadrupled in four yearsNEW EU VAN1 SALES BY POWER SOURCE Market share,202020231.1Light commercial vehicles up to 3.5 tonnes2.Includes battery and plug-in hybrid vehicles3.Includes full and mild hybrids4.Includes natural gas,LPG,ethanol and fuel cell electric vehicles Diesel Petrol Electrically chargeable2 Hybrid electric3 Alternative fuels4 Total alternatively powered vehicles20232.3%1.4%6.3.6%7.4 211.7%1.4%3.8.2%3.0 200.9%1.3%3.4.4%2.0 222.5%1.2%5.2.7%5.4%4.2%6.1%9.1.14REGISTRATIONSThe market share of alternatively powered trucks was relatively stable at around 4%SOURCE:ACEA1.Data for Bulgaria and Malta not available2.Commercial vehicles over 3.5 tonnes3.Includes battery and plug-in hybrid vehicles4.Includes full and mild hybrids5.Includes natural gas,LPG,ethanol and fuel cell electric vehiclesNEW EU1 TRUCK2 SALES BY POWER SOURCE Market share,20202023 Diesel Petrol Electrically chargeable3 Hybrid electric4 Alternative fuels5 Total alternatively powered vehicles20210.5%0.02%0.1.9%3.6 200.4%0.1%0.1.5%3.0 220.8%0.02%0.05.2%3.0 230.1%2.6%0.04.7%1.5%3.4%4.1%3.8%4.25REGISTRATIONSThe market share of electrically chargeable buses has nearly trebled in four yearsSOURCE:ACEA1.Data for Bulgaria and Malta not available2.Buses and coaches over 3.5 tonnes3.Includes battery and plug-in hybrid vehicles4.Includes full and mild hybrids5.Includes natural gas,LPG,ethanol and fuel cell electric vehiclesNEW EU1 BUS2 SALES BY POWER SOURCE Market share,20202023 Diesel Petrol Electrically chargeable3 Hybrid electric4 Alternative fuels5 Total alternatively powered vehicles12.8%9.0b.3.9.3.4%0.003h.8.6%9.5.1%0.02s.2%6.1%7.1.4%0.02%0.0f.9.6 2120202022202326.71.23.17.7%THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/202536The trade surplus generated by the EU auto industry rose by 5%in 20231.Commercial vehicles up to 5t2.Commercial vehicles over 5tSOURCE:EUROSTATEU VEHICLE TRADE By type,in million,2023TRADE37Trade in valueCarsVans1Trucks2BusesTOTAL2023Imports78,4156,6617812,54488,401Exports176,6399,7577,6521,086195,134Trade balance98,2243,0966,871-1,458106,7332022Imports61,8365,5516451,76369,795Exports157,5326,9366,199796171,464Trade balance95,6971,3855,554-966101,669%change 23/22Imports 26.8% 20.0% 21.0% 44.3% 26.7%Exports 12.1% 40.7% 23.4% 36.4% 13.8%Trade balance 2.6% 123.6% 23.7% 50.9% 5.08TRADEEU vehicle imports and exports grew by 16%and 10%respectively1.Commercial vehicles up to 5t2.Commercial vehicles over 5tEU VEHICLE TRADE By type,in units,2023SOURCE:EUROSTATTrade in volumeCarsVans1Trucks2BusesTOTAL2023Imports3,847,522360,88613,94117,2374,239,586Exports5,836,492578,482166,03053,3686,634,3722022Imports3,198,464342,009108,74213,0843,662,299Exports5,363,491434,928202,38613,8256,014,630%change 23/22Imports 20.3% 5.5%-87.2% 31.7% 15.8%Exports 8.8% 33.0%-18.0% 286.0% 10.39TRADEThe value of EU vehicle imports has increased from all top five countries of origin compared to 2022MAIN COUNTRIES OF ORIGIN OF EU VEHICLE IMPORTS In million,20192023SOURCE:EUROSTAT2019202020212022202302,0004,0006,0008,00010,00012,00014,00016,000 United Kingdom China Trkiye Japan South Korea40TRADEChina,Trkiye,and the UK are the top three countries of origin for EU vehicle imports(in units)MAIN COUNTRIES OF ORIGIN OF EU VEHICLE IMPORTS In million units,2023SOURCE:EUROSTATChinaTrkiyeUnitedKingdomJapanMoroccoMexicoSwitzerland00.10.20.30.40.50.60.70.8SouthKoreaUnited StatesSouth Africa 40.2% 9.4% 0.6% 36.7% 5.7% 14.7% 5.3% 29.5% 2.0% 4.6 22 202341TRADEThe US and the UK are the two most valuable markets for EU vehicle exportsMAIN DESTINATIONSFOR EU VEHICLE EXPORTS In million,20192023SOURCE:EUROSTAT2019202020212022202305,00010,00015,00020,00025,00030,00035,00040,00045,000 United States United Kingdom China Trkiye Switzerland42TRADEThe UK,the US,and Trkiye are the top three destinations for EU vehicle exports(in units)SOURCE:EUROSTATMAIN DESTINATIONS FOR EU VEHICLE EXPORTS In million units,2023ChinaAustraliaNorway00.20.40.60.81.01.21.41.6South Korea 14.7% 15.0% 92.3% 0.7% 15.5% 11.1% 3.4%-17.6%-19.0%-8.2%UnitedKingdomUnited StatesTrkiyeUkraineSwitzerlandJapan 2022 202343TRADEChina is the top country of origin by value for EU battery-electric car importsMAIN COUNTRIES OF ORIGIN OF EU BATTERY-ELECTRIC CAR IMPORTS In million,20192023SOURCE:EUROSTAT2019202020212022202302,0004,0006,0008,00010,000 China South Korea United Kingdom United States Japan44TRADEThe UK and the US are the most valuable markets for EU battery-electric car exportsMAIN DESTINATIONS OF EU BATTERY-ELECTRIC CAR EXPORTS In million,20192023SOURCE:EUROSTAT United Kingdom United States Norway Trkiye Switzerland2019202020212022202301,0002,0003,0004,0005,0006,0007,0008,00045TRADEMore than one-third of EU vehicle exports go to other European(non-EU)countriesSOURCE:EUROSTATMAIN DESTINATIONS FOR EU VEHICLE EXPORTSValue market share,2023SOURCE:EUROSTATCentral andSouth AmericaAsia&Oceania1.8).2TA UK Eastern Europe(non-EU)North America35.7$.1rica4.0%Middle East5.2%THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/202546VEHICLES ON ROADS47VEHICLES ON ROADSThere are 659 vehicles per 1,000 inhabitants in the EUVEHICLES PER 1,000 EU INHABITANTS 1 2022SOURCE:ACEA1.Data for Bulgaria and Malta not availableCyprusLuxembourgItalyEstoniaCzechiaFrancePortugalGreeceAustriaSpainGermanyNetherlandsBelgiumEUROPEAN UNIONFinlandSlovakiaDenmarkIrelandSwedenCroatiaLithuaniaHungaryRomaniaLatvia819801787774750690664677646641639638637596594575571547545544534533487482464659PolandSlovenia20030040050060070080090048VEHICLES ON ROADSThere are almost 290 million vehicles on EU roadsEU VEHICLE FLEET:SIZE AND SEGMENT DISTRIBUTION In million units,20132022SOURCE:ACEA Passenger cars Commercial vehicles and buses1.Includes light,medium,and heavy commercial vehicles,and buses and coaches150200250300252.237.42014201520162017201820192020202120222013 0.7% 1.8% 2.2% 2.4% 2% 1.9% 1.2% 1.4% 1.1049VEHICLES ON ROADSTrucks have the highest average age of all vehicle typesAVERAGE AGE OF EU VEHICLE FLEET By country,in years,2022SOURCE:ACEA1.Light commercial vehicles up to 3.5t2.Medium and heavy commercial vehicles over 3.5t3.Buses and coaches over 3.5tCARSTRUCKS2BUSES3VANS1EU AVERAGE12.312.513.912.512.614.712.613.4FINLAND6.810.79.2SWEDEN7.97.98.97.5DENMARK4.46.78.96.5AUSTRIA9.89.811.210.1SLOVENIA14.519.112.514.7ITALY18.823.017.321.4GREECE10.010.011.710.1NETHERLANDS11.412.29.89.0BELGIUM6.37.67.96.9LUXEMBOURG7.79.310.810.6FRANCE9.18.711.310.7IRELAND13.914.011.814.7SPAIN13.615.514.115.4PORTUGAL16.613.414.820.9ESTONIA15.214.313.314.3LATVIA14.713.513.59.8LITHUANIA14.914.416.113.2POLAND10.09.38.010.4GERMANY15.914.214.718.2CZECHIA14.713.311.315.9SLOVAKIA14.612.811.512.2HUNGARY14.915.917.115.7ROMANIA13.311.411.614.4CROATIA50VEHICLES ON ROADSThe average age of cars and vans is rising,while that of trucks and buses is decliningSOURCE:ACEAEVOLUTION OF AVERAGE AGE OF EU FLEET By vehicle type,in years,20202022Cars12.312.011.8Vans12.512.011.9Trucks13.914.214.1Buses12.512.712.810.011.012.013.014.015.051VEHICLES ON ROADSJust over 2%of cars on EU roads are electrically chargeableSHARE OF ALTERNATIVELY POWERED VEHICLES IN THE EU FLEET By segment,%share,2022SOURCE:ACEA1.Includes battery and plug-in hybrid electric vehicles2.Includes full and mild hybrids Cars Vans Trucks Buses0.00.51.01.52.02.53.03.54.04.55.0Electrically chargeable1Hybrid electric2Natural gas and LPG2.2%3.1%3.1%0.8%0.3%1.4%0.1%0.05%0.8%1.9%2.0%4.1%THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/20255253ROAD SAFETYThe EU has by far the best road safety record in the worldSOURCE:CARE(COMMUNITY ROAD ACCIDENT)DATABASE,WHO GLOBAL HEALTH OBSERVATORYROAD FATALITIES PER MILLION INHABITANTS By region1,2021,20221.WHO regions 2.Calculated by ACEA using data by country 147 road fatalities per million inhabitantsWORLDWestern PacificSouth-EastAsia152161Others(Europe)2AmericaEuropeanUnion8414146AfricaEasternMediterranean19416454ROAD SAFETYRoad fatalities have fallen significantly since 2011 despite an increase in the number of cars on EU roadsSOURCE:ACEA,CARE(COMMUNITY ROAD ACCIDENT)DATABASENUMBER OF EU VEHICLES AND ROAD FATALITIES 20112022 EU road fatalities(in thousands)Vehicles on EU roads(in millions)220230240250260270280290300141618202224262830201120122013201420152016201720182019202020212022-28% 17.9(.7245.726.5248.324.2250.024.1251.724.4256.3261.923.823.4268.323.3273.822.8279.0282.518.819.9286.420.7289.655ROAD SAFETYAverage EU road fatalities have plummeted by around a quarter since 2012SOURCE:CARE(COMMUNITY ROAD ACCIDENT)DATABASEROAD FATALITIES PER MILLION INHABITANTS By country,2012,2022 2012 2022 EU average 2012 EU average 2022120100806040200RomaniaBulgariaCroatiaGreecePortugalLatviaLuxembourgHungaryItalyMaltaCzechiaPolandSlovakiaFranceBelgiumFinlandEstoniaGermanyIrelandDenmarkSwedenLithuaniaCyprusAustriaSloveniaNetherlandsSpain466056ROAD SAFETYEU road fatalities declined by 9%in 2022SOURCE:CARE(COMMUNITY ROAD ACCIDENT)DATABASEROAD FATALITIES IN THE EU By country,2022 Road fatalities%change 22/191 %change 22/19120,653EU-9.2%1.The reference year for comparison is 2019 since the traffic levels of 2020 and 2021 were significantly impacted by the COVID-19 pandemicFINLAND196-7.1%SWEDEN227 2.7%NETHERLANDS655 11.8%LUXEMBOURG36 63.6%FRANCE3,260 0.7%MALTA26 62.5%ITALY3,159-0.4%CROATIA275-7.4%CYPRUS37-28.8NMARK154-22.6LGIUM540-16.4%SLOVENIA85-16.7%AUSTRIA370-11.1%POLAND1,896-34.8%ESTONIA49-5.8%GERMANY2,788-8.5%LATVIA113-14.4%HUNGARY537-10.8%ROMANIA1,633-12.4%CZECHIA527-14.7%SPAIN1,746-0.5%PORTUGAL618-10.2%GREECE654-4.9%LITHUANIA120-35.5%IRELAND155 10.7%BULGARIA531-15.4%SLOVAKIA266-1.5%THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/20255758ENVIRONMENTEU27 ICELAND NORWAYEU27-1.5%-2.0 231 average emissions(g CO2/km)%change 23/22%change 23/22 The average new car in the EU emits 2%less CO2/km than in 2022CO2 EMISSIONS FROM NEW CARS BY COUNTRY In g CO2/km,202311.Provisional;from 2021 onwards the WLTP will replace fully the NEDC for the purpose of the CO2 emission standardsSOURCE:EEA106.6107.8FINLAND60.9-28.6%SWEDEN61.0-8.4%NETHERLANDS74.2-14.5%LUXEMBOURG106.8-7.8%FRANCE96.8-6.1%ITALY120.1 0.7%CROATIA127.2-1.2%CYPRUS100.4-26.7NMARK73.3-15.1%NORWAY14.5-19.0LGIUM85.3-18.5%SLOVENIA123.9-4.3%AUSTRIA104.1-7.1%POLAND134.8-1.5%ESTONIA134.5-4.9%GERMANY113.0 6.6%LATVIA132.1-1.8%HUNGARY127.6-3.0%ROMANIA115.8-3.3%CZECHIA136.3-1.3%SPAIN117.5-3.4%PORTUGAL89.8-12.9%GREECE112.7-4.5%LITHUANIA129.9-4.4%IRELAND97.6-3.1%BULGARIA130.8-2.9%SLOVAKIA137.6-0.6%ICELAND61.9-18.7%MALTA-1.9.559ENVIRONMENT 130g CO2/km 96130g CO2/km 95g CO2/kmAlmost a quarter of new cars emit 95g CO2/km or lessNEW CARS BY EMISSION CLASSES IN THE EU In million units,%share,2016202311.Provisional;from 2021 onwards the WLTP will replace fully the NEDC for the purpose of the CO2 emission standardsSOURCE:EEA108642201620172018201920202021202220231022#&0%9 !#9898ffdaYBENVIRONMENTCO2 emissions from new cars are down by 15%since 2013CO2 EMISSIONS FROM NEW CARS IN THE EU In g CO2/km,%change,2013202311.Provisional;NECD(2013-2020),WLTP(2021-2023)SOURCE:EEA80859095100105110115120125130201320142015201620172018201920202021 1.6%-2.6%-3.2%-1.3% 1.8% 0.3 2220231-11.3% 7.5%-5.4%-2.0aENVIRONMENTCar makers have slashed production energy use per unit by 15%since 2005 Energy total(million MWh/year)Energy per unit produced(MWh/car)Car production trend CAR PRODUCTION:ENERGY CONSUMPTION 20052023SOURCE:ACEA20222426283032342.02.22.42.62.83.03.23.4million MWhMWh/car-31.2%-15.0 05200720092011201320152017201920212022202362ENVIRONMENTCar makers have cut production CO2 emissions per unit by over half since 2005 Total CO2 emissions(million t/year)CO2 emissions per unit produced(t/car)Car production trendCAR PRODUCTION:CO2 EMISSIONS 20052023SOURCE:ACEA2.03.04.05.06.07.08.09.010.011.012.00.20.30.40.50.60.70.80.91.01.11.2-53.4%million tonnestonnes/car-62.3 05200720092011201320152017201920212022202363ENVIRONMENTCar makers have reduced production water use per unit by almost half since 2005 Total water(million m/year)Water per unit produced(m/car)Car production trend CAR PRODUCTION:WATER CONSUMPTION 20052023SOURCE:ACEA202530354045505560652.02.53.03.54.04.55.05.56.06.5m3/carmillion m3-47.1%-57.2 05200720092011201320152017201920212022202364ENVIRONMENTLevels of car manufacturing waste largely follow production trends Total waste(million t/year)Waste per unit produced(kg/car)Car production trendCAR PRODUCTION:WASTE 1 200520221.Excluding scrap metal and demolition wasteSOURCE:ACEA0.00.10.20.30.40.50.60.70.80.91.060657075808590959095100million tonneskg/car 3.8% 28.2 05200720092011201320152017201920212022202365ENVIRONMENTCar makers have reduced production VOC emissions per unit by over half since 2005SOURCE:ACEA VOC emissions total(thousand t/year)VOC emissions per unit produced(kg/car)Car production trend CAR PRODUCTION:VOC 1 EMISSIONS 200520231.Volatile organic compounds10152025303540451.01.52.02.53.03.54.04.5-60.6%-51.3%thousand tonneskg/car20052007200920112013201520172019202120222023THE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/20256667INNOVATIONEU auto makers account for a third of all EU R&D investmentSECTORAL R&D SHARE IN THE EU%share,2022SOURCE:THE 2023 EU INDUSTRIAL R&D INVESTMENT SCOREBOARDHealthcare equipment&servicesChemicalsBanksAerospace&defenceIndustrial engineeringElectronic&electrical equipmentSoftware&computer servicesAutomobiles&partsOthersTechnology hardware&equipment3%3%3%4%3%6%6%93%Pharmaceuticals&biotechnology68INNOVATIONEU auto makers invest around 73 billion annually in R&D,about twice the amount as the pharmaceutical and biotech sectorEU R&D INVESTMENT IN THE TOP 10 INDUSTRIAL SECTORS In billion,2022SOURCE:THE 2023 EU INDUSTRIAL R&D INVESTMENT SCOREBOARDAutomobiles and partsPharmaceuticals and biotechnologySoftware and computer servicesElectronic and electrical equipmentIndustrial engineeringBanksHealthcare equipment and servicesTechnology hardware and equipmentAerospace and defenceChemicals02040608072.837.020.113.811.78.77.17.16.55.569INNOVATIONAuto makers invest over 70 billion in R&D in the EUAUTOMOTIVE R&D INVESTMENT BY REGION In billion,%change 2021 20221020304050607080EUJapanUSChinaRest of the world 55.1% 23.2% 49.8% 4.6 6%SOURCE:THE 2023 EU INDUSTRIAL R&D INVESTMENT SCOREBOARDTHE AUTOMOBILE INDUSTRYPOCKET GUIDE 2024/20257071TAXATIONSOURCE:ACEATAX BENEFITS AND PURCHASE INCENTIVES:ELECTRIC CARS 2023TAX BENEFITSAustriaBelgiumBulgariaCroatiaCyprusCzechiaDenmarkEstoniaFinlandFranceGermanyGreeceHungaryAcquisitionOwnershipCompany carINCENTIVESPurchaseInfrastructure72TAXATIONSOURCE:ACEATAX BENEFITS AND PURCHASE INCENTIVES:ELECTRIC CARS 2023TAX BENEFITSAcquisitionOwnershipCompany carINCENTIVESPurchaseInfrastructureIrelandItalyLatviaLithuaniaLuxembourgMaltaNetherlandsPolandPortugalRomaniaSlovakiaSloveniaSpainSwedenOnly a handful of EU countries offer incentives for electric car charging infrastructure73TAXATIONTAX BENEFITS AND PURCHASE INCENTIVES:ELECTRIC COMMERCIAL VEHICLES 2023SOURCE:ACEATAX BENEFITSAcquisitionOwnershipAustriaBelgiumBulgariaCroatiaCyprusCzechiaDenmarkEstoniaFinlandFranceGermanyGreeceHungaryINCENTIVESAcquisitionInfrastructure74TAXATIONTAX BENEFITS AND PURCHASE INCENTIVES:ELECTRIC COMMERCIAL VEHICLES 2023SOURCE:ACEATAX BENEFITSAcquisitionOwnershipINCENTIVESAcquisitionInfrastructureIrelandItalyLatviaLithuaniaLuxembourgMaltaNetherlandsPolandPortugalRomaniaSlovakiaSloveniaSpainSwedenOnly four EU countries provide incentives for electric commercial vehicle infrastructure75TAXATION1.Latest available data;only country for which sourced data is available are listed2.Euro foreign exchange reference rates at 26 March 2024;source:ECB3.EstimatesFISCAL INCOME FROM VEHICLES IN MAJOR EU MARKETS 1 SOURCE:ACEAAustriaBelgiumDenmarkFinlandFranceGermanyGreece bn2022 bn2020DKK bn20243 bn2021 bn2022 bn2022 bn2022Purchase or transfer1.VAT on vehicle sales servicing,repair&parts3.27.61.620.230.10.82.Sales®istration taxes0.40.510.10.51.90.43.Annual ownership taxes2.81.710.91.10.79.51.24.Fuels&lubricants5.67.319.34.041.734.94.85.Others:Driving license fees0.00.010.20.03 Insurance taxes0.41.01.40.45.75.50.5 Tolls2.40.70.613.97.4 Customs duties0.5 Other taxes0.30.81.80.2TOTAL(national currencies)15.219.642.37.685.988.27.9TOTAL()215.219.65.77.685.988.27.976TAXATION1.Latest available data;only country for which sourced data is available are listed2.Euro foreign exchange reference rates at 26 March 2024;source:ECB3.EstimatesFISCAL INCOME FROM VEHICLES IN MAJOR EU MARKETS 1 SOURCE:ACEAVehicles contribute over 380 billion to public budgets in major EU marketsIrelandItalyNetherlandsPortugalSpainSweden bn2019 bn2022 bn2022 bn2021 bn2023SEK bn2021Purchase or transfer1.VAT on vehicle sales servicing,repair&parts0.719.21.42.811.125.52.Sales®istration taxes1.01.61.60.40.63.Annual ownership taxes0.97.24.40.73.015.54.Fuels&lubricants3.532.89.62.822.857.05.Others:Driving license fees0.00.40.10.0 Insurance taxes0.13.71.21.12.8 Tolls2.20.22.8 Customs duties Other taxes4.30.61.50.81.3TOTAL(national currencies)6.271.019.28.539.5104.9TOTAL()26.271.019.28.539.59.277TAXATIONCar VAT rates in the EU range from 17%to 27%VAT SHARE IN NET CAR PRICES%share,202427%HungaryFinlandGreeceItalySloveniaAustriaBulgariaEstoniaFranceSlovakiaMaltaCroatiaDenmarkSwedenIrelandPolandPortugalBelgiumCzechiaLatviaLithuaniaNetherlandsSpainCyprusGermanyRomaniaLuxembourg25$#! %SOURCE:ACEA78TAXATIONAnnual tax income averages at 1,900 per vehicle in major EU marketsSOURCE:ACEAAVERAGE ANNUAL TAX PER VEHICLE IN MAJOR EU MARKETS 1 In per vehicle,20231.Per country estimates based on total number of vehicles on roads1,306SPAIN1,290PORTUGAL1,673GERMANY2,661AUSTRIA1,871FRANCE2,896BELGIUM2,438IRELAND1,632SWEDEN2,379FINLAND1,775DENMARK1,852NETHERLANDS1,571ITALY1,196GREECE1,0001,5002,0002,5003,00079TAXATIONThe Netherlands,Italy,and Greece rank top for the highest petrol excise dutiesSOURCE:ACEAEXCISE DUTIES ON UNLEADED PETROL In/1,000 litres,2023 Petrol Minimum EU rate petrol0100200300400500600700800NetherlandsItalyGreeceFinlandFranceDenmarkGermanyIrelandBelgiumPortugalEstoniaLuxembourgSloveniaCzechiaSlovakiaLatviaSpainSwedenAustriaLithuaniaCroatiaRomaniaHungaryPolandBulgariaCyprusMalta35980TAXATIONItaly,Belgium,and France rank top for the highest diesel excise dutiesSOURCE:ACEAEXCISE DUTIES ON DIESEL In/1,000 litres,2023 Diesel Minimum EU rate diesel7006005004003002001000ItalyBelgiumFranceIrelandNetherlandsFinlandDenmarkGermanySloveniaPortugalLuxembourgLatviaGreeceLithuaniaCzechiaAustriaCroatiaSpainEstoniaRomaniaSlovakiaHungarySwedenPolandBulgariaCyprus330MaltaACEA MEMBERSDRIVING MOBILITY FOR EUROPEThe European Automobile Manufacturers Association,or ACEA,unites Europes 15 major car,truck,van and bus makers.We are the voice of the auto industry:a technological world leader and the backbone of the EU economy.Our members keep Europe on the move,providing diverse solutions for moving people and goods from A to B.Together,we are progressing on the road to zero-emission and zero-fatality transport.We are addressing major technology shifts and the changing mobility needs of Europeans.ACEA is working towards a new era of mobility,where all Europeans can access affordable transport solutions that are:Green&Clean Smart&Efficient Safe&ReliableOur aim is to drive Europes mobility transformation while at the same time ensuring that the auto industry remains a strong Global&Competitive player.WHAT ACEA DOESACEA acts as one with common industry positions that also reflect the overarching interests of European citizens,transport users and operators,and auto industry workers.We bring our collective expertise to policy makers,sharing a wealth of factual information to enable well-informed decisions.We foster a societal debate around mobility,and are open to working with all interested parties to advance the common aim of clean,smart,and safe mobility.ACEA|September 2024ACEAEuropean 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1Electrification of LogisticsOpportunities,Challenges,and Strategies for an Industry in TransitionWHITEPAPERTable of Contents03Foreword05Dynamics and Change in Logistics07EU Legislation09Challenges11Cost Efficiency and Sustainability12MHPs Roadmap to Electrification20Outlook13The E-Mobility Ecosystem Framework 08The Growing E-Truck Ecosystem03ForewordClimate-neutral by 2050:How Electric Trucks Are Driving Europes Green TransformationClimate-neutral by 2050:This is the ambitious goal that the European Union has set to combat global climate change.With road freight transport accounting for 77%of all freight traffic within the EU,its clear that this sector is key to these efforts.Traditional trucks contribute significantly to CO2 emissions,which makes their electrification crucial to meeting climate targets.However,this transition faces a critical challenge known as the“chasm”the gap between early adopters and the early majority.This whitepaper will show you how switching to electric trucks can lead to significant cost savings,compliance with stringent environmental regula-tions,and an improved corporate image.However,the transition is not without its challenges:financ-ing,driver skepticism,the still-growing charging infrastructure,and technical requirements like range and charging cycles are just a few of the issues well explore.Our goal is to provide you not only with the informa-tion and analyses that you need,but also with con-crete suggestions for making your logistics processes future-proof and sustainable.This whitepaper is an essential tool for anyone in the logistics industry who wants to embrace the challenges and opportunities of e-mobility.Learn how you can benefit from electrifying your truck fleet and seize the opportunity to estab-lish yourself as an innovation driver in your indus-try while also making an important contribution to environmental protection.Table of Contents04The Challenges of“The Chasm”The term“chasm”refers to a key concept intro-duced by Geoffrey A.Moores in“Crossing the Chasm.”It describes the critical phase in the intro-duction of technology products to the market,in which the product must overcome the gap between the early adopters and the early majority.This phase is decisive for determining whether a new technol-ogy will successfully reach the general public,or if the product will fail.Moore emphasizes the need for specific strategies to successfully bridge this gap and reach broad market acceptance.Market penetration of e-trucksAcceptance of e-trucks by companiesEarly AdoptersInnovatorsEarly MajorityLate MajorityLaggardsGrants and FundingCostsCharging InfrastructureEcosystem“Chasm“Early MarketMainstream MarketFiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents05To illustrate the momentousness and urgency of these changes,we will present current data,figures,and facts related to the logistics industry and truck electrification.Europes E-Truck Market:Some Growth,but Room for ImprovementDue to increasing pressure to reduce CO2 emissions,we are seeing a positive trend in the registration of electric trucks(e-trucks).In 2023,there was a striking increase in e-truck registrations in the Euro-pean Union.According to the latest data from the European Automobile Manufacturers Association(ACEA),registrations of e-trucks rose by an impres-sive 234.1%,totaling 5,279 units.The Netherlands and Germany were leaders in this growth,with increases of 889.7%and 169.8%respectively.Sales in these countries made up over 60%of all e-truck sales in the EU.The market share of e-trucks climbed from 0.8%in 2022 to 1.5%in 2023.While this is a significant step forward,it also shows that there is still a long way to go before widespread market penetration is achieved.Why Road Freight Transport Remains Crucial for Europes EconomyThe growing share of road freight transport within the EU contrasts with the original goal of shifting more freight transport to rail and inland waterways.In 2021,only about 17%of freight in the EU was transported by rail and 6%by inland waterways.This clearly shows that road freight transport con-tinues to dominate and significantly contributes to CO2 emissions.Dynamics and Change in Logistics:Trends and Statistics on Truck ElectrificationTable of Contents06Growing Market,Growing Pressure on LogisticsAlong with the continuous increase in road freight transport,the number of trucks is also rising.In Ger-many alone,the number of trucks has increased by over one million in the last ten years.As of January 1,2022,about 530,000 heavy trucks with a permissi-ble total weight of over 3.5 tons were registered in Germany,accounting for about 15%of the 3.55 million registered trucks of all sizes.Another problem exacerbated by the growing logistics market is the shortage of parking spaces.Currently,Germany lacks about 40,000 truck park-ing spaces at rest stops.This severely limits drivers ability to comply with legally required break times and overnight stays.With the increasing number of electric trucks,which not only require fixed parking spaces but also additional charging infrastructure,this problem will further intensify.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents07To meet the requirements of the Paris Agreement,the European Union has significantly tightened its CO2 emission standards for heavy commercial vehi-cles.The latest amendments,ratified by the Council of the European Union in May 2024,set stricter emission targets for 2030,2035,and 2040.The tar-get for 2030 has been raised from a 30%reduction to a 45%reduction compared to 2019 emission levels;the 2035 target is a 65%reduction,and the 2040 target is a 90%reduction.Political pressure and hefty fines for non-compliance with fleet limits are propelling the transition forward.In the past,generous subsidies played a crucial role in incentiv-izing alternative drives.Even though these subsidies have since been discontinued,their reintroduction remains a key component in the successful transfor-mation of the logistics sector.To achieve Germanys goal of reducing greenhouse gases,the federal government is focusing on the electrification of vehicle fleets.Initially,the focus was on the passenger car sector,so the purchase of electric vehicles was incentivized,and the nec-essary charging infrastructure was expanded.Now,the need to expand the charging infrastructure for electric commercial vehicles is also being explicitly addressed.For the first time,the governments“Master Plan Charging Infrastructure II”addressed the rapid improvements in charging infrastructure for heavy trucks in a separate chapter.To support the ramp-up of electric heavy commercial vehicles,an adequate charging network is needed to ensure long-dis-tance mobility,high charging capacities,and suit-able spaces for trucks.The development of an initial charging network along key long-distance routes is a concrete measure of the master plan and was expected to be tendered in the third quarter of 2023 in cooperation with Autobahn GmbH.As of the third quarter of 2024,this charging network has yet to be tendered.As part of Master Plan II,a public tender for the construction and operation of fast-charging stations for trucks at unmanned rest areas along the federal autobahn is expected to be launched in late summer 2024.EU Legislation:The Driving Force Behind Europes Focus on E-TrucksTable of Contents08In addition to subsidy measures and a nationwide charging infrastructure,a holistic ecosystem is essen-tial if we want to successfully electrify the logistics industry.A mobility ecosystem is a complex network of actors,resources,technologies,and institutions that work together to provide,optimize,and con-tinuously develop mobility services.It incorporates individual components such as vehicles,infrastruc-ture,energy sources,services,and regulatory mech-anisms;interactions within this system significantly influence peoples movement as well as the social,economic,and environmental aspects of mobility.A well-functioning mobility ecosystem is important because it ensures efficient,sustainable,and com-prehensive mobility offerings.By optimizing the inte-gration of a variety of elements,the ecosystem can help to improve traffic flow,reduce environmental impact,and meet user needs.It also enables the development of new mobility solutions that meet the changing needs of society.The existing mobility ecosystems are designed for conventional vehicles.However,e-trucks have specific requirements for charging infrastructure,energy supply,and technological integration.To ensure their smooth operation and fully realize the potential of e-mobility in freight transport,it will be necessary to create an ecosystem tailored to e-trucks.Although all major manufacturers have already introduced e-trucks,it is now crucial that key players such as governments,local authorities,energy providers,charging station operators,and logistics and transport companies work together to develop and expand the necessary infrastructure.These key players play a vital role in creating an eco-system that makes it possible to seamlessly deploy e-trucks and fully exploit the potential of e-mobility in freight transport.Currently,charging stations for e-trucks are rare,but forecasts predict massive expansion in the coming years.Aral is a pioneer in this area in Germany and(2024)already operates more than 20 charging sta-tions for electric trucks,with a capacity of 300kW each.Furthermore,new locations are planned to expand the infrastructure and meet the needs of electric large vehicles.The Growing E-Truck EcosystemTable of Contents09Making the switch to e-trucks poses numerous chal-lenges,ranging from financing to driver skepticism to public charging infrastructure.These challenges were identified during numerous interviews that MHP carried out with numerous players in the logis-tics sector.Here are the five greatest challenges that the logistics sector must overcome to successfully manage the transition to e-mobility.1:FinancingFinancing e-trucks is a significant challenge for many companies,especially since the funding programs for such vehicles have been discontinued.Although there is still some support for the construction of charging infrastructure,the discontinuation of direct vehicle subsidies through the“Climate-friendly Commercial Vehicles and Infrastructure”(KsNI)program significantly increased the financial burden on companies.This situation makes the widespread adoption of e-trucks difficult and challenges logistics companies to explore alternative financing models and develop efficient operational strategies.2:Driver skepticismRecruiting drivers for e-trucks can be a challenge.While experienced drivers tend to be enthusiastic,inexperienced drivers are often uncertain and reluc-tant to adopt new technologies.MHPs interviews revealed that attitudes toward e-mobility are highly individual;there is no across-the-board skepticism.Companies aim to build driver confidence by demon-strating real-world use cases,while also emphasizing the need for open dialogue so they can adapt the technology to meet drivers needs.The transition to e-mobility requires both technical and cultural adjustments.3:Public charging infrastructureThe availability of public charging infrastructure for e-trucks is crucial for the logistics sector.Depending on their charging speed and the availability of charging locations,e-trucks can,in most cases,only be charged at logistics companies depots due to the lack of widespread public charging infrastructure.This limits their use to predefined routes with a max-imum range of 150 km.For widespread integration of e-trucks in the logistics industry to be possible,nationwide public charging infrastructure is needed.Insights from the Logistics Industry:Top 5 Challenges in the Transition to E-TrucksTable of Contents104:Range and charging cyclesAn e-trucks range has a significant impact on how practical and usable it is.In an interview with MHP,a leading transportation company in Austria,points out that the limited range makes it difficult to use them everywhere,especially in urban areas.More-over,a well-known postal company pointed out that comparing e-trucks to diesel trucks is unfair,as diesel technology has been perfected over the course of a century,while battery technology is still in its infancy and needs a quantum leap to catch up.According to truck drivers,vehicle range is indeed important,but the suitability is determined by the specific use case an e-truck must be able to effectively replace a diesel.5:Alternatives to the secondary marketThe secondary market for e-trucks is still in its early stages and faces a variety of challenges.In its con-versation with MHP,the Austrian transport company emphasized that the residual value and resellability of e-trucks and batteries are unclear,which damp-ens interest in the secondary market.Companies wonder what will happen to the e-trucks after their initial use.Currently,they are frequently exported to Africa.However,in the future,the batteries could be replaced instead.These uncertainties underscore the need for thoroughly evaluating the situation and developing a strategy to ensure a trouble-free segue to the sustainable reuse of these vehicles.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents11Choosing e-trucks offers businesses a multitude of advantages that have a positive effect on both their finances and their environmental footprint:Reduce operating costs:E-trucks lead to a sig-nificant reduction in operating costs compared to traditional diesel trucks.This is due to lower energy consumption,lower electricity prices,and lower maintenance requirements.Additionally,battery-electric vehicles are not subject to tolls,which further reduces operating costs.Meet sustainability goals:Switching to e-trucks helps companies meet stringent envi-ronmental standards and reduce their CO2 emis-sions.This is crucial for meeting future regulatory requirements and strengthening the companys image as a responsible player in the market.Increase operational efficiency:E-trucks offer better energy efficiency.Technological advance-ments such as regenerative braking further reduce operating costs.Increase acceptance in urban areas:With the increasing number of emission restrictions in urban areas,e-trucks provide the opportunity to operate in environmentally regulated zones without restrictions.This makes them particularly valuable for inner-city distribution.An additional advantage is that e-trucks significantly reduce noise pollution,which improves the quality of life in urban environments.By adopting e-trucks,companies not only position themselves as pioneers in technological development but also enhance their competitiveness through increased efficiency and improved compliance with environmental standards.Cost Efficiency and Sustainability:The Double Benefit of Electric Trucks Table of Contents12As part of our structured approach to supporting our clients,we have developed a comprehensive five-step model.This model is based on detailed data research and customer consultations and is designed to ensure the seamless and efficient transformation of your logistics processes.MHPs Roadmap to Electrification:Our Five-Phase Model for Transforming Your LogisticsThe biggest challenges here are cost control,overcoming the“chasm”,and data integration.Factors that contribute to success include step-by-step electrification,charging optimization,employee training,and close collaboration with partners to integrate their charging infrastructure.MHP is committed to developing a comprehensive strategy that will guide your company through the entire transformation process and prepare it for a sustainable future.1 I Research2 I Check3 I Planning4 I Validation5 I ScalingIn-depth analysis and data collection to document current operational processes.Detailed opera-tional planning and requirements analysis for optimal integra-tion of solutions.Practical tests of the implemented strategies and techno logies to verify their effectiveness.Development of concepts and obtain-ment of required authorizations to ensure feasibility and compliance.Expansion of the ecosystem to enhance the solu-tions and encourage broader adoption.Analysis&data collectionOperational planning&requirements analysisVerification&commissioningConcept development&authorizationIntegration&ecosystem expansionThe Five-Phased Process ModelTable of Contents13To effectively address the challenges described ear-lier and bridge the“chasm”,MHP has developed the E-Mobility Ecosystem Framework specifically for electric trucks.This framework uses a clear visual representation to illustrate the ecosystem for e-trucks.It also provides a point of orientation that,like a compass,helps businesses successfully navi-gate market challenges and gaps.With a pragmatic approach,this framework makes it possible to create customized portfolios along the value chain.Based on this solid foundation,the ecosystems expected development for the coming years is further ana-lyzed and presented using the same framework.The MHP E-Mobility Ecosystem Framework is struc-turally divided into three basic components:seg-ments,circles and elements.The segments are divided into hardware,software and service,which form the technical and service-oriented basis of the system.In addition,three interlinked circles energy,charging and vehicle visualize the key areas of elec-trification.In addition,specific tasks and priorities within the framework are represented by individ-ual elements of different sizes,ranging from basic requirements to specialized extra functions.The Segments of the FrameworkThe E-Mobility Ecosystem Framework The second segment examines software aspects in detail;it is crucial that software design be hardware-agnostic and backward-compatible.The third segment illustrates the ecosystem of services and functions,offering room for continuous expansion and monetization.This segment includes hard-ware and addresses in detail the technological aspects of electric trucks,ensuring a future-oriented vehicle design.Table of ContentsServiceHardwareSoftware14The Frameworks CirclesThe E-Mobility Ecosystem Framework uses a clear visual representation in the form of concentric cir-cles,along with segmentation,to illustrate the var-ious fields of action in the electrification of truck fleets.Each circle represents a specific area of focus essential to the transformation process.The circles clarify the frameworks structured approach.The Frameworks ElementsThe MHP E-Mobility Ecosystem Framework not only divides the ecosystem into segments and circles,but also into elements that are differentiated by their dot sizes.The large dots(Basis)represent funda-mental components that are essential to avoid falling behind in the market.The medium dots(Priority)stand for priority components that offer market participants the chance to gain competitive advantages.The small dots(Extra)indicate additional components through which market partici-pants can differentiate themselves.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of ContentsThe outermost circle addresses all elements related to“energy”.This includes the generation and management of the energy needed to operate the electric vehicles.The middle circle focuses on everything related to“charging”,incorporating components and processes necessary to construct and manage an efficient and accessible charging infrastructure.The innermost circle represents the“vehicle”itself,addressing all aspects directly related to the electric truck.The vehicle serves as a central interface between the other areas,making it an integral part of the overall system.EnergyChargingVehicle15HardwareSoftwareServiceEcosystem FrameworkDynamic charging/pricingCharging station reservationsWirelessBattery swapEnergy storageElements of MHPs E-Mobility Framework(EMF)BasisExtraPriorityPhotovoltaic/Balcony power plantHEMSDC converterDC wallboxDC charging stationAC wallboxBIDIPlug&chargeTHG quoteAuthen-tificationBillingLoad managementSmart chargingCharge XLoyaltyAdhoc chargingE-consul-tationInstallationCharging ratesElectricityEnergyChargingVehicleFiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents16The MHP E-Mobility Ecosystem Framework in PracticeThe individual elements of the framework make it possible to visualize the complex ecosystem and map specific company portfolios.With this visualization,companies can perform direct competitive analysis and identify which components are included in the market leaders portfolio.This enables them to iden-tify gaps in their own product portfolio and make strategic decisions to catch up with the competi-tion or,in the best case,build a long-term strategic advantage.Over the course of a client relationship,MHP helps companies seamlessly integrate electric trucks into existing logistics structures.Our comprehensive framework ensures that the electrification process is systematic and efficient,with careful planning and execution of every detail from initial analysis to full scaling.The following graphic illustrates an example port-folio of a logistics company that owns around 50 vehicles and intends to electrify 10%of its fleet.Example Portfolio for a Logistics Company Planning to Electrify its FleetFiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents17The practical application of the MHP E-Mobility Eco-system Framework involves a systematic approach to the successful design of truck fleet electrification.The key steps are:1.Analysis and strategy developmentWe begin with a detailed analysis of the existing fleets and create an electrification strategy tailored to your specific needs.This includes identifying opti-mal routes and vehicles for the start of the electrifi-cation process and planning the required charging infrastructure.2.Implementation and trainingAfter planning is complete,the process continues with the implementation of the charging infrastruc-ture and staff training.Our experts ensure that all stakeholders can confidently and efficiently handle the new systems,which promotes quick adoption within the company.3.Monitoring and adjustmentAfter the e-fleet is deployed,we monitor perfor-mance and continuously adjust processes to take advantage of potential optimizations and achieve maximum efficiency and cost savings.4.Scaling and ongoing innovationOnce the initial phase is successfully completed,MHP will assist you in scaling your electric truck ini-tiatives.We help you integrate innovative solutions like smart charging and continuously develop your ecosystem.A collaboration with MHP gives you access to indus-try-leading consulting and technology,as well as a partner dedicated to your long-term success.We work closely with you to design an optimum elec-trification strategy and position you as an innovative leader in the logistics industry.Use our expertise to achieve your sustainability goals while simultane-ously increasing operational efficiency.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents18Concrete Recommendations for Logistics CompaniesTo make electrifying your truck fleet successful and efficient,we offer comprehensive support as part of our e-consulting services.These recommendations are based on our proven strategic framework and are tailored specifically to your particular customer portfolio.Driver training and high-voltage management Driver training:Intensive training programs for drivers are essential to ensure safety and efficiency when dealing with electric trucks.These training programs should include safe handling of high-voltage technologies,optimizing driving behavior to maximize battery life,and handling emergencies.High-voltage safety training:Special training modules on proper handling of high-voltage systems should ensure that all technical staff are trained in dealing with the new technologies and are familiar with emergency procedures.Reservation systems Integration of reservation systems:Logistics companies should pursue direct collaborations with OEMs or charging station operators so they can effectively integrate these reservation systems into their operations.That will make it possible to check availability in real time to plan and book charging sessions efficiently.Route and schedule adjustments:The system should be flexible enough to allow for adjust-ments to routes and schedules based on the cur-rent charging situation and the specific supply chain requirements.Charge X Providing a comprehensive information system:Companies should develop a system that not only provides information about the location and availability of charging stations but also offers detailed information about the facilities available at charging locations.This includes restaurants,waiting areas,showers,Wi-Fi access,and rest areas.Optimizing the charging experience:Companies should also ensure that the charging experience for drivers is as pleasant and efficient as possible.All necessary amenities and information should be easily accessible.In-depth analysis of elements in the portfolio Competitive analysis:We recommend a detailed analysis of the competitive landscape to under-stand where the company stands in the market and how it can differentiate itself.Identifying profit pools:It is necessary to analyze the most profitable areas of logistics electrifica-tion and develop targeted strategies to exploit this potential.Strategic recommendations:Based on the results of the analysis,we provide tailored recommen-dations to help you achieve operational excel-lence and strengthen your market position.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of Contents19In addition to offering comprehensive consulting services for logistics companies,MHP also provides support for OEMs and charging station operators involved in the electrification of trucks.Our expertise spans a wide range of industries and thematic areas,allowing us to offer customized solutions for every phase of electrification and beyond.Regardless of your position in the value chain,MHP can provide strategic insights and practical recommendations for successfully implementing your electrification strategy and future-proofing your business.FiguresEU LegislationForewordChallengesE-Truck Ecosystem FrameworkBenefitsOutlookRoadmapTable of ContentsElectrification of E-Truck Fleets is the Key to the FutureWe are at a crucial turning point:the electrification of our truck fleets is essential to reach environmen-tal policy goals and shape our future sustainably.Political support and legal provisions are key driv-ers behind electrification.Successful management of the transformation will take a holistic approach that integrates technical innovations,cultural adap-tations,and practical solutions.A well-functioning,optimized ecosystem that links vehicles,infrastruc-ture,energy sources,and services is essential.Companies that make the switch to electric trucks early on can position themselves as innovation lead-ers while also making a significant contribution to protecting the environment.With this proactive approach,companies will benefit not only from lower operating costs but also from a boost to their brand image,as they demonstrate their commitment to sustainable business practices.Use our insights and recommendations to future-proof and sustain-ably design your logistics processes and establish yourself as a responsible market player.MHP is here to help you successfully navigate the challenges of e-mobility and make the most of the opportunities it offers.Let us help you to make emission-free logistics a reality and actively shape the future of mobility.Together,we can successfully position your company in the market.Outlook20Table of Contents21PublisherMHP Management and IT Consulting GmbHENABLING YOU TO SHAPE A BETTER TOMORROWAs a technology and business partner,MHP has been digitizing the processes and products of its roughly 300 mobility and manufacturing sector customers worldwide for 28 years and providing support for their IT transformations along the entire value chain.MHP believes that digitalization is one of the most effective levers on the path to a better tomorrow.This is why MHP provides both operational and strategic consulting in areas such as customer experience and workforce transformation,supply chain and cloud solutions,platforms and ecosystems,big data and AI,as well as Industry 4.0 and intelligent products.The subsidiary of Porsche AG operates internationally,with headquarters in Germany and subsidiaries in the USA,UK,Romania,and China.Around 5,000 MHP employees are united by their pursuit of excellence and sustainable success.It is this aspiration that continues to drive MHP today and in the future.Dustin LangeManagerMobility Transformation Esma ErogluConsultantMobility Transformation Selina HeiligersConsultantMobility Transformation Get in Touch!Florian WindelerSenior ManagerMobility Transformation Felix WeigandSenior ConsultantMobility Transformation ContactDEMaximilian Sander Partner Tel.: 49(0)7141 78562 7330 E-Mail:MHP Management-und IT-Beratung GmbH Film-und Medienzentrum Knigsallee 49 71638 Ludwigsburg GermanyUSCHINATobias Hoffmeister CEO Tel.: 1(0)770 3918 181 E-Mail:MHP Americas Inc.One Porsche Drive Atlanta,Georgia,30354 USAThomas Mooser CEO Tel. 49(0)7141 7856 2757 1 E-Mail:MHP(Shanghai)Management Consultancy Co.,Ltd.Room 705-706,No.288 West Nanjing Road Huangpu District,Shanghai P.R.CUKBodo Philipp Director Tel.: 49(0)7141 7856 2636 7 E-Mail:MHP Consulting UK Limited Bath Road Calcot Reading RG31 7SE United Kingdom
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AI AS GAME CHANGER The New Driving Force of the Automotive IndustrySTUDYAuthors&Contact personAuthorDr.Nils SchaupensteinerTransformation AdvisoryNils.SLeadAugustin FriedelSoftware Defined VehiclesAugustin.FLeadMatthias BorchArtificial IntelligenceMatthias.BContact PersonStephan BaierArtificial IntelligenceStephan.BAuthorMarcus WillandMobility Marcus.WAuthorPatrick RuhlandTransformation AdvisoryPatrick.RThe study“AI as Game Changer“and its summary were published by:MHP Gesellschaft fr Management-und IT-Beratung mbHAll rights reserved!No reproduction,microfilming,storage,or processing in electronic media permitted without the consent of the publisher.The contents of this publication are intended to inform our customers and business partners.They correspond to the state of knowledge of the authors at the time of publication.To resolve any issues,please refer to the sources listed in the publication or contact the designated contact persons.Opinion articles reflect the views of the individual authors.Rounding differences may occur in the graphics.3AI as Game Changer|ContentsContents 4Table of figures 612 Key Findings 8Welcome to Change!1001.Revolution and Automotive Market Potential 1102.Investment in Companies With an AI Focus 1503.Pilot Projects and Implementation 1904.AI Models,Levels,and Use Cases 234.1 The Game Changer:What Can Be Achieved With AI 264.2 Automobile Manufacturers With Low AI Investment 294.3 AI Models:Make or Buy?2905.AI Applications Along the Automotive Value Chain 315.1 AI Operation in Vehicles and in the Cloud 355.2 AI Monetization in Vehicles 395.3 Added Value of AI Applications in Companies 4006.What the Customer Wants:The User Perspective 476.1 Use and Understanding of AI Applications 496.2 Advantages and Disadvantages Generally and in Vehicles 496.3 Purchasing Decision,Trust and Willingness to Pay 51407.Success Factors and Strategic Approach 557.1 Strategy and Goal Planning 567.2 Think from the Perspective of the Customer,not the Technology 567.3 Organizational Anchoring and Ownership 587.4 Local Differences require local Setup 597.5 Reducing Complexity 597.6 Use and Monetization of Data 607.7 Checklist for successful Implementation 6108.Challenges,Responsibility,and Risks 638.1 Costs of Training and Operation 648.2 Data and Digitalization as a Basis 658.3 Business Models and Cases for B2C and B2B 658.4 Ethics and Responsibility 678.5 New Risks and Regulatory Challenges 6909.AI Applications in the Automotive Industry:7 Recommendations for Action 7110.Further Informations 75Literature and Sources 76Contact International 78About MHP 795AI as Game Changer|ContentsTable of figuresFigure 1:Technology super cycles artificial intelligence as the next relevant platform shift (Coatue,2024)12Figure 2:AI market size in the automotive sector(Precedence Research,2024)12Figure 3:Total investments in AI companies founded since 2001,in USD billion(Scheuer,2024)16Figure 4:Investment in AI stack layers(Coatue,2024)17Figure 5:Companies with team and budget for AI(Capgemini,2023)21Figure 6:Interconnected AI concepts 24Figure 7:Visualization of AI as a pyramid 25Figure 8:Classification of AI terms 27Figure 9:The performance of AI models compared to human capabilities in the MMLU test(iAsk,2024)28Figure 10:Schematic diagram of the training of AI foundation models for vehicles 30Figure 11:Use of AI along the value chain 32Figure 12:Significant improvements of functions and features through AI 33Figure 13:Interest in AI functions compared internationally 34Figure 14:Role of on-premise,cloud,and vehicle for AI models 35Figure 15:Levels of a software-defined vehicle(SDV)(Willand,Friedel,&Schaupensteiner,2023)36Figure 16:Different models for ADAS and AD applications and functions 37Figure 17:AIs potential at different stages of the value chain(Capgemini,2023)40Figure 18:Use of AI-based solutions by region 41Figure 19:Key drivers behind the use of AI in production 426Figure 20:Decisive issue fewer users of software due to AI or free software(Coatue,2024)43Figure 21:Possible uses of AI in software development(Wee 2024)44Figure 22:Understanding of AI in cars 48Figure 23:Advantages of using AI in cars 49Figure 24:The perceived advantages and disadvantages of using AI 50Figure 25:AI in cars:purchase motivation or blocker?51Figure 26:Trust in stakeholders with regard to the implementation of AI in vehicles 52Figure 27:Willingness to pay for AI functions 52Abb.28:Assessment of the future AI competence of car manufacturers by region 53Figure 29:Customer and use case first,and then AI applications and models 57Figure 30:Dimensions for validating technical feasibility 57Figure 31:Training costs for AI models are increasing(Stanford University,2024)64Figure 32:Data availability and quality by region 65Figure 33:Customers willingness to pay is unclear;costs arise for implementation and operation 66Figure 34:Classification of AI use case categories and possible business models 67Figure 35:Risks associated with the use of AI 68Figure 36:Principles and penalties of the EU AI Act 70Table 1:The development of AI models divided into different time phases 277AI as Game Changer|Table of figuresof respondents in China state that the risks of AI outweigh the benefits;this figure is around 25 percent in Europe and the US.of respondents see time-saving as the biggest benefit of AI applications.More than OnlySkepticism about AI applications is greater in the US than in Europe or China.The most frequently mentioned disadvantages of AI are fear of loss of control,loss of data protection and personal privacy,and security risks.The widespread use of AI is predicted to be the next relevant platform shift after cloud transformation original equipment manufacturers(OEMs)need to step up their activities.12 Key Findings 8Successful implementation of AI applications is not possible without prior digitalization and access to specific data sources.Customers worldwide want to use AI in cars,but rarely pay for it.In China,more than twice as many customers have already used AI in their cars as in Europe.Today,Chinese car manufacturers are regarded as leaders in AI innovation.In five years time,Japanese OEMs will be at the forefront,followed by Chinese and German OEMs.Traditional car manufacturers are the most trusted when it comes to the use of AI,far ahead of state institutions and new car manufacturers.AI is not only revolutionizing the in-vehicle customer experience the entire value chain is experiencing disruptive change.In China,AI functions mostly have a positive influence on car purchasing decisions only of respondents would not buy a vehicle based on AI functions.KI9AI as Game Changer|12 Key Findings Welcome to Change!Dear readers,Artificial intelligence will be the next platform shift that revolutionizes all industrial sectors.Stakeholders in the automotive value chain have realized that AI is challenging many tradi-tional processes and ways of thinking.The introduction of the PC,the stationary Internet and then the mobile Internet,and Cloud/SaaS previously had a similarly disruptive impact.New business models and profit pools are emerging,while at the same time there are nu-merous challenges to be tackled with regard to technology,partnerships,and ethical issues.In this study,we trace the groundbreaking developments in AI so far and examine the op-portunities and risks within the automotive industry.Accompany us through present and future scenarios with specific recommendations for action for your own strategy when it comes to implementing AI applications in production and in vehicles.Whether the new technologies meet the expectations of drivers is determined right there in the cockpit.Thats why,in Chapter 8,we outline the user perspective based on our own current data.Our international survey provides information about which products and services from automotive companies could fulfill AI needs and what the willingness to pay looks like.That makes this study essential reading for decision-makers,CIOs,and applica-tion developers.Investors in AI technologies and AI teams need a consistent,long-term cost-benefit ratio.We therefore examine the direct/indirect monetization of in-car AI and look at new business models based on AI and digitalization.Ultimately,as is so often the case,it becomes clear that the journey into new technological territory is best undertaken with experienced travel guides.Get the know-how you need and always be curious!ENABLING YOU TO SHAPE A BETTER TOMORROWBest regards,Dr.Jan WehingerCluster Lead Software Defined Vehicles MHP Management-und IT-Beratung GmbHLudwigsburg,September 20241001.Revolution and Automotive Market Potential11AI as Game Changer|01.Revolution and Automotive Market PotentialFigure 2:AI market size in the automotive sector(Precedence Research,2024)AI-Based systems for automotive industry to reach US$35.7 billion by 203320233.23.94.75.87.39.211.715.220.026.635.7.in billion US$2024202520262027202820292030203120322033Figure 1:Technology super cycles artificial intelligence as the next relevant platform shift (Coatue,2024)Everyone recognizes that AI is the next platform shift2022.Generative AIMainframePCNetworkingDesktop Internet(Web 1.0)Mobile Internet(Web 2.0)Cloud/SaaS201520202010s2000s1990s1980s1960198012It is highly likely that the big technology companies such as Google,Meta,and Microsoft which gained in importance with the last platform shifts(super cy-cles)will also dominate the AI age.Along the automotive value chain,stakeholders are sometimes accused of having responded to the last platform shifts too late or with an ineffective strategy.In our opinion,the relevance of connectivity and cloud solutions was recognized too late and implementation could have been better.The industry is at the begin-ning of the AI platform shift and there is still the op-portunity to respond early with a targeted strategy.Companies like Apple have shown that it is not neces-sary to be the first innovator.With a strong AI strategy,a company can also exploit potential as a fast follower.The market for artificial intelligence in the automotive industry has shown remarkable growth in recent years.It is currently estimated to be around USD 3.9 billion in 2024 and is expected to grow to USD 15 billion by 2030.Some market analyses anticipate that AI sales in the automotive sector will rise to over USD 35 billion in 2033.Growth from 2024 to 2033 corresponds to a rate of 28 percent.Estimates in other market reports may be slightly high-er or lower,but all show the same trend.This means that extensive economic opportunities are being creat-ed along the value chain for manufacturers,suppliers,and service providers.One fear,however,is that artificial intelligence will increasingly replace people and jobs may disappear.Currently,AI applications are regarded more as a com-plement rather than a replacement.Academics such as Karim Lakhani from Harvard Business School believe that AI will not replace humans.One possible scenario is that people who use AI will have a significant advan-tage over workers who do not use it.Regarding the question of whether AI will improve the economy,a survey shows a mixed picture.Worldwide,34 percent of respondents believe that the use of AI will improve the economic situation in their country in the next three to five years.This hope is above average in countries such as Thailand,India,and South Africa.At the lower end of the ranking are countries includ-ing Belgium,Japan,the US,and France(Ipsos,2023).Overall,there are increasing signs that there are far more opportunities than risks.The targeted use of arti-ficial intelligence will significantly affect our prosperity in the coming decades.AI boosts efficiency and can counter the negative effects of skills shortages,demo-graphic changes,and high location costs.It is now up to the automotive industry to take bold and appropri-ately fast action and follow a strategically intelligent approach.“AI Wont Replace Humans But Humans With AI Will Replace Humans Without AI.”(HBR,2023)13AI as Game Changer|01.Revolution and Automotive Market Potential1402.Investment in Companies With an AI Focus15AI as Game Changer|02.Investment in Companies With an AI Focus6.1 bn.US$France5.0 bn.US$Germany16.5 bn.US$Great Britain39.6Bn.US$bn.US$101.216.6 bn.US$Boston4.6 bn.US$Washington DC7 bn.US$Seattle10.2 bn.US$Los Angeles5.3 bn.US$San Diego8.4 bn.US$Dallas55.8 bn.US$San Francisco29.2 bn.US$New YorkBn.US$234.141.7 bn.US$Silicon ValleyA look at the distribution of AI investment shows the dominance of those regions that also dominated the market in the last platform shifts(see Coatue,2024;Figure 1).It can be assumed that the automotive in-dustry will continue to be dependent on hyperscalers and technology companies.Collaborations regarding software,cloud applications,and the use of AI are ex-pected to increase.An analysis shows that a large share of the investment in AI companies comes from the US.A closer look(Coatue,2024)shows that only approx.3 percent of the venture capital deals have a clear link to AI,but that 15 percent of the invested capital flows into AI start-ups.From this imbalance,it can be concluded Figure 3:Total investments in AI companies founded since 2001,in USD billion (Scheuer,2024)that the market sees relatively high valuations and correspondingly high investment rounds.The financ-ing rounds show that most of the investments in 2024 went into companies that develop AI models such as ChatGPT,Mistral,and Claude.A total of USD 14 bil-lion was invested in AI models in the first half of the year.This equates to 62 percent.In 2024,a smaller proportion of the capital invested in AI companies went into firms that develop semicon-ductors for AI applications.Robotics applications,such as humanoid robots,garnered approx.USD 2 billion in capital,which corresponds to around 9 percent of the total.Magnet for investment:Total investment in AI companies founded since 2001 in billions of US dollars16Figure 4:Investment in AI stack layers(Coatue,2024)62%AI Models20%AI Apps9%AI Ops/AI Cloud9%AI Robotics 1%AI Semis020406080100Where are AI VC dollars going?Funding$14B$4B$2B$2B$100MAmong the largest investors in the AI field are the major technology companies including Microsoft,Amazon,NVIDIA,and Alphabet(Googles holding company).In 2023,these companies invested around USD 25 billion and were thus responsible for 8 percent of investment.Car manufacturers investments in companies that deal with artificial intelligence are more modest.Below are some examples:Investments by NIO CapitalMomenta:Start-up with a focus on autonomous driv-ing and on the development of technologies for envi-ronmental perception and high-precision mappingPony.ai:Company focusing on autonomous driving;it forms partnerships to develop mobility solutionsBlack Sesame Technologies:Company specializing in AI chips and systems Investments by BMW iVenturesAlitheon:Specializes in optical AI technology for ob-ject identification and authentication with FeaturePrint technologyRecogni:Focuses on high-performance AI processing with low power consumption for autonomous vehiclesAutoBrains:Develops AI solutions for the automotive industry,particularly in the field of autonomous driv-ing technologiesInvestments by PorscheSensigo:Developer of an AI-supported platform for optimizing vehicle diagnostics and repair processesWaabi:Canadian developer of AI-based solutions for self-driving trucksApplied Intuition:Provides software solutions for the development of driver assistance systems and auton-omous drivingCresta:Specializes in real-time intelligence for custom-er interactions and communication solutions17AI as Game Changer|02.Investment in Companies With an AI Focus1803.Pilot Projects and Implementation 19AI as Game Changer|03.Pilot Projects and Implementation Without comprehensive prior digitalization,the implementation of AI applications will be an insurmountable challenge.Car manufacturers and suppliers should allocate budgets for AI and build up expertise promptly.2030tbR6%RetailAerospace/defenseTele-communi-cationsHigh TechCar manufacturingAverageFigure 5:Companies with team and budget for AI(Capgemini,2023)Proportion of companies with a dedicated team and budget for AIIn the automotive industry,a mixed picture is emerging with regard to the acceptance and implementation of AI applications along the value chain.The level of im-plementation is low among suppliers and dealers and in after-sales services.Automobile manufacturers have made further progress in terms of implementation,but there is significant potential for improvement here.Looking at the automotive industry as a whole,only 4 percent of companies have begun to implement AI applications at selected locations.That is around half as much as in the pharmaceutical industry.In retail,the figure is four times higher.Some 28 percent of companies in the automotive value chain are working on AI pilot projects,and the vast majority(68 percent)are still at exploration stage(Capgemini Research In-stitute,2023).Only 30 percent of the companies in the automotive sector have a dedicated team and an extra budget for the introduction and implementation of AI projects.By comparison,the rate is 62 percent in retail,74 percent in the high-tech sector,and 52 percent in aerospace/defense.(Capgemini,2023)Interim conclusion:The automotive industrys invest-ment in AI has been below average to date;this affects budgets and specialized teams.Given the huge impact of AI on the industry,it is advisable to rectify this situa-tion quickly.21AI as Game Changer|03.Pilot Projects and Implementation 2204.AI Models,Levels,and Use Cases23AI as Game Changer|04.AI Models,Levels,and Use CasesFigure 6:Interconnected AI conceptsInterconnected AI conceptsEach concept is a specialized part of the one preceding it.AI covers a wide field that can be divided into several areas and terms using a hierarchical diagram:Artificial Intelligence(AI):Research area focusing on the creation of intelligent machines.Machine learning(ML):Branch of AI focusing on the development of machines that can learn from data.Deep learning:A sub-category of machine learn-ing based on artificial neural networks.Examples are convolutional neural networks(CNNs)and recurrent neural networks(RNNs).Generative AI:A special type of artificial neural net-works that generate data similar to the training data.Examples are generative adversarial networks(GANs)and large language models(LLMs).With AI applications,various categories of use cases can be implemented:Data management:This involves harmonizing data and obtaining findings.It is essential for the efficient use of information.Pattern recognition:This category includes anomaly detection,categorization,and prediction,and also time series analysis.These techniques en-able the identification of trends and patterns in large data sets.Decision-making:Includes recommendation sys-tems and recommended actions based on data analyses.These are used to support decision-mak-ing processes.Text and image processing:Includes semantic search,text summaries,and translations,which enable the processing and analysis of text and im-age data.Communication:This category includes voice rec-ognition,chatbots,voice control,intelligent pro-cess automation,and voice output,which facili-tates human-machine interaction.Creativity and content generation:The gener-ation of texts and images can automate and accel-erate creative processes.24Figure 7:Visualization of AI as a pyramidVisualization of AI as a pyramidAI systems can be visualized as a pyramid with a num-ber of layers.The lowest layer describes the computing power required for the other layers.Companies such as NVIDIA,ARM,and AMD are established companies that provide chipsets and high-performance comput-ers for this layer.Performance has developed rapidly in recent years.For example,market leader NVIDIA de-livered a 1000-fold increase between 2016 and 2024.The second layer from bottom consists of cloud in-frastructure and enablers.The biggest,most well-known companies that provide the infrastructure layer are companies such as Amazon with AWS,Alphabet with Google Cloud,and Microsoft with Azure.As in the cloud computing segment,the providers are re-gion-specific.In China,the infrastructure layer is op-erated by companies such as Tencent,Alibaba,and Baidu;they are among the chip providers largest cus-tomers.The computing capacity and the infrastructure layer are needed in order to improve the foundation mod-els(computer models trained by machine learning).The best-known foundation models are GPT-4 from OpenAI,Metas Llama models,and Googles PaLM models.These foundation models make applications and use cases possible.Users most likely come into contact with the applica-tion layer of the AI pyramid,for example when they ask a question in tools like ChatGPT from OpenAI,Claude from Anthropic,or Gemini from Google.Semiconductor ecosystemInfrastructure&enablerFoundational modelsApplicationsTrainingConvenienceInferenceADAS/ADOutside vehicle(e.g.cloud)In vehicle(pute units,software)25AI as Game Changer|04.AI Models,Levels,and Use CasesIt is important to distinguish between the follow-ing AI terms:AI models are mathematical and statistical con-structs that are developed and trained to carry out specific tasks based on data.AI components consist of AI models and include a pipeline for processing input and output data.They cover preprocessing(processing of raw data)and post-processing(preparation of results).AI capabilities are specific functions or features that the AI system can execute,such as voice or image recognition.AI use cases define the purpose and context in which AI capabilities are applied.A use case can in-clude several AI capabilities.Figure 8 shows how these elements build on one an-other.4.1 The Game Changer:What Can Be Achieved With AIThe development of AI models can be divided into dif-ferent time phases.We are coming out of the phase of artificial narrow intelligence(ANI),which was shaped by machine learning and applications like Siri and Al-exa.Generative AI models can be regarded as a devel-opmental step on the path to artificial general intelli-gence(AGI).In this phase,machines would be able to match humans in a wide range of cognitive abilities.In the phase of artificial superintelligence(ASI),AI ap-plications and machines with embedded AI will have surpassed humans as regards cognitive abilities.The use of AI will become a game changer because the technology enables the following functions for the first time:Human interaction Features:Ability to have colloquial and multi-level conversations,as well as use context and memory Importance:These characteristics enable AI to communicate more naturally and intuitively with people particularly crucial for applications such as virtual assistants.Human thinking Features:Logical thinking,the creation of world models and predictive abilities Importance:These abilities are important for solving complex problems and making well-founded deci-sions,similar to a human.Visual understanding Features:Profound interpretation,open set of con-clusions,understanding of consequences Importance:These aspects enable AI to analyze and interpret visual data,which is important in areas such as image processing and autonomous naviga-tion.Internet-scalable knowledge Features:Training on extensive textual and visual data,adaptation to new situations,awareness of local customs and signs Importance:These characteristics enable AI to in-tegrate knowledge from a variety of sources and apply it in different contexts.26AI model divided into phasesTable 1:The development of AI models divided into different time phasesOutputClassification of AI termsFigure 8:Classification of AI termsPreprocessingEmbeddingPostprocessingInputAI use casesAI capabilitiesAI components AI modelsArtificial Narrow Intelligence(ANI)Generative Artifical IntelligenceArtificial General Intelligence(AGI)Artificial Super Intelligence(ASI)TodayIn the next few yearsExample:Siri,AlexaExample:OpenAIMachine LearningMachine IntelligenceMachine ConsciousnessReturns answers based on existing data,based on algorithms andstatistical techniques.AI cannot create data instances independently.AI can create data instances independently.Not yet close to human intelligence.Comparable with a computer that comes close to human intelligence in all areas.Intellect that is superior to humans in many or all areas.27AI as Game Changer|04.AI Models,Levels,and Use CasesMeasuring Massive Multitask Language Understanding(MMLU)RankingFigure 9:The performance of AI models compared to human capabilities in the MMLU test(iAsk,2024)70u%iAsk ProClaude 3.5SonnetLlama 3.1TurboGPT-4oGeminiProGPT-4Llama 3Yi-largeQwen2InstructMistralLarge 2Expert AGI:93.0%Human expert:89.80.8986.584.584.282.782.482.480.079.379.3AI tech cards are simple tools that can be used to show the possible uses of AI.The method allows the clear documentation of application examples,added value,and limits of different AI applications.In recent years,the capabilities of AI models have continuously improved.For some tasks,the models are already coming close to human capabilities.In a benchmark test called Massive Multitask Language Un-derstanding(MMLU),which was developed to evalu-ate language models,current models are achieving ac-curacy values of 86 to 94 percent.The human expert opinion is 89.8 per cent.This means the first AI models are performing better than human experts(iAsk,2024).Background:The MMLU test consists of 57 tasks from the fields of mathematics,US history,law,and more.284.2 Automobile Manufacturers With Low AI InvestmentBased on different research(Shilov,2023),(Mu,2024)it can be assumed that NVIDIA sold approx.500,000 to 620,000 H100 and A100 chips in 2023.Around 450,000 of the chips were purchased by big tech and hyperscaler companies including Amazon,Microsoft,Meta,and Alphabet.One of the few automotive manufacturers to build up computing power on a large scale is Tesla.By the end of 2024,the number of H100 GPUs is expect-ed to increase from 35,000 to 85,000(Walz,2024).The supercomputer at Tesla will be used to train the models for the Tesla ADAS(advanced driver assistance systems),among other things.The inference of the models is expected to take place in the vehicles as far as possible.Other automotive manufacturers have so far been re-luctant to invest in their own data centers which can be used for AI applications.It is to be assumed that they will use the data centers of large technology com-panies to train AI applications and run them later.Advanced driver assistance systems(ADAS)support drivers in certain driving situations,in-crease safety,and enhance driving comfort.Automated/autonomous driving(AD):self-driving vehiclesInference is the process that a trained machine learning model uses to draw conclusions from new data.Example:A self-driving car recognizes a stop sign on a road it has never driven on before.The ability to recognize this stop sign in a completely new context indicates an AI model capable of mak-ing inferences.Forecasts predict that the demand for computing ca-pacity for the inference of models will increase in the long term and that the demand for AI training will de-cline in relative terms.Inference can take place either in the cloud or in processing units in the vehicles.As part of the development of software-defined vehicles(SDV),the computing power installed in the vehicles will continually increase,which is positive for the use of AI applications in vehicles.Distribution of the use of computing power in the cloud or in the vehicle de-pends very much on the use cases.4.3 AI Models:Make or Buy?A number of large language models are in existence already,and a great deal of time and money has been spent on developing and training them.Put simply,in-put data is required to build AI models in order to train foundation models in large data centers.The models are fed and trained with unstructured raw data from sources including Wikipedia,Reddit,books,Common Crawl,and research reports.To implement use cases,existing LLMs can be used and combined with relevant data sets.Selecting suitable LLMs per use case is a pertinent decision.It is import-ant to understand which type of use case and tasks each of the LLMs has been trained for and what data has been used for this.The information generated by an LLM should be checked because it could be out of date or the model may hallucinate if it cannot provide an answer(AWS,2024).Creating a user-defined language model from the ground up is a resource-intensive and complex pro-cess.However,companies also have other efficient options:the use of cloud-based interfaces.By adapting existing models to the specific require-ments of the organization and fine-tuning them with additional data,companies can strike a balance be-tween economic viability and individualization.This approach,known as retrieval-augmented generation(RAG),combines the strengths of pre-trained models with domain-specific knowledge.29AI as Game Changer|04.AI Models,Levels,and Use CasesFigure 10:Schematic diagram of the training of AI foundation models for vehiclesData strategy as an important lever for building AI applications in vehiclesIn addition,companies can also use existing open source language models and build on established foundations instead of starting from scratch.These models can be adapted for certain tasks or domains,which ultimately saves time and resources.Generative AI models can be linked to proprietary data sources.A semantic search layer is linked to a Q&A reference architecture;the different components fulfill the following tasks:Semantic search layer Raw documents are used as input.The documents are converted into embeddings that capture their semantic meaning.The embeddings are saved in a database.Q&A reference architecture The user asks a question.This is converted into an embedding for the chat.The embeddings are compared with those in the database in order to find relevant documents (similarity search).The relevant documents are fed into the prompt.Based on the documents and question,a response is generated and provided to the user.Applications Answering questions Sentiment analysis Following instructionsInformation extraction Image captioning Object recognitionOpen data resourcesCommon CrawlBooksWikipediaRedditVehicle manuals Customer data Mapping data Vehicle dataTrainingTrainingFine TuningSelective data sourcesFoundation models3005.AI Applications Along the Automotive Value Chain31AI as Game Changer|05.AI Applications Along the Automotive Value ChainAI is used along the entire value chain.Customers and OEMs benefit at different stages.1234785AI assistantsADAS6Marketing content generationAI knowledge assistantFigure 11:Use of AI along the value chainProductionResearch and developmentCustomersCompanyUseReturn of vehicleInspection of vehicles and componentsRecyclingPredictive maintenance and quality controlAI-supported sorting systemsSupply chain monitoringProcurement and materialsSales and marketingCode generation324040606080801001002020overalloveralloveralloveralloverall%Figure 12:Significant improvements of functions and features through AI n=4.711overalloveralloveralloveralloverallHighly automated and autonomous driving(e.g.driving on the freeway without hands on the steering wheel)Personalized driving experiencesPredictive maintenanceVehicle developmentProductionNothingDriver assistance systems(e.g.adaptive cruise control,lane departure warning,emergency brake assistant)Personalized enter-tainment and info-tainment contentIntelligent route planningVirtual assistant in car37.540.127.639.635.535.536.134.739.936.741.823.427.937.537.236.650.934.533.649.034.829.329.325.113.11.626.725.221.015.119.531.427.130.329.026.931.932.432.145.9AI can be used in various parts of a vehicle and along the entire value chain.All departments in a company that is active along the value chain in the automotive industry can benefit from the use of AI applications.Up to now,it has been observed that the industry re-mains skeptical about the benefits of AI applications.In April 2023,companies from various sectors were asked whether the advantages of using AI models outweighed the disadvantages.Unsurprisingly,most of the high-tech companies(84 percent)thought the advantages outweighed the disadvantages.What is surprising is that the automotive industry is the least convinced.Only 66 percent of the companies surveyed said that the advantages outweighed the disadvantages.The opinion of drivers is also a factor.Our global survey shows one thing very clearly:Consumers see signifi-cant potential for improvement through the use of AI.Especially in China,it is assumed that driver assistance systems,highly automated driving,and a personalized driving experience will be enabled or improved by AI.Globally,intelligent route planning and virtual assis-tants are also highly rated.What do you think can be significantly improved,or even made possible at all,by AI?Multiple answers possible33AI as Game Changer|05.AI Applications Along the Automotive Value Chain40608010020overalloveralloveralloveralloverall%Highly automated and autonomous driving(e.g.driving on the freeway without hands on the steering wheel)Driver assistance systems(e.g.adaptive cruise control,lane departure warning,emergency brake assistant)Personalized entertainment and infotainment contentIntelligent route planningVirtual assistant in car40608010020%overalloverallPersonalized driving experiencesPredictive maintenanceFigure 13:Interest in AI functions compared internationally n=4.711What AI functions would you be interested in for your next vehicle?Standard equipment or moderate extra charge specified62.770.775.764.870.274.390.963.892.078.964.778.469.163.860.790.675.370.793.557.058.090.855.375.472.694.252.691.2More thanof respondents in China express a high level of interest in AI functions.34Legacy Onboard Legacy Onboard and CloudKI Onboard and AI-CloudNever connected Implemented offline functionsImplemented offline functionsEmbedded AIConnected/onlineConnected/onlineAPIAIAIAPIFigure 14:Role of on-premise,cloud,and vehicle for AI models5.1 AI Operation in Vehicles and in the CloudA distinction must be made between training and ap-plication or inference.In most cases,the models are trained in cloud environments.Individual companies,such as Tesla,have started building their own super-computers so they can develop models on-premises.Our survey shows that customers are mainly interested in functions relating to driver assistance systems,intel-ligent route planning,and predictive maintenance.It is also clear that interest in the different functions is much higher in China.More than 90 per cent of respondents show an interest in AI functions.For use cases implemented in-vehicle,proprietary com-puter hardware may be required as security-critical as-pects and connectivity requirements limit cloud solu-tions.The integration of large language models(LLMs)in vehicles paves the way for personalization,but there are technical challenges.Because of their size,LLMs are typically deployed in the cloud,which impacts interac-tion and performance.A local version that runs in the vehicle itself enables more seamless integration,faster responses,and a better user experience.Sufficient computing power is required for securi-ty-critical,high-performance AI applications in cars.For AI-supported driving functions like ADAS and NOA,processing capacities of up to 1000 TOPS and more are required.Car manufacturers use high-performance computers from firms such as NVIDIA,Black Sesame,Qualcomm,and Ambarella for these functions.For less critical applications,a cloud solution can be used,or a hybrid solution.With a cloud solution,the processing of queries and information takes place in the cloud and the results are communicated to the vehicles.5.1.1 Software-Defined Vehicles and AIAI enables new functions and USPs,which car man-ufacturers use to impress.The concept of the soft-ware-defined vehicle plays a key role here.The SDV is the evolution from a car based mainly on mechanics and hardware to a car that is primarily controlled elec-tronically and dependent on software.By decoupling software and hardware,new functions and software updates can be developed and implemented quickly and continuously throughout the entire service life of the vehicle.The SDV levels are a prerequisite for the scalable use of AI.At the vehicle hardware level,sufficient computing ca-pacity must be available so that AI applications can be implemented in the vehicle.AI applications are used in the digital living space.Virtual assistants are implement-ed in the intelligent cockpit,and the automated driving functions are also used at this level.35AI as Game Changer|05.AI Applications Along the Automotive Value ChainFigure 15:Levels of a software-defined vehicle(SDV)(Willand,Friedel,&Schaupensteiner,2023)DigitalcockpitIn-car softwareand featuresContextual intelligence(location,AI)Cloud solutionsHolisticUI/UX Differentiating software Brand building Customer needs Non-differentiating software Increase standardization Economies of scaleVehicle software(Car.OS)Vehicle hardware(sensors,high-performance-computer)EV skateboard(battery,drivetrain)Digital living spaceHardware platform&car OS Software-defined vehicleSoftware-defined vehicles as a game changer and enabler for competitive vehicles5.1.2 AI Enables Automated Driving Without AI,there will be no autonomous vehicles or highly automated driving functions.The use of AI enables the introduction of ADAS and,later,also AD(automated driving)functions.End-to-end neural net-works are often used for ADAS functions.Companies such as Tesla and XPeng are among the leaders here.At XPeng,the end-to-end model consists of at least three different models.One model is responsible for environmental recognition and another model for the planning and ongoing optimization of driving maneu-vers.An additional LLM is relevant for learning and comprehension capabilities.In the automotive industry,two different strategies are apparent.Companies such as Tesla,XPeng,and Nio are pursuing a vertical strategy.They develop and im-plement most levels of the AI applications themselves.Other manufacturers have chosen a horizontal strate-gy.They use suppliers instead of developing AI models and applications themselves.The system at XPeng has been trained based on 1 bil-lion kilometers of video material,6.46 million kilome-ters of real-world testing,and 216 million kilometers of simulation testing(XPeng,2024).The models are trained in a cloud infrastructure operated by Alibaba.It has a capacity of 600 PetaFLOPS(Data Centre Dy-namics Ltd,DCD;2022).36Figure 16:Different models for ADAS and AD applications and functionsFunctions in autonomous drivingModalityFoundation models for AV Perception Video Generation and World Model Unified Perception and Planning Visual Understanding and Reasoning Planning Trajectory Prediction Simulation and Testing User Interface and PersonalizationLarge language modelsVision foundation modelsMulti-modal foundation modelsMany ADAS and AD functions are based on different foundation models(also called modalities,Figure 15)and combine these.For example,large language mod-els are used to train or simulate the models.Vision foundation models process large quantities of video material and enable new perception functions.Mul-timodal models work with text,images,audio,and video signals and plan driving routes or facilitate quick decision-making.5.1.3 AI Enables Personalized AssistantsLarge language models are used in the cockpit to im-prove the customer experience and make new func-tions possible.Personal assistants,where the AI is built directly into the vehicle,are becoming more efficient and effec-tive.The latest iterations enable smart reasoning and smart scheduling features.For instance,the occupant of the vehicle can say they feel too cold and the vehicle responds by adjusting the air conditioning.AI appli-cations also make it possible,for example,to request information from the vehicle manual and have this presented as audio-visual output.A crucial aspect is ensuring the human-machine in-terface receives sufficient attention.It is not primarily about putting AI applications in vehicles from a tech-nological or product perspective.What is important is 37AI as Game Changer|05.AI Applications Along the Automotive Value Chainimplementation in a way that results in a high level of customer acceptance.The overriding objective should be to make the use of the functions feel natural,famil-iar,and human,thus ensuring continued use.If inte-gration is too technical without adequate investment in the interfaces between people and machines,AI may end up being rejected.One ambitious example is the Q6 e-tron.With this series,the Volkswagen Group brand Audi has intro-duced a self-learning digital assistant that understands over 800 voice commands and can respond to them.This is made possible through the use of natural lan-guage processing and deep learning models(CARIAD,2024).Many car manufacturers are working on anthropo-morphizing AI assistants so that they exhibit human behaviors and traits,such as the ability to recognize emotions and respond to them.A further step towards anthropomorphism is the in-tegration of facial recognition technology,which en-ables the assistant to visually identify the driver and analyze their emotions.Anthropomorphism goes be-yond simply imitating human characteristics and may also include adapting to cultural and regional differ-ences.Toyota is developing AI systems that are able to understand regional dialects and take local charac-teristics into account in communication.In Japan,for example,an assistant could speak more formally and bow respectfully(in the form of an animated avatar),while in the US a more relaxed and humorous commu-nication style is used.5.1.4 Further AI Applications in Vehicles and in Customer InteractionIn addition to the applications described here,AI ap-plications can also be used in the following domains in order to improve results and experience for customers.Customer/driver experience Personalization:AI analyzes customer data to cre-ate personalized experiences that boost customer loyalty.Anthropomorphism:The aim of humanizing AI is to develop assistants that not only respond to commands but are also able to hold conversations,recognize emotions,and respond appropriately.Intelligent traffic data analysis:AI uses data to opti-mize multimodal mobility and improve traffic man-agement.Predictive maintenance:AI models enable dynamic predictions for the purpose of detecting anomalies at an early stage and taking countermeasures.Marketing and Sales Automated customer interaction:Chatbots and vir-tual assistants improve customer service by dealing with routine inquiries.Other in-vehicle AI applications that are enabled by AI and generative AI technologies:Visualization of surroundings and driving situations Safe environment recognition:AI analyzes the sur-rounding environment and shows the systems con-fidence in identifying objects and situations.Automated driving functions:Visualization of auto-mated driving functions to make the vehicles deci-sions clear to the driver.AR HUD:The augmented reality head-up display projects information directly into the drivers field of vision.Visualization of parking situation:Visual aids and sensors provide support when parking.Visualiza-tion of vehicle position and movement.Extended rear view with AI-supported object recognition.Sensors and convenience Optimized gesture control:Recognition and inter-pretation of hand gestures to control vehicle func-tions.Facial recognition in video conferences:Online meetings in the vehicle with facial recognition and tracking.Gaming:In-vehicle games with AI-supported graph-ics and interaction.Improved safety Interior monitoring:Observation of the vehicle in-terior for the detection of activities and conditions.Environment warnings:Warning about approach-ing objects or people when the doors are opened.Child left alerts:Detects whether a child has been left in the vehicle.General monitoring:Vehicle security check with AI-supported analysis.38Some of the functions mentioned can also be used in the vehicle without generative AI,but only to a fixed extent which was trained before use.Formerly rule-based functions are taken to a new level through AI models.The comprehensive AI features of LLMs drasti-cally increase the scope of the functions.5.2 AI Monetization in VehiclesThe monetization of AI applications in vehicles will be a relevant issue in the coming years.Here,companies can use MHPs Business Model Framework to assess the business potential of AI applications.Custom-er-centered use cases are developed and financially evaluated based on market and competition and also customer requirements.Consideration of the value chain helps with the make-or-buy decision for indi-vidual stages of the value chain.The direct monetization of ADAS functions is set to be a lucrative market.However,the direct monetiza-tion of AI applications for personal assistance over the lifetime of the vehicle is regarded as a challenge.In addition to direct monetization,companies should also consider indirect options.The information and data obtained through AI applications can be used to continuously optimize products and services.Quality as perceived by the customer is improved,and prod-ucts and services can be tailored personally to them.This influences purchasing decisions and increases loyalty and customer retention.Another important aspect is the role of partnerships and ecosystems.Car manufacturers could tap into additional monetization opportunities through col-laboration with technology firms,software develop-ers,or data providers.This could not only generate new revenue streams but also reduce development efforts and accelerate innovation.Examples of approaches for monetizing AI applicationsDirect monetization of functions(pay-per-use or subscriptions)One of the most obvious methods is direct payment for AI-based functions:Manufacturers offer auto-mated driving,ADAS functions,and more as addi-tional options which the user activates with a one-off payment or a subscription.Features can be activated after purchasing the vehicle,thus generating addi-tional revenue during the lifetime of the vehicle.Direct monetization via subscription modelsManufacturers provide access to certain AI services(e.g.personal assistants,entertainment/information services)as part of a subscription model.Users pay monthly or annually to access special functions or updates.This way,manufacturers establish a steady revenue stream.Indirect monetization:data-based business modelsCompanies obtain valuable insights by using and an-alyzing the data generated in the vehicle.For exam-ple,data relating to driving behavior can be used to develop personalized insurance quotes(usage-based insurance).In addition,anonymized data can also be sold to third parties,e.g.for improving traffic man-agement systems or further developing smart cities.Indirect monetization:personalized services and advertising AI can improve the user experience through person-alized recommendations and advertising.In-car com-merce(e.g.ordering products directly in the vehicle)or targeted advertising based on the preferences and driving behavior of the user could also become a source of income.Indirect monetization:market places and third party integrationCar manufacturers can create open platforms on which third party providers offer their own AI-based applications.These platforms could be similar to app stores for smartphones,with the vehicle manufac-turer receiving a commission for the apps or services sold.Indirect monetization:improved customer experiences and servicesAI-supported vehicle diagnostics and predictive main-tenance help to optimize vehicle maintenance and detect problems at an early stage.Manufacturers can offer special premium services for this that go beyond standard maintenance plans.Remote diagnostics or updates could also be offered for a fee.39AI as Game Changer|05.AI Applications Along the Automotive Value ChainAIs potential for innovation and value creationFigure 17:AIs potential at different stages of the value chain(Capgemini,2023)67%LogisticsProductionResearch and developmentMarketing,sales,customer serviceIT and software development5211%9%5.3 Added Value of AI Applications in CompaniesAI applications can not only revolutionize the cus-tomer experience but also unlock potential within the company in the various divisions.The biggest potential within companies is in the IT segment.AI applications can help with developing software innovations,writing code,or automating testing and quality management.Two thirds of the companies state that the biggest opportunities are in this area.Great potential is also seen in marketing,sales,and customer service this can be unlocked through the use of AI applications.Around 50 percent of respon-dents believe that these segments are positively im-pacted by AI.The approach to customers can also be improved if customer data and other information can be used to deliver personalized marketing cam-paigns.AI-supported chatbots can also positively im-pact on the user experience and increase the amount of self services thus reducing costs.Payment service provider Klarna shows the poten-tial here.Its AI applications do the work of around 700 full-time customer service employees.Satisfac-tion ratings are on a par with those for responses produced by employees.The rate of repeat inquiries has been reduced by 25 percent,and the AI applica-tions are also able to communicate in 35 languages (Cerullo,2024).No information is provided about possible cost reductions,but it can be assumed that the business case is positive.After IT and the creative fields come the value creation stages of research and development and production.Around two thirds of respondents see these stages as having relevant potential to generate innovation and create value with the use of AI(Capgemini,2023).Interestingly,companies see only limited potential for AI in logistics only 9 percent see opportunities for innovation and added value in this segment.5.3.1 AI in the Manufacturing Industry and in Car ProductionThe use of AI in manufacturing processes is increas-ing.Chinese companies are far ahead of their global competitors here,in some instances integrating AI-based solutions into their production processes more than twice as often as the competition.Aspects in-cluding cultural acceptance and political support can be seen as possible drivers of this impressive progress(Herf,Hager,&Schreiber,2024).In the DACH region,20 percent of companies use AI-based solutions in manufacturing processes,compared to 46 percent in the US and an impressive 94 percent in China.What impacts do companies expect AI to have in manufacturing processes?Some 60 percent expect high to radical future impacts.Only 13 percent of re-spondents believe impacts will be negligible to low.The reasons for the use of AI in production can be traced back to the drivers of every business activity:Lower costs,higher efficiency,and higher quality are the key motives which,from the point of view of the companies surveyed,are driving the use of AI in pro-duction.40DACHChinaUSUKNoYesDont know20F)pFX%6%8%0%Does your business use AI-based solutions(e.g.predictive maintenance,detection of anomalies,autonomous robots)in production processes?Figure 18:Use of AI-based solutions by regionAI can make production in the car industry more efficient in various ways,such as:1 Process optimization:AI can help to optimize processes in production by analyzing data and identi-fying patterns in order to increase efficiency.2 Quality control:AI can help to monitor and im-prove the quality of the vehicles produced by analyzing data from various sources and identifying anomalies.3 Predictive maintenance:AI can help predict and plan the maintenance of machines and systems with the aim of minimizing outages and downtime.4 Automation:AI can help to automate processes in production by controlling and monitoring robots and other machines.5 Supply chain optimization:AI can help to optimize the supply chain by analyzing data and identifying pat-terns in order to increase efficiency.41AI as Game Changer|05.AI Applications Along the Automotive Value ChainIn your opinion,what are the most important factors that will drive forward the use of AI in production?Operational efficiency and lower costsHigher quality12%Greater flexibility8%Greater reliability11%Figure 19:Key drivers behind the use of AI in production n=4.7115.3.2 Self-Learning Humanoid RobotsA relevant use case is AI use in robotics.Humanoid robots based on an AI model are being developed by various start-ups.Developments at Tesla are causing a stir.The electric car maker is working on a robot called Optimus.It is expected to be operational in the next few years and be sold to external customers.German car manufacturer BMW Group has signed an agree-ment with the company Figure,and Mercedes-Benz is testing humanoid robots from Apptronik.The narrative is clear.The use of humanoid robots can ensure greater efficiency and also provide a solution to the shortage of skilled workers.The refinement of AI models has ensured that human-oid robots are experiencing a step forward in devel-opment.Humanoid robots,which look and move like humans,need AI models for a number of important reasons.These models enable the robots to understand,learn,and perform complex tasks which otherwise re-quire human skill and intelligence.Case study:BMW iFACTORYAt BMW,new technologies are being used in the iFACTORY,including AI applications.It is important to understand that AI is only a part of the solution and other enablers need to be available too.Some of the most important factors:Digitalization of production to boost efficiency and reduce costs Artificial intelligence to optimize production and boost efficiency Interconnection of all relevant aspects of production to boost efficiency and reduce costs Flexibility to adapt to the needs of customersExamples of increased efficiency:25 percent efficiency gain in production 200 AI applications to optimize production and boost efficiency Interconnection of 31 sites in 15 countries to boost efficiency and reduce costs42Figure 20:Decisive issue fewer users of software due to AI or free software(Coatue,2024)Battleground Debate:Is Software an AI Loser or Winner?Will AI shrink the labor force and pressure seat-based monetization?If AI drives cost of coding to zero,why buy software vs.build your own?Seat-based model deadCode no longer a software moatPricing:Consumption&Value BasedData is KingWork-flowKnowl-edge GraphAction for Software FoundersAI Implication for Soft-wareAI Threats for SoftwareSoftware Founders are you AI ready?Humanoid robots must be able to work in diverse and dynamic environments.AI models,particularly those based on machine learning and neural networks,en-able the robots to learn from experience and adapt to new situations.5.3.3 AI in Software Development AI applications can be used in many areas of software development.The impact of AI in this field is currently being discussed as a controversial topic.On the one hand,the argument is that the use of AI reduces jobs.The focus is on office jobs that rely on computers and software.Fewer staff here would have an adverse im-pact on Software-as-a-Service business models.On the other hand,there is discussion around wheth-er the use of AI could reduce software development costs to virtually zero.It could then be cheaper for businesses to develop software with AI themselves instead of buying expensive licenses or using SaaS ap-plications.The automotive industry would be among those who would benefit from this development.Rel-evant skills,data pools,and processes should there-fore be thought through and set up,if necessary,in order to be AI-ready.Until then,AI applications can be used along the value chain for the development of software relating to cars and software-defined vehicles.An AI-enabled copilot can help to compile the require-ments from unstructured and dispersed documents and document them in a uniform way.A consistent and thorough check can be carried out with the AI tool.Other AI tools can help developers write,document,or test software code.AI applications can also be used for bug fixing.They can be used for cyber security and safety,with the aim of preventing security gaps and attacks throughout the lifespan of the software.Here again,it is becoming clear that there are diverse possibilities for the use of various AI applications.43AI as Game Changer|05.AI Applications Along the Automotive Value ChainFigure 21:Possible uses of AI in software development(Wee 2024)RequirementsAgentI can help to extract requirements from unstructured documentsAutomotive Software Defined Vehicle(SDV)ToolchainDevelopmentand Testing AgentI can help to generate,explain,test,and bug fix software code documentsSecurityAgentI can prevent security problems at every stage of the SW lifecycleSoftware artifactsDevelopment ToolsDevelopment,Validation andIntegrationEnvironmentRequirements&ArchitectureSoftware Telemetry,Logs,Metrics,Traces,Behavior GenAI use cases alongside the SDV toolchainBuildTestDevelopmentHardware-in-the-Loop(HiL)Vehicle Security Operations Center(VSOC)TestFleetsCustomerVehicles44Building relevant knowledge,gaining experience,and continuously refining and implementing AI applica-tions in the software development field can make a difference.7.3.4 Other AI Use Cases in CompaniesThe use cases described above can be further expand-ed in a range of business areas:Procurement and supply chains Contract management:AI-supported software can automatically scan and analyze contracts to identify potential savings.Supplier risk management:AI monitors potential risks in the supply chain and sends warnings if there are problems.ESG data management:Automated generation,validation,and processing of ESG data;this includes CO2 data,in particular Scope 3 upstream emissions.-Purchasing automation:AI can automatically check and approve orders,making the purchasing pro-cess more efficient.AI can help with automated text generation for sus-tainability reporting.AI analyzes market trends,consumer behavior,and logistic variables in order to precisely predict de-mand and optimize supply chains.Enterprise IT IT support and helpdesk automation:AI automates the categorization and processing of support re-quests,thus boosting efficiency.Cyber security:AI monitors networks and detects threats in real time in order to minimize security risks.Manufacturing/operations Process optimization:AI helps to predict system er-rors and optimize production processes.Intelligent algorithms optimize the energy con-sumption of production facilities,leading to more environmentally friendly solutions.Optimization of production output:AI adapts pro-duction parameters in real time and responds to changes,thus guaranteeing consistently high effi-ciency.Improved quality management:Machine learning models continually refine inspection processes,re-duce human error,and increase throughput.Cost-efficient maintenance:Intelligent systems opti-mize maintenance plans,avoid unnecessary checks,and deploy resources exactly where they are most urgently needed.Predictive analyses and machine learning identify patterns that could lead to malfunctions.This en-ables predictive maintenance and minimizes un-planned downtime.Research&development,engineering Product development:AI analyzes data from ex-periments to accelerate product development and lower costs.Error detection:Automated visual inspection tools detect manufacturing defects faster and more ac-curately than the human eye.AI-supported simulations and generative design software shorten the development cycle and make new concepts market-ready faster.Development of customer-focused products:With the aid of AI,field data and customer feedback can be used to derive specific requirements for products and services.Customer-specific offerings can boost selling opportunities and sales.Marketing,retail,sales/after-sales Inventory management:AI predicts future buying trends with the aim of optimizing stocks and reduc-ing waste.Price optimization:AI analyzes market trends and buying behavior in order to dynamically adjust pric-es and maximize profitability.In short,the possible applications for AI are diverse and can be maximized through a combinatorial anal-ysis of difference technologies and use cases.In the next few years,we expect further sustainable applica-tions to emerge that are not yet known to us today.45AI as Game Changer|05.AI Applications Along the Automotive Value Chain4606.What the Customer Wants:The User Perspective47AI as Game Changer|06.What the Customer Wants:The User Perspectiveof respondents in China have an understanding of AI in carsof respondents in Europe have an understanding of AI in carsMore thanOnly40608010020%Yes,I have an ideaNo,not reallyYes,more or lessNo,I have no ideaIntermediate total:Yes,I have an idea/yes,more or lessIntermediate total:No,not really/no,I have no ideaNo informationoveralloveralloveralloveralloveralloveralloverallFigure 22:Understanding of AI in carsUnderstanding of artificial intelligence in cars22.816.623.737.138.637.134.246.561.328.433.431.438.346.041.615.80.40.30.50.613.09.912.610.22.853.757.983.64840608010020overalloveralloveralloveralloveralloveralloverallFigure 23:Advantages of using AI in carsWhat do you think the advantages are of using artificial intelligence in cars?Multiple answers possibleG.244.338.862.942.639.135.635.132.021.518.420.420.434.738.452.939.047.031.160.541.352.740.138.638.124.215.11.5More efficientdrivingGreater safetyGreater comfortBetter main-tenanceMore personal-izationLower costs for usersDont see any advantageHow familiar are end customers with AI applications?What are drivers expectations?A recent survey by MHP with more than 4,700 respondents provides an-swers.We carried out the representative population panel survey in China,the US,Germany,the UK,Italy,Sweden,and Poland.6.1 Use and Understanding of AI ApplicationsThe overall conclusion is that around 90 percent of respondents say that they know what is understood by artificial intelligence in general.This shows the high relevance of the topic.However,based on the survey,no conclusions can be drawn about the depth of AI understanding.What is surprising is that the general understanding of AI is at a consistent level across Europe,the US,and China.The situation regarding in-car AI shows a different picture:In total,only 60 percent of respon-dents state that they understand the use of AI in cars.There are also global differences when it comes to this question.In China,more than 80 percent of respon-dents have an understanding of AI in cars,whereas in Europe this figure is only 53.7 percent.When respondents were asked whether they had ever used AI functions in a car,a clear picture emerges.In China,almost three quarters of respondents have used an AI function in a car,while in Europe this figure is just 31 percent.Overall,50 percent of respondents from the US said they had already used an AI function in a car.6.2 Advantages and Disadvantages Generally and in VehiclesAccording to our survey,two general advantages of AI receive a high approval rating of more than 40 per-cent.Across all regions,51 percent of respondents rated time-saving as the biggest advantage.Gaining a similarly high score is the aspect of increased efficiency and productivity 43.7 percent see this as an advan-tage.Other advantages such as increased creativity,improved safety,or better decision-making were only rated from 26.6 to 29.3 percent.It is striking that the ratings in China are positive for most of the advantag-es asked about.Time-saving is ranked at a relatively similar level worldwide;the other advantages in the survey are affirmed much more frequently in China compared to the US and Europe.With regard to dis-49AI as Game Changer|06.What the Customer Wants:The User Perspectiveoveralloveralloveralloveralloveralloveralloveralloveralloveralloverall4040606080801001002020ta protection and personal privacyGreater risk of incor-rect informationSafetyrisksLoss of controlReliability of the technologyInfluence on formation of opinionHigher costs for usersDont see any disadvantagesOther disadvantageTime savingsGreater efficiency and productivityIncreased creativityImproved safetyPersonalized experiencePersonalized entertainment AI-assisted personalized content creationBetter decision-makingDont see any advantagesOther advantage Advertising tailored to individual needs/customized advertising/environment(e.g.AI controlled virtual perimeter advertising in sport)What do you think the advantages and disadvantages are of using artificial intelligence in general?Multiple answers possibleAdvantagesDisadvantages51.049.246.745.944.034.433.127.32.08.37.56.711.82.32.60.631.233.634.139.624.323.734.928.643.047.149.047.248.548.526.650.140.155.853.534.248.143.729.329.128.826.726.620.60.815.218.820.50.91.20.20.923.925.434.515.518.735.153.238.543.256.923.326.124.928.340.322.528.744.521.526.540.147.446.450.4Figure 24:The perceived advantages and disadvantages of using AIn=4.7115040608010020overalloveralloveralloveralloverall%Would buy the car because of themWould buy the car because of them and would also be prepared to pay a moderate extra chargeWould neither encourage nor deter meWould deter me from buying itDont knowIf AI functions were integrated into a vehicle,would you be more likely to buy the car or would they perhaps even deter you from buying it?29.624.925.944.925.024.227.330.010.412.014.312.712.83.010.310.62.022.816.538.8Figure 25:AI in cars:purchase motivation or blocker?n=4.711advantages,respondents from the US are most likely to express their concerns.Risks for data protection and personal privacy,a greater risk of incorrect informa-tion,and security risks are mentioned by 45.9 to 49.2 percent of respondents from all regions.When broken down into car and mobility,advantages and disadvantages are also seen and classified accord-ingly.The biggest advantage is for efficient driving 47.2 percent believe that AI ensures progress in this area.In second place with 42.5 percent is increased safety,followed by greater comfort with 40.1 percent.It is noteworthy that respondents from China show significantly higher approval with regard to the advan-tages.The lowest ratings were found in the US.With regard to the disadvantages associated with the use of AI in cars,aspects including safety risks,data protec-tion and personal privacy,and possible loss of control received the highest ratings.6.3 Purchasing Decision,Trust and Willingness to PayIn the survey,respondents opinion on the impact of AI on the purchasing decision was also evaluated.It is clear that it is mainly respondents from China who would be likely to buy a car with AI functions.Some 45 percent stated that they would be likely to buy a car due to its AI functions;only 2 percent said AI functions would stop them from buying.The picture is different in Europe and the US.Only 25 to 26 percent would buy a car because of AI functions,and 12 to 14 percent said they would be more likely not to buy a car due to implemented AI functions.In China,the ratio of“likely to buy”to“would stop me from buying”is therefore around 22:1;in Europe and the US,this is closer to a ratio of 2:1.There is a significant advantage for vehicle manufac-turers who have been in the market for a long time.When it comes to the use of AI applications,respon-dents stated that they would place the most trust in car manufacturers with a long history.In China,this group gets the most approval,while in the US it gets the least.After car manufacturers,it is technology companies like Apple,Baidu,Google,and Tencent who are the most trusted regarding the use of AI applications in the au-tomotive sector.In the US,trust is almost at the same level as trust in traditional car manufacturers.New car manufacturers who have only been in the market for a few years still need to acquire this trust.Only in China is a high level of trust shown in these companies.The willingness to pay for AI functions varies around the world.What is striking is that most of the respondents 51AI as Game Changer|06.What the Customer Wants:The User Perspective4040606080801001002020overalloveralloverallr manufac-turers who have been in the market for a long timeTechnology companies(e.g.Apple,Google,Microsoft)Car manufac-turers who have only been in the market for a few yearsState institutionsStart-up companiesOthersFigure 27:Willingness to pay for AI functions Base:all participants,n=4.711overalloveralloveralloverall63.550.326.313.810.66.30.2710.69.712.410.963.455.272.244.754.260.420.925.640.611.823.69.1Figure 26:Trust in stakeholders with regard to the implementation of AI in vehicles n=4.71177.311.88.12.878.310.87.83.067.318.19.84.9Immediately after purchaseActivate later Activate later Flexible monthly use No willingness to pay/no informationImmediately after purchaseActivate later Activate later Flexible monthly use No willingness to pay/no informationImmediately after purchaseActivate later Activate later Flexible monthly use No willingness to pay/no informationImmediately after purchaseActivate later Activate later Flexible monthly use No willingness to pay/no information13.08.475.33.3Which stakeholders would you trust regarding the use of artificial intelligence in the vehicle sector?Multiple answers possibleYou have indicated that you would be prepared to pay a moderate extra charge for the following AI functions.In what way would you like to use the function?52 Chinese manufacturers USmanufacturersAsian manufacturers(excluding China)European manufacturers%OEMs from China are most often considered to have expertise;European OEMs need to prove their expertise“Which of these car manufacturers do you think will have particular expertise in AI technologies in five years time?”10203040500Figure 28:Assessment of the future AI competence of car manufacturers by regionn=4.711are not prepared to pay for functions.Should the cus-tomer accept an additional charge,it is most likely to be when purchasing a vehicle.Monthly flexible payments are the least popular(function on demand).To conclude,it can be said that the opportunities out-weigh the risks when it comes to implementing AI.As can be deduced from the individual questions,the attitude to AI is much more positive in China than it is in Europe or the US.Overall,47.5 percent of the respondents from China said that the opportunities outweighed the risks;only 3.6 percent said the risks outweighed the opportunities.By comparison,23.4 percent of the respondents in Europe considered the opportunities to outweigh the risks,while 20.1 percent said the risks were higher.In the US,25.2 percent see more opportunities,and 23.7 percent see more risks.Our tip:Companies should be aware of these global and regional differences and align and im-plement their strategy accordingly so that they are able to respond in a targeted way to customer concerns and expectations.Which car manufacturers do users think currently have the greatest AI expertise?The outlook for the next five years provides a clear picture in favor of Chinese OEMs.Europe and thus Germany lag behind at least in the perception of potential customers.53AI as Game Changer|06.What the Customer Wants:The User Perspective5407.Success Factors and Strategic Approach55AI as Game Changer|07.Success Factors and Strategic Approach56Many success factors are relevant for the long-term successful use of AI applications.In addition to the pure hard facts like data availability,hardware,and sustainable distribution/use,it is primarily strategic and organizational levers that are crucial.7.1 Strategy and Goal PlanningIn order to successfully introduce and operate AI appli-cations,a clear overarching strategy is required from which specific strategies can be derived for the indi-vidual departments and segments.The strategy pro-cess should begin with a review,preferably involving relevant stakeholders and interest groups,in order to achieve the highest possible level of approval and identification.In addition to the internal review,a mar-ket and competition review is critical to assess the di-rection in which the market is moving and what the competitive situation looks like.Based on the reviews and analyses,the strategic North Star can be developed,which can be quite ambitious.Here again,it is advisable to include the various stake-holders and interest groups in order to gain a collective picture that can be firmed up with clear goals and tar-gets.Division into relevant modules reduces complexi-ty and makes control easier.The following criteria are crucial for implementation of the AI strategy:The strategy must be supported by management;the commitment of management determines suc-cess or failure.The responsibilities must be clearly defined and lived in practice.Sufficient freedom must be created in order to be able to assume responsibility.KPIs:Defined metrics measure the impact of AI ini-tiatives on operational performance.ROI measurement:Frameworks measure the return on investment of AI projects,thus ensuring tangible value.The strategy should be designed for the long term;acting without proper planning and short-term thinking will not lead to success.Because the field of AI applications is highly com-plex and dynamic,the relevant expertise must be built up and further developed internally.Special-ized service providers such as MHP can be commis-sioned to accelerate entry and build up skills.We are at the start of the platform shift we are not yet in a stable phase,but in a dynamic market.The operationalization of the AI strategy must reflect this momentum and enable regular reviews.A robust strategy and genuine ownership of AI topics are essential for ensuring companies are successful.7.2 Think from the Perspective of the Customer,not the TechnologyTo maximize the likelihood of sustainable implementa-tion of AI applications,the customers problem must be known and described adequately.Companies should in-vest enough time in solving customer problems.A quote from Einstein serves as a guiding principle:Acting without proper planning should be avoided when it comes to introducing AI models,and demand will only be sustainable if a corresponding customer problem is solved.Ownership in the corporate culture:With ownership,stakeholders take responsibility for the development of an optimum product.They drive the success of the product forward,detect logjams and problems,and solve them.“If I had one hour to solve a problem,I would spend 55 minutes to define the(customer)problem.”(Albert Einstein)Firgure 29:Customer and use case first,and then AI applications and modelsFrom AI models firstcustomer and pain point firstUse CasesAI applicationsAI modelsAI modelsAI applicationsUse case with business case or positive cost-benefit balanceFigure 30:Dimensions for validating technical feasibilityAI dimensions for validating technical feasibilityDataDo we have access to all the necessary data?Is this data of the required quality?Is the volume of data sufficient?IntegrationCan it be reliably integrated into the IT?Can it be reliably integrated into the product?Are the necessary skills available for operation?InfrastructureIs there enough computingpower for the models?Is the infrastructure economically scalable?Are the required SW licenses available?ModelIs there a suitablearchitecture for the task?Does the model achieve the necessary performance?Can the model be trained and optimized?ComplianceAre there relevant legal restrictions?Is the AI decision-making process transparent?What risk level does the use case belong to?57AI as Game Changer|07.Success Factors and Strategic ApproachThe following steps can be used to define AI use cases:What hypotheses exist regarding the customer or user problem?Have the hypotheses been sufficiently validated so that a solution can be developed?Definition and assessment of the solution space.The solution space can consist of AI applications and also other solutions.If the problem is to be solved with AI,the appro-priate model and implementation must be defined.After implementation,continuous monitoring and fine-tuning,where applicable,are required.To describe use cases,the Business Model Canvas can be used(Wikipedia,2024).Based on the structured data and the procedure,the use cases can be described,discussed,assessed,and prioritized.Only then can a proof of concept be drafted which validates feasibility.7.3 Organizational Anchoring and OwnershipThe AI revolution needs clarity regarding responsibility and organizational anchoring.The introduction of AI applications is not a plug-and-play process that can be implemented with little effort.Waiting and copying is the wrong approach.Managers need to actively en-gage in the introduction of AI,define responsibilities,and further develop the organization.The Industry 4.0 Barometer(Herf,Hager,&Schreiber,2024)has shown that companies make slower progress in introducing industrial AI if they operate without a Chief Informa-tion Officer(CIO).This reduces digital progress and impacts competitiveness.From the findings,it can be concluded that also for the introduction of enterprise AI and vehicle AI,relevant decision-makers such as a Chief Technology Officer(CTO),Chief Executive Of-ficer(CEO),or Chief Information Officer(CIO)must receive the mandate for introducing and further devel-oping AI applications and must act on it.Companies in the automotive industry need to catch up when it comes to responsibilities and budgets for the implementation of AI applications(Capgemini Re-search Institute,2023).Only 30 percent of companies have a dedicated team and a defined budget for the introduction of AI applications.This figure is 74 per-cent in high tech sector;the average is around 40 per-cent of the companies.AI competencies must be continually developed in order to reduce external dependency.In the Industry 4.0 Barometer,around 70 percent of the businesses surveyed(Herf,Hager,&Schreiber,2024)said they commission external AI experts to make up for the current lack of AI skills.To enable the success of AI,in-novation-driven AI expertise should be combined with company or industry-specific knowledge.Businesses must choose an end-to-end,long-term,and strategic approach so that they can take own-ership of AI topics.The most important approach-es to ensure genuine ownership are:Clear governance structures Companies should create a clear governance struc-ture for AI in which responsibilities at management and technical level are clearly defined.This means that,in addition to central management for AI initia-tives,there should also be decentralized teams with responsibility in their respective departments.A Chief AI Officer(CAIO)or person in a similar management role can take over strategic direction and ensure that AI initiatives are consistently driven forward across de-partments.Integration into the corporate strategy AI must be embedded into the overarching corporate strategy rather than just being treated as a technolo-gy experiment.Companies should set clear goals for the application of AI;these must align with their core values and business goals.Key question:How does AI help us achieve long-term business goals?It is crucial to develop a roadmap for AI projects that seeks both short-term success and long-term transformation.Investment in talent and expertise Ownership of AI means not just relying on external advisors and partners,but also investing in internal ex-pertise.Companies should specifically appoint AI ex-perts and at the same time provide training programs to enable existing employees to work with AI technol-ogies.Ongoing training on dealing with AI tools and processes helps to retain and strengthen expertise in the company.Ethical guidelines and responsibility A company that uses AI responsibly must also take ownership for the ethical implications.This includes developing guidelines for the use of AI to ensure that issues such as data protection,fairness,transparency,and non-discrimination are considered.All AI applica-tions should align with company values.58Data ownership and infrastructure Possession and control of data is a key prerequisite for the development and application of AI.Companies must invest in the data infrastructure that allows them to collect,store,and process data effectively.This in-cludes creating data silos and secure storage solutions,and establishing data management practices.Com-panies that take ownership also ensure a sustainable data strategy in which data quality,data protection,and data security play a key role.Support research and innovation Ownership of AI also means continually investing in research and development.Companies should be able to develop their own AI solutions and not rely solely on ready-made third party solutions.A company with a long-term AI strategy invests in its own R&D depart-ments or in collaborations with academic institutions to achieve their own technological breakthroughs.Agility and no-blame culture AI projects often call for an experimental approach and an agile way of working.Ownership of AI also means establishing a no-blame culture in which innovation is supported and mistakes are seen as learning opportu-nities.Companies should be prepared to adapt and re-fine their AI initiatives,based on the findings obtained during development and implementation.Transparency and communication Companies must ensure that AI decisions and process-es are communicated transparently,both inside and outside the organization.This includes explaining the decisions made by AI systems,and demonstrating the added value of AI for various stakeholders.Through regular,open communication on progress,challenges,and successes in AI implementation,companies create trust among customers and employees.Build collaborations and ecosystems Ownership also means understanding and using eco-systems.Companies should invest in partnerships with AI providers,universities,start-ups,and industry orga-nizations.These collaborations help to ensure access to the latest developments,tools,and best practices and at the same time strengthen the companys own expertise and innovation potential.Sustainability and long-term value Companies that take genuine ownership make sure that AI solutions are sustainable and add value in the long term.This means that they not only use AI in the short term to increase efficiency,but also aim for sus-tainable business values.This includes implementing AI in such a way that it has positive ecological and social impacts.Overall,taking ownership of AI calls for extensive commitment at all levels of the compa-ny,from management to the operational teams.By investing in talent,technology,ethics,and innovation,companies can ensure that they benefit from AI in the long term and at the same time take full responsibility for its impacts.7.4 Local Differences require local SetupAs in the cloud computing segment,there will be no AI solutions that can be used globally.Car manufacturers will be required to source and implement local models.On the one hand,global providers of AI models will not offer their models everywhere due to regulations.On the other hand,some countries will impose strict regu-lations that prevent the use of global models.The for-mer is evident in Europe.Providers of AI models,such as Meta,have announced that the latest generation of models will not be rolled out in Europe for now(Kroet,2024).The latter can be observed in China.Providers such as Tesla need to build local structures because local legislation prohibits data transfer across national bor-ders.Alongside regional differences,the use case demands on AI models are relevant.As described above,there are many AI models that have been trained and optimized for various use cases.The appropriate capabilities and processes need to be developed and embedded so that they are able to respond to local conditions and select the right AI applications for the use cases and usage en-vironments.Identifying,evaluating,and selecting part-ners for the various layers of the AI systems becomes a core competency that companies must learn.7.5 Reducing Complexity The complexity of AI projects may pose a challenge for automobile manufacturers.Reducing the complexity of AI applications is seen as a success factor.To manage this complexity effectively,the follow-ing strategies can be used:1 Introduction of agile methods:Agile methods such as Scrum or Kanban can help to reduce the complex-ity of AI projects by breaking development down into small,manageable steps.59AI as Game Changer|07.Success Factors and Strategic Approach2 Modularization of AI systems:The modularization of AI systems can help to reduce complexity by dividing the systems into smaller,independent modules.3 Use of AI platforms:AI platforms can help to reduce the complexity of AI projects by providing a uniform in-frastructure for developing and operating AI systems.4 Involvement of AI experts:The involvement of AI experts can help to reduce the complexity of AI projects as they contribute their expertise and experience to the development of AI systems.5 Use of explainable AI methods:These methods can help to reduce the complexity of AI projects by making the decisions of AI systems transparent and understand-able.6 Involvement of data scientists:The involvement of data scientists can help to reduce the complexity of AI projects as they contribute their expertise in data analy-sis and interpretation.7 Use of AI tools and frameworks:AI tools and frame-works can help to reduce the complexity of AI projects by providing a uniform infrastructure for developing and operating AI systems.7.6 Use and Monetization of DataData is one of the most important elements of AI appli-cations without an extensive quantity of relevant data,the potential of AI applications cannot be exploited.Companies in the automotive industry have access to exclusive treasure troves of data which can be used for the respective applications in order to train their own AI systems.If the relevant data sets are missing,they can be obtained separately.The data sets of companies in the automotive industry may also be of interest to other market players.It is con-ceivable that the licensing of data streams could open up revenue potential for the companies.Below,we have listed some data sets that could be in-valuable to the automotive industry because they en-able the development and implementation of AI models that improve efficiency,safety,and the user experience.Automotive supply chain data:Data sets that contain information about prominent au-tomotive companies and their suppliers up to the sec-ond level(tier 2 suppliers)are essential for supply chain management.This data helps with planning,capacity analysis,performance monitoring,and supplier coop-eration.Production data:This includes information about the production of ve-hicles,e.g.production times,quantities,and costs.This data can be used for optimizing production processes and predicting production capacities.Vehicle test data:Data collected during the vehicle development and test phase,including vehicle simulations and crash tests,is valuable for improving vehicle safety and performance.Telemetry data:This data includes information on vehicle performance,driving behavior,and the state of maintenance.It is im-portant for predictive maintenance and improving ve-hicle safety.Sensor data:Data from onboard sensors such as LiDAR,radar,cam-eras,and ultrasound devices is essential for the devel-opment of autonomous driving technologies.These sensors continuously capture data about the vehicles surroundings and help to monitor and interpret other vehicles,pedestrians,road conditions,and traffic signs.Customer data:This includes information about customers,e.g.buying behavior,preferences,and demography.It can be used for developing AI models to predict customer needs and behavior.Market data:This includes information about the market,e.g.market trends,size,and growth.This data can be used to ana-lyze market opportunities and risks.607.7 Checklist for successful ImplementationThe following checklists can be run through to assess the viability of AI plans and implementation:Strategy and leadership commitment Are responsibilities for the data and AI strategies and their implementation clearly defined at man-agement level?How can potential for added value be identified and business cases prioritized in order to minimize risks and support the corporate strategy?Are sufficient resources provided to internally devel-op AI products and services and maximize the use of partners in the ecosystem?What measures promote the successful integration of AI in the business strategy?What steps can be taken to ensure that the AI strat-egy aligns with the companys long-term goals?Data and AI core How efficiently do the cloud platform and technolo-gy strategies currently support the implementation of the AI strategy?Are a company-wide data platform and effective data management and governance practices in place that meet business requirements?Will data science and machine learning teams be leveraged throughout the AI development cycle?Are security and data protection guaranteed in the data and AI infrastructure?What measures ensure the scalability of the data platform used?Talent and culture How is the strategy for developing data and AI competencies aligned with the companys goals?To what extent are data and AI competencies prioritized for managers,business partners,and employees?Can a holistic staff development approach be implemented in order to scale,differentiate,retain,and further develop AI talent(e.g.teams of ma-chine learning engineers,data scientists,experts,and data engineers)?How is a data and AI culture established in the organization?What training programs boost employees data skills?Can a culture of innovation and experimentation be encouraged?Responsible AI What is the company-wide framework for imple-menting responsible data and AI practices?How can a coherent and industrialized approach to responsible data and AI practices be taken through-out the entire lifecycle of AI models?Is the development of AI-related laws and directives systematically monitored?Is adequate preparation being made for future necessary changes?How are the ethical implications of AI applications checked and monitored?What measures ensure that AI models are free of bias and risks?61AI as Game Changer|07.Success Factors and Strategic Approach6208.Challenges,Responsibility,and Risks63AI as Game Changer|08.Challenges,Responsibility,and RisksModel training is becoming more and more expensiveTransformerLaMDAPaLM(540B)Gemini UltraTraining cost(in U.S.dollars log scale)Training computer(petaFLOP log scale)10K10K1000100K100K1M1M10M10M100M100M1B10B100BEstimated training cost and compute of select Al models.Source:Epoch.2023 I Chart 2024 Al Index reportBERT-LargeRoBERTa LargeLlama2 70BMegatron-Turing NLG 530BGPT-4GPT-3 175B(davinci)Figure 31:Training costs for AI models are increasing(Stanford University,2024)A number of obstacles stand in the way of progress on AI applications in the automotive industry.Firstly,factors relating to organization,decision-making,and corporate culture must be mentioned.Secondly,prog-ress is hindered by systems with a lack of technical maturity and insufficient digitalization and standard-ization,which sometimes make full use of data impos-sible.Current vehicles usually do not have sufficient computing capacity,and connectivity is not powerful enough to implement AI applications.8.1 Costs of Training and OperationThe training of models is a basis for the use of artificial intelligence.Ever more powerful hardware is required to train increasingly powerful models.According to the 2024 AI Index report,the cost for training the GPT-4 model was 10 times more than the cost for train-ing the GPT-3 model,increasing from approx.USD 10 million to USD 100 million.These costs have to be over-compensated for by corresponding sales.A conclusion for stakeholders in the automotive indus-try may be that building their own model would not pay off financially.Due to the high cost of training the models,usage fees will continue to be relevant and possibly rise.As a result,automotive companies have to reckon with the fact that up-front costs and usage costs will remain high.Because companies are break-ing new ground,the return on investment is some-times not clear.The success factors described above may help to minimize risk and uncertainty.In addition to costs for hardware,energy requirements increase and thus also energy costs.AI models that run in a cloud environment drive up the energy needs of hyperscalers like Google Cloud,Amazon Web Ser-vices,and Microsoft Azure.That impacts the compa-nies budgets and also means that their self-imposed sustainability targets can no longer be achieved in the planned timeframes.It can be assumed that the ener-gy costs will be passed on to customers.64We have access to very large,unstructured,and dynamic data for the analysis.We are able to acquire data with the right level of detail in order to obtain meaningful findings.DACHDACHUSUSUKUKChinaChina323834292 %3$%6%25%5 %8%6%Generally agree Agree Completely agreeFigure 32:Data availability and quality by region8.2 Data and Digitalization as a BasisThe primary pain point is inadequate data availability and missed digitalization.AI cannot function without these.While LLMs can deliver impressive results,a recognized challenge for them is the“hallucination”of respons-es.It is essential to ensure that AI systems are halluci-nation-free if they are to be used for security-related functions in vehicles and in the value chain.The quality of LLM results depends heavily on the quality of the input data.A systematic framework is essential in order to detect and rectify inaccuracies.Data must be curated and appropriate guidelines established.New techniques in todays market can identify confabulations arbitrary and wrong outputs by assessing semantic uncertain-ty and not individual word sequences.These methods help customers recognize when to exercise caution with LLM responses.8.3 Business Models and Cases for B2C and B2BThe development of AI business models and business cases creates specific challenges.Firstly,high invest-ment in various layers of the AI systems comes with uncertainty as to whether a sustainable business mod-el will emerge.In the case of B2C applications,it is therefore neces-sary to validate whether and under what conditions a positive business case is possible.All costs for im-plementing and operating the AI applications must be 65AI as Game Changer|08.Challenges,Responsibility,and Risksconsidered and assessed in relation to the possible rev-enue.Criteria such as customers willingness to pay,competitors offerings,and the quality of implemen-tation are decisive.Indirect potential is also part of the business case review.For virtual assistants,direct monetization is becom-ing increasingly unlikely because market players offer these features at no additional cost.Customers expect assistants as convenience and safety factors in their cars at no additional cost.In spite of this,investment in AI-supported assistants can be worthwhile,for ex-ample to improve the customer experience,increase loyalty,or demonstrate competitiveness.The insights gained through AI about customers and products can also be used to continuously improve the range of ser-vices and products.In the medium and long term,this can lead to sustainable results because the expecta-tions of users and customers are met more accurately.Generally speaking,companies can focus on three main principles in order to determine the price of AI features.Cost-based pricing Process:Offering(product,service)costs plus profit surcharge price Result:Product-oriented saleFigure 33:Customers willingness to pay is unclear;costs arise for implementation and operationCompetition-based pricing Process:Competitors(prices,offerings)position compared to competition price Result:Greatest competitive pressure,fight for market shareValue-based pricing Process:Competitors(prices,offerings)value-based benefit analysis from customers perspective price Result:Demand-driven offering,target costs depen-dent on priceIn the case of B2B applications,the modeling of busi-ness models and cases with other goals is required.This is about using AI to boost efficiency,reduce costs,and improve quality.In most cases,AI applications are intended to enhance or replace processes and proce-dures that have so far managed without AI.Accord-ingly,a before-and-after comparison is possible and useful to prove that the AI investment is value for money.CustomerOEMDifferent business models as a challengeCloud-InfrastructureAI featuresApplicationsIntegration&operationFoundation model66Operational value chainProcess automationDecision-makingBusiness area User acceptance Value creation Model choice Data source Feasibility ScalabilityRisk classificationKnowledge transferAI capabilityCustomersCompetitionCompanyInnovationAI classificationStrategyOrganizationData&AI Transformation DimensionenValue deliveryContent generationTechnologyDataProducts&servicesCustomer and market understandingMonetizationA general classificationGrouping of AI use case areas within the business model.Business modelBusiness added valueTOMPersonProcessFigure.34:Classification of AI use case categories and possible business models8.4 Ethics and ResponsibilityTo ensure that AI technologies are used responsibly for the common good,many car manufacturers have pro-duced a code of ethics.These vary depending on the company,but there are common principles and guide-lines.One example is the BMW Groups code of ethics which sets out seven principles covering the use of AI:1 Human agency and oversight:People should always have control over the decisions of AI applications.2 Technical robustness and safety:AI applications should be developed robustly and safely to avoid the risk of unintended consequences and errors.3 Privacy and data governance:The storage and pro-cessing of data for AI applications should ensure data protection and data security.4 Transparency:Decisions relating to AI applications should be explainable and transparent.5 Diversity,non-discrimination,and fairness:AI appli-cations should be fair and non-discriminatory.6 Environmental and societal well-being:AI appli-cations should promote the well-being of customers,employees,and partners.7 Accountability:AI applications should be imple-mented so they work responsibly.Another example is Continentals Code of Ethics for Artificial Intelligence,which contains similar principles(Continental,2020).The European Commission has also published ethical guidelines for artificial intelli-gence entitled Ethics Guidelines for Trustworthy AI.Overall,it is clear that car manufacturers and the in-dustry as a whole are making an effort to develop and implement ethical principles for the use of AI with the aim of ensuring AI applications are used responsibly for the common good.67AI as Game Changer|08.Challenges,Responsibility,and RisksFigure 35:Risks associated with the use of AIGenerative AI risk assessmentGenerative AI risksData protectionData breachesInsufficient anonymization Unauthorized disclosur
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E-fuels:Evaluating the Viability of Commercially Deploying E-fuels in Road TransportNOVEMBER Sustainabilityis our business.As the largest global pure play sustainability consultancy,ERM partners with the worlds leading organizations,creating innovative solutions to sustainability challenges and unlocking commercial opportunities that meet the needs of today while preserving opportunity for future generations.ERMs diverse team of 8,000 world-class experts in over 150 offices in 40 countries and territories combine strategic transformation and technical delivery to help clients operationalize sustainability at pace and scale.ERM calls this capability its“boots to boardroom”approach-a comprehensive service model that helps organizations to accelerate the integration of sustainability into their strategy and operations.Contributing authors:Lucy Liu,Nathan Nguyen,Jo Howes,Robert Pearce-Higgins,Hana Douglas,Meriem Chennoufi,Lizzie Knight,Abdul Petersen,Annie Hargrove,George Naismith2024 Transportation Energy Institute Disclaimer:The opinions and views expressed herein do not necessarily state or reflect those of the individuals on the Transportation Energy Institute Board of Directors and the Transportation Energy Institute Board of Advisors or any contributing organization to the Transportation Energy Institute.Transportation Energy Institute makes no warranty,express or implied,nor does it assume any legal liability or responsibility for the use of the report or any product or process described in these materials.3TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTEXECUTIVE SUMMARY .06INTRODUCTION .11SECTION 1 WHAT ARE E-FUELS?.13 How are e-fuels produced?.14 How mature are e-fuel technologies and what are the key technical challenges?.16 Feedstock Production.16 Fischer Tropsch(FT)Synthesis Routes.17 E-methanol Synthesis.18 Ethanol via Partial RWGS and Fermentation.18 Alcohol-to-hydrocarbons.19 E-methane via Methanation.20 Summary.21SECTION 2 HOW CAN E-FUELS BE USED IN TRANSPORT?WHAT ALTERNATIVE OPTIONS ARE THERE?.22 Which road transport vehicles can use e-fuels?.23 How do e-fuels compare to other decarbonization options in road transport?.24 Biofuel in ICEVs.24 Alternative Powertrains.26 How could the uptake of alternative technologies affect e-fuel demand in the road transport sector?.31 What other transport modes can use e-fuels?.33 Rail Sector.33 Aviation Sector.34 Shipping Sector.35 Summary.36SECTION 3 WHAT ARE THE GHG BENEFITS OF E-FUELS AND HOW DO THEY COMPARE TO OTHER OPTIONS?.39 How do e-fuels lead to GHG savings?.40 What are the well-to-wheel GHG savings of e-fuels now and in the future?.44 Base case emissions.45 Low GHG Emissions Case.47 Partial Grid Electricity Case.48 Contents4TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTHow do the well-to-wheel GHG emissions of e-fuels compare to alternative technologies?.49 How do emissions per mile compare today?.50 How could emissions per mile compare in 2040?.52 What are the other environmental impacts of e-fuel production and use?.53 Water Demand.53 Land Use.55 Use of Mined Resources.56 Air Quality.57 Summary.58SECTION 4 HOW MUCH E-FUELS PRODUCTION CAPACITY COULD THERE BE?.60 What are the development trends of announced e-fuel projects?.61 Trends in E-fuel Production Technologies.61 Trends in Products.62 Trends in Project Locations.63 Major Players.64 How much e-fuel production capacity will be available in the U.S.?.67 Ramp-up Methodology.67 Scenario Assumptions.67 Production Capacity Potential in 2030 and 2040.68 Will there be enough renewable electricity and carbon dioxide in the U.S.to support e-fuels scale-up?.71 Renewable Electricity.71 CO2.74 Summary.77SECTION 5 HOW MUCH DO E-FUELS COST TO PRODUCE AND USE?.79 What is the current production cost of e-fuel technologies?.79 Cost Assumptions.80 E-fuel Production Cost per Pathway.81 What affects e-fuels production costs?.82 Hydrogen and Renewable Electricity.82 Plant Utilization.84 Carbon Dioxide.85 Processing Energy.85 How much could costs come down in the future?.86 How much do e-fuels plants cost to build?.88 What are the cheapest decarbonization options for the road transport sector?.89 Costs for Cars.89 Costs for HDVs.92 How do decarbonization options compare on emissions reduction and cost?.94 Summary.965TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT5 5SECTION 6 ARE POLICIES STRONG ENOUGH TODAY TO SUPPORT E-FUEL DEPLOYMENT IN ROAD TRANSPORT?.98 How do U.S.policies support e-fuels today?.99 The Renewable Fuel Standard.99 The IRA.100 State Level Low Carbon Fuel Standard.103 Are these policies enough to support e-fuel production?.104 Understanding Policy Support.105 Current Policy Support Value.106 Future Policy Support Value.107 Will global fuel policies affect e-fuel supply in the U.S.?.110 EU Fuel Policies.110 UK Fuel Policies.112 Summary.114SECTION 7 WHAT ROLE WILL E-FUELS HAVE IN DECARBONIZING U.S.ROAD TRANSPORT?.116 Will e-fuels be needed to decarbonize U.S.Road transport?.117 How much of this demand could be met by e-fuels,and how would this interact with e-fuel use in other sectors?.118 Key actions needed to support e-fuel uptake.120APENDIX,ACRONYMS&ABBREVIATIONS.122 Acronyms&Abbreviations .123 Appendix A:E-fuel Product Slate References.124 Appendix B:Technical Characteristic of Alternative Powertrains Supporting Information.125 Appendix C:Avoided Emission of Using Renewable Electricity-Assumptions.126 Appendix D:Production Cost Assumptions.127 Appendix E:Cost and Emissions Per Mile Assumptions and Sources.129 Appendix F:Policy Support.1346TRANSPORTATION ENERGY INSTITUTEExecutive SummaryEvaluating the Viability of Commercially Deploying E-fuels in Road TransportThe United States road transport sector accounts for 22%of US greenhouse gas(GHG)emissions.Policies have been put in place to reduce emissions in the road transport sector both on a federal and state level in the U.S.,as well as around the globe.Many decarbonization technologies are available and are being incentivized under such policies,each facing a unique set of challenges as they are deployed commercially.Amongst these options,e-fuels(or synthetic fuels)are a renewable technology that can be used in existing and new vehicles while potentially yielding near-zero emissions.WHAT ARE E-FUELS?E-fuels are renewable fuels produced from water,renewable electricity and carbon dioxide(CO2)via chemical or biochemical processes,which can be used to decarbonize the road,aviation,maritime,and rail sectors.SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2FIGURE ES-1.E-FUEL PRODUCTION PROCESS7TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTWHY IS THERE GROWING INTEREST IN E-FUELS?E-fuels can achieve up to 75-99%GHG savings compared with fossil fuels,when made from additional renewable electricity(i.e.renewable electricity which meets incrementality,deliverability and temporal correlation requirements).They are highly compatible with existing infrastructure and vehicles in the road,aviation,shipping and rail sectors.E-fuels are produced from renewable electricity,carbon dioxide,and water which are highly abundant resources globally.However,most e-fuels technologies are at a low level of technological and commercial development today.Key challenges are the technical risks associated with production processes,high costs,and limited policy support to bridge the cost gap with fossil fuels.To contribute meaningfully to decarbonization across the transport sector,e-fuels will have to become commercially available and be deployed at large scale.This will depend on technical progress,feedstock availability in particular locations,availability of funding,strong policy support,and the speed in which other transport decarbonization options ramp up.This report evaluates the viability of e-fuels in the U.S.,based on their current technical suitability,emission reduction potential,scalability,and economic competitiveness,and how this could change by 2040.It focuses on e-fuels potential contribution to the sustainable transition of the road sector and other transport energy sectors.WILL E-FUELS BE NEEDED TO DECARBONIZE U.S.ROAD TRANSPORT?E-fuels could close potential emission reduction gaps or accelerate emission reduction efforts in road transport in the U.S.The U.S.currently lacks a clear path for road transport decarbonization,leading to uncertainties in how quickly low carbon technologies could be adopted.Battery electric vehicles(BEVs),which are cost-effective and have high GHG savings,will play a significant role in emission reduction,but the speed at which they could replace existing internal combustion engine vehicles(ICEVs)is uncertain due to the technical and infrastructure challenges they currently face,and a lack of policy certainty.As a result,it is expected that ICEVs will continue to be on the road into the 2040s.E-fuels could be deployed to achieve higher emission reductions from existing vehicles,particularly if the supply of sustainable biofuels is slow to ramp up.SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO28TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTHOW COULD DEMAND FROM OTHER TRANSPORT SECTORS INTERACT WITH E-FUELS SUPPLY FOR ROAD VEHICLES?Whether e-fuels will be supplied to the road transport sector in the U.S.will be largely influenced by policy.E-fuel production capacity in the U.S.could grow significantly between now to 2040.We estimate that they could be scaled up significantly to achieve an annual production capacity of 6-14 million tonnes(approximately 2-5 billion gallons)by 2040,but this volume is small(around 6-14%)compared to projected demand for low carbon fuels in transport overall.Currently,e-fuels are much more costly to produce than fossil fuels and biofuels,and while costs could come down in future,they are unlikely to reach cost parity.Because of this,policy support plays a key role in bridging the cost gap,but also in determining in which transport sectors e-fuels could be deployed.Current policy landscape could result in e-fuel producers favoring markets outside of the U.S.Today,Inflation Reduction Act(IRA)tax credits(TC)in the U.S.could help bring down e-fuel production costs but the lack of widespread blending mandates for e-fuels means there is currently no guaranteed market demand for e-fuels.In contrast,fuel policies in the EU and UK include sub-targets for e-fuels and penalties for non-compliance,which create clearer and stronger demand signals,particularly in the aviation sector.Under this policy environment,e-fuels are likely to be produced in the U.S.but sold to the EU/UK markets,so that producers can capitalize on financial support from both supply and demand policies in the U.S.and Europe(including the UK).The strongest demand signals for e-fuels come from the aviation sector but e-fuels could be supplied for both aviation and road transport.E-fuel producers may tune production capacity to maximize e-sustainable aviation fuel(e-SAF)volumes over road fuels due to the higher policy premium being available through ReFuelEU Aviation,the UK SAF Mandate,and the premium offered to SAF under the 45Z Clean Fuel Production TC,and interest from the aviation industry and customers.However,most e-SAF pathways produce diesel and naphtha as co-products,and so their ramp-up will also provide additional fuel for the road sector.High willingness to pay(WTP)from the aviation industry could potentially also help to support road e-fuel prices.The strongest demand signals for e-fuels come from the aviation sector but e-fuels could be supplied for both aviation and road transport.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT9TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTKEY ACTIONS NEEDED TO SUPPORT E-FUEL UPTAKEE-fuels are(and will continue to be)more expensive to produce than their fossil counterparts,making policy support critical for projects to be economically viable.Today,the production cost of e-fuels is 2.5-4 times more than fossil fuels when using low-cost renewable electricity.Despite policy support being available,it could still be challenging for most early e-fuel plants to be economically viable in the near future.The cost gap could fall to 1.5-3 times current fossil fuel prices by 2040 1,2.Policy support in the U.S.could help close this price gap in the future-however this relies on the availability of TCs and the ability to stack them.Further policy drivers are needed to provide additional confidence for investments in e-fuels and to support their uptake.Without a guaranteed market,e-fuel uptake will also be highly unpredictable in the road transport sector given that cheaper alternatives are already commercially available.Given this highly uncertain outlook,enabling the uptake of e-fuels requires a multifaceted approach across technology,sustain-ability,policy,and market development.If U.S.policymakers are keen to further incentivize e-fuel uptake in the transport sector,some recommend-ations they could consider include the following:RECOMMENDATION 1:Set Clearer Transport Decarbonization Pathways,Targets and E-fuels Road Map Develop a knowledge base on U.S.transport decarbonization,including all decarbonization options:There is currently very little detailed analysis and scenarios that show the role of all transport decarbonization options in all modes in the U.S.1 The reference prices for 2023 for gasoline is 3.50 U.S.$/gal(930 U.S.$/tonne).2 EIA(2024):Short-term Energy Outlook.Available from:Link Set clear emission reduction targets for the transport sector,including by mode:Allow market to anticipate what types of low emission transport solutions(including e-fuels)will be needed in road transport decarbonization.Develop a U.S.roadmap for e-fuels production and use:Include the demands of the road,aviation,maritime and rail transport sectors,so that the production plants,infrastructure and policy for these can be developed together,rather than being seen as competing markets.RECOMMENDATION 2:Set Requirements to Ensure E-fuels are Developed Sustainably Standardize lifecycle assessment methodologies:The U.S.currently does not have an agreed and published methodology for calculating the GHG emissions of e-fuels,including the treatment of renewable electricity used.Because some policies set GHG thresholds to determine eligibility or provide higher support for options that provide greater GHG emissions reductions,developing standardized methodologies that account for the benefits of e-fuels will allow stakeholders to evaluate the environmental performance quantitatively to make informed decisions about prioritization.SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO210TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTRECOMMENDATION 3:Implement Policies to Further Incentivize Market Development Guarantee markets for e-fuel producers:The U.S.e-fuel policy landscape currently lacks demand-side policy support to promote the uptake of e-fuel.Policy makers could consider mandating a minimum share of e-fuel use in the road transport sector.Unlike the technology-neutral approach taken by the Low Carbon Fuel Standard(LCFS),an e-fuel sub-target is the most direct way to facilitate market access and provide market certainty to e-fuel developers and investors.The cellulosic sub-target within the Renewable Fuel Standard 2(RFS2)is an example of this.This could be designed to ensure that e-fuels plants in the U.S.,which will receive production-side support,prioritize domestic demand instead of being drawn away to the UK/EU with mandated markets.Some have argued that a technology neutral carbon intensity(CI)-based target is more appropriate for meeting GHG reduction goals,however guaranteed markets for emerging technologies can help to give confidence in markets and so secure investment.3 For more information on the AFF,see LinkRECOMMENDATION 4:Create Funding Opportunities for E-fuels Increase public funding for e-fuel projects:E-fuel production is capital intensive with capital expense(CAPEX)contributing 17-24%of the levelized production costs.It is challenging to secure private investment for early development technologies due to large risks associated with low maturity plants.Having access to public funding to secure capital costs for early plants could help promote e-fuel plant roll-out in the U.S.,like the Advanced Fuels Fund(AFF)3 in the UK.While funding programs for biofuel and hydrogen projects are available in the U.S.,none to our knowledge exist which targets e-fuels.Securing public funds can also provide confidence to investors and unlock additional private investment to projects as well.SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT11The need to tackle climate change will require deep emissions reduction in all sectors of the economy.The U.S road sector accounts for 80%of emissions arising from the transport sector(excluding all off-road applications),and 22%of overall US GHG emissions,4 while at a global level it accounts for approximately 12%of total anthropogenic emissions.5 Increasingly stringent regulations have been put in place to reduce emissions in the U.S.road sector,both at a federal and state level,as well as around the globe.Many decarbonization technologies are available and are being incentivized under such policies,each facing a unique set of challenges as they are commercially deployed.4 EPA(2022),Fast Facts on Transportation Greenhouse Gas Emissions.Available from:Link5 EPA(2024),Global Greenhouse Gas Overview.Available from:LinkIntroductionTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT12One decarbonization option is e-fuels,a type of renewable fuel produced synthetically from electrolytic hydrogen and captured carbon dioxide(CO2).E-fuels represent a promising opportunity because they:Can achieve high lifecycle GHG savings compared with fossil fuels.Section 3 looks at this in detail.Are compatible with existing infrastructure and vehicles in the road,aviation,shipping and rail sectors as“drop-in”fuels as shown in Section 2.E-fuels are produced from renewable electricity,carbon dioxide,and water which are highly abundant resources globally.Feedstock availability in the U.S.is explored further in Section 3.Given their potential scalability,e-fuels could strongly contribute towards ambitious decarbonization targets across all transport sectors.However,their production is in the early stages of technology development today,with key challenges including:Technology risks,as many e-fuels production technologies are yet to demonstrate commercial operation.This is explored in detail in Section 1.High costs,driven by the high energy consumption of producing green hydrogen and fuels processing,and the high capital investment costs of e-fuels plants.Section 5 compares this to current fossil fuel prices.Competition with other uses of renewable electricity,and between end-use sectors,meaning that consideration is needed of impacts on the energy system,and the options available to different transport sectors,which will change over time.This is discussed further in Section 3.Limited policy support,which is yet to bridge the cost gap between e-fuels and conventional fossil fuels or biofuels and provide clarity around GHG accounting methodologies.A policy analysis is carried out in Section 6.To contribute meaningfully to decarbonization across the transport sector,e-fuels will have to become commercially available and be deployed at large scale.This will depend on several factors,such as technical progress,feedstock availability,availability of funding,strong policy support,and successful competition with other transportation decarbonization options.Despite these challenges,they could be an important way to decarbonize transportation sectors with limited alternative options.This report evaluates the viability of e-fuels in the U.S.,with a specific focus on road transport sector,based on their emission reduction potential,scalability,and economic competitiveness.KEY QUESTIONS What are e-fuels and how are they produced?How can e-fuels be used in the transport sector and what alternative options are there?How can e-fuels reduce GHG emissions and how does this compare to other options?How much e-fuels production capacity could there be?What are the costs of producing and using e-fuels?What policy support is available for e-fuels?TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT13Many low carbon fuel equivalents to the fossil fuels used in road transport vehicles today can be produced from alternative sources such as biomass,or,in the case of e-fuels,synthetically from renewable electricity,water and captured CO2.There are many e-fuels technology pathways that can produce a range of products,but generally they are all at early stages of development today,though some production technologies are already nearing commercialization.This section defines e-fuels and introduces the main production technologies that will be discussed in this report.SECTION 1.What are E-fuels?SECTION 1:KEY QUESTIONS How are e-fuels produced?How mature are e-fuel technologies and what are the key technical challenges?TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT141.1 HOW ARE E-FUELS PRODUCED?FeedstocksE-fuels are a type of low carbon fuel produced from water,renewable electricity and CO2 feedstocks via a range of production technologies using chemical or biochemical processes as summarized in Figure 1-1.Renewable electricity is used as a primary energy source for the electrolysis of water to create green hydrogen,which can then be combined with CO2 captured from biogenic or existing industrial point sources such as bioenergy plants and cement plants respectively,or directly from the atmosphere through direct air capture(DAC).Green hydrogen and its derivatives,such as e-ammonia,are also considered to be e-fuels,but are not discussed in detail in this report as their production and use differs from other e-fuel pathways involving captured CO2.ProductsE-fuel technologies can produce a range of products that can be used to decarbonize the transport sectors,including vehicles used in road,aviation and shipping,as well as the chemical sector.They can produce fuels that have very similar chemical properties to fossil fuels,such as gasoline,diesel or jet fuel,and are free of sulfur content.These are often referred to as drop-in-fuels,which can be blended in at high levels and used directly in existing ICEs and infrastructure without any major modifications(some can also be used to improve the property of fuels such as density,aromatics contents,and lubricity)this can include both liquid and gaseous fuels.E-fuel technologies can also produce fuels that are non-drop-ins,such as alcohols(i.e.ethanol and methanol).These are fuels that can only be blended and used in conventional gasoline vehicles up to a blend limit but require vehicle modifications to enable their use at higher blends.Alcohols can also be further processed into drop-in fuel products.SYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productH2 -RENEWABLE ELECTRICITYWATERINDUSTRIALSOURCESATMOSPHERECARBON DIOXIDEELECTROLYSISHYDROGENE-FUELTECHNOLOGIESDROP-IN FUELSNON-DROP-IN FUELSUTILITY INCENTIVEPOWERTRAINUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeCO2CO2FIGURE 1-1.E-FUEL PRODUCTION PROCESSTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT15E-fuel production technologiesThere are many methods of producing e-fuels.This report covers the following five main technologies.TABLE 1.E-FUEL PRODUCTION PATHWAYS IN THIS STUDYPRODUCTION TECHNOLOGYFUEL PRODUCTSFischer Tropsch(FT)based routesJet fuel,diesel,gasoline(from naphtha upgrading)E-methanol synthesisMethanolEthanol via partial reverse water gas shift (pRWGS)and fermentationEthanolAlcohol-to-hydrocarbons E-methanol-to-jet/gasoline (e-MTJ/e-MTG)E-ethanol-to-jet(e-ETJ)Jet fuel,diesel,gasolineE-methane via methanationCompressed or liquified methane(i.e.CNG or LNG)PRODUCT SLATEMany e-fuel pathways can produce a range of products in varying percentages,known as a product slate,that can be used to decarbonize the road,aviation and shipping transport sectors.Product slates are largely determined by the chemical reaction of each processing technology but can be altered to a certain degree through reconfiguring operating conditions,similar to the way in which conventional crude oil refineries can vary the proportion of gasoline and diesel output.Typical product slate ranges referenced in literature and producer data are shown for the technologies in Section 1.2.These references can be found in Appendix A.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT161.2 HOW MATURE ARE E-FUEL TECHNOLOGIES AND WHAT ARE THE KEY TECHNICAL CHALLENGES?Most e-fuel production pathways are at low stages of technological development today.Pilot and demonstration projects have only recently entered operation in the last 1-2 years.Notably,e-fuels developer Highly Innovative Fuels(HIF)opened a demonstration plant producing drop-in e-gasoline in Chile at the end of 2022,with the fuel transported to the UK for use by Porsche.More on this can be seen in Section 4 through a case study on HIF.Most e-fuels production processes are at a Technology Readiness Level(TRL)of 7 or below,which is a system of measurement used to evaluate and compare the maturity of a technology as illustrated in Figure 1-2.However,there are plans to implement larger demonstration and first-of-a-kind(FOAK)commercial e-fuels projects in the next 2-3 years,particularly in the U.S.and the EU,which would move many of the technologies to TRL 7 and 8.More information is provided about project 6 NASA(n.d.),Technology Readiness Level Definitions.Available from:Link7 IEA(n.d.),Electrolyzers.Available from:Linkdevelopment timelines,future plant capacities and supply scalability in Section 4.6The following section provides an overview of the five main e-fuels pathways,including a brief explanation of the technology processes and maturity.Each technology pathways are scored a TRL based on their progress against the criteria in Figure 1-2,followed by a discussion of their key technical challenges.1.2.1 FEEDSTOCK PRODUCTIONE-fuel synthesis begins with the production of its chemical building blocks:electrolytic hydrogen and CO2,which are relatively mature.Green hydrogen,or electrolytic hydrogen,is produced from water and renewable electricity using an electrolyzer.There are many types of electrolyzer technologies available today-polymer exchange membrane(PEM)and alkaline(ALK)are the main technologies and are at TRL 9,7 with many commercial projects operating today.Across all e-fuel pathways,electrolysis FIGURE 1-2.THE TECHNOLOGY READINESS LEVEL SYSTEM OF MEASUREMENT6Basic principles observedTechnology concept and/or application formulatedAnalytical and experimental proof-of-concept achievedTechnology validated in a laboratory environmentSystem prototype demonstration in operational environmentSystem complete and qualifiedTechnology validated in relevant environment(industrially relevant environment in the case of key enabling technologies)Technology demonstrated in relevant environmet(industrially relevant environment in the case of key enabling technologies)Actual system proven in operational environment(competitive manufacturing in the case of key enabling technologies)TRLTRLTRLTRLTRLTRLTRLTRLTRL123456789TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT17requires the highest electricity input,typically representing 60-70%of total energy requirements for e-fuel production.CO2 capture from industrial point sources,such as power stations and cement plants,is also at TRL 9.CO2 could also be captured directly from the atmosphere via DAC,but this is at a lower maturity(TRL 7).8 1.2.2 FISCHER TROPSCH(FT)SYNTHESIS ROUTESThe FT synthesis process begins with the production of syngas,which is a mixture of hydrogen and carbon monoxide(CO).The two main syngas production technologies are co-electrolysis and reverse water gas shift(RWGS),both of which are at an early stage of development(TRL 6)with a handful of small pilot systems in operation today.Reverse water-gas shift This is a chemical reaction that uses hydrogen to convert CO2 to CO at very high temperatures and pressures.8 ADI Analytics,(n.d),Going Blue:A review of direct air capture.Available from link The challenges are the very high energy consumption and maintaining a stable reaction to produce the required amount of syngas.Co-electrolysis This is an electrochemical reaction which converts CO2 into CO using electricity.Key challenges include the high electricity consumption and the low lifetime of membranes used in the electrolyzer.This syngas is then chemically converted via the FTprocess into drop-in products such as jet fuel and diesel,as well as naphtha and hydrocarbon waxes.These can also be upgraded further into gasoline products and other drop-ins.FT is a commercial process(TRL 9)used in the fossil fuel industry,with many large industry players such as Shell,Johnson Matthey and Sasol aiming to license their technology to e-fuels demonstration projects in the next 2-3 years.Although FT is commercial,the overall TRL of integrated FT synthesis and upgrading routes is TRL 6,because this is limited by the low TRL of co-electrolysis and RWGS.FIGURE 1-3.FT SYNTHESIS-BASED PATHWAYSReverse watergas shiftFT synthesisandupgradingCo-electrolysisSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVGreen hydrogen and CO2Syngas(H2 and CO)CO2H20FEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATEUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeOverall TRL of route:6 FT jet 25-75%Naphtha 25-50%FT diesel 0-50%NaphthaFT jet fuelFT dieselOverall TRL of route:617TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT181.2.3 E-METHANOL SYNTHESISE-methanol can be produced through the reaction of hydrogen with CO2 at high temperatures and pressures using a metal catalyst.There are few technical challenges with this conversion process and it is already a commercial technology(TRL 8-9)but most operational projects today use fossil hydrogen and CO2.The first commercial e-methanol projects using green hydrogen and captured CO2 are slated to enter operation this year9,which would move the technology from TRL 7 to TRL 8.Though the technology risk remains low as the process is highly similar to the already commercialized fossil process.1.2.4 ETHANOL VIA PARTIAL RWGS AND FERMENTATIONE-ethanol routes also involve the use of syngas but using a different process from FT synthesis.There are two main steps in these routes:Partial RWGS(pRWGS)This is a chemical reaction that produces syngas from hydrogen and CO2.The syngas composition required for further processing into ethanol is different to FT and therefore lower temperatures and pressures than the full RWGS reaction are needed.This technology is at TRL 5.Fermentation The resulting syngas is then fermented in a biochemical reaction using micro-organisms to produce ethanol and other organic compounds.The fermentation process is at TRL 8,with five demonstrations and first commercial projects operated today by Lanzatech,who are the only player actively pursuing this technology.However,these facilities use waste fossil gases from industrial facilities rather than green hydrogen,which are not categorized as e-fuel pathways.As such,the integrated e-fuel pathway is only at TRL 5 as the pRWGS step is yet to be demonstrated.Additionally,the fermentation step faces challenges with low yield of ethanol due to the slower reaction rate of the biological processes compared to thermal/chemical routes.9 Mitsu&Co(2023),Mitsui Invests in the Worlds Frist e-Methanol Production&Sales Business in Denmark.Available from:LinkFIGURE 1-4.METHANOL SYNTHESIS PATHWAYFIGURE 1-5.ETHANOL VIA PRWGS AND FERMENTATION PATHWAYMethanol synthesisSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVGreen hydrogen and CO2FEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATEUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeOverall TRL of route:7 E-methanol 100%E-methanolOverall TRL of route:7Partial reversewater gas shiftFermentationSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVGreen hydrogen and CO2FEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATEUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeOverall TRL of route:*Other types of alcohols and compounds can be produced from this process,depending on the use of the microbes and reactio conditions E-ethanol 100%*E-ethanolSyngas(H2,CO2,CO)Overall TRL of route:5TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT191.2.5 ALCOHOL-TO-HYDROCARBONS Methanol and ethanol are not drop-in fuels but can be converted to drop-in gasoline,diesel or jet fuel.To achieve this,they are first converted to olefins such as ethylene and propylene,which are more easily reacted into the desired hydrocarbon products.For methanol-based routes,this is via a chemical reaction called methanol-to-olefins(MTO).For ethanol,this is through a dehydration reaction using heat and catalysts.A range of further processing steps then convert the olefins into transport fuels using a small amount of additional hydrogen.Methanol can be converted to drop-in fuels through Methanol-to-gasoline(MTG)or Methanol-to-jet(MTJ).This process was developed in the 1980s but has typically used methanol from fossil sources.The first demonstration plant producing e-MTG was commissioned by HIF in 2022,bringing the technology to TRL 7.The MTJ process is less mature at TRL 6.There are generally low technical risks in the individual processing steps but there has been limited development to date of the entire e-MTJ/G production process including use of green hydrogen and captured CO2.Ethanol can also be converted to jet fuel,with drop-in diesel as a by-product.This pathway is referred to as Ethanol-to-jet(ETJ).This technology is currently at TRL 7,but several large demonstrations and first commercial plants are planned in the next 1-2 years which would move it to TRL 8.While the majority of individual processing technology steps in alcohol-to-hydrocarbon routes have been demonstrated,the main technical challenge may be in integrating multiple steps together to achieve efficient e-fuels production.FIGURE 1-6.METHANOL-TO-GASOLINE/JET PATHWAYSMethanol-toGasolineMethanol-toGasolineMethanol-to-olefinsSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productOlefins MethanolFEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATE Gasoline 80-90%Hydrocarbons 25-50%(LPG*,fuel gas)FUEL PRODUCT SLATE Jet 65-75%Diesel 12-15%Naphtha etc.10-22%OthersGasolineNaphtha etc.DieselJetOverall TRL of route:67*Liquefied Petroleum GasFIGURE 1-7.ETHANOL-TO-JET PATHWAYEthanol-to-JetNaphtha etc.DieselJetDehydrationSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVEthanolOlefinsFEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATE Jet 75%Diesel 15%Naphtha etc.10%Overall TRL of route:67TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT201.2.6 E-METHANE VIA METHANATION E-methane is a drop-in alternative to natural gas,which can be compressed or liquified and used in natural gas vehicles(NGVs)or liquefied natural gas(LNG)vessels.E-methane can be produced via a catalytic methanation reaction of CO2 and hydrogen using metal catalysts or biological micro-organisms.The former process has been used since the 1980s using CO2 and hydrogen from fossil sources,but biological routes are currently at demonstration stage(TRL 7).The main challenge is the relatively low yield of e-methane due to a slow biological reaction.FIGURE 1-8.E-METHANE PATHWAYS VIA METHANATIONCatalytic methanationBiological methanationSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVGreen hydrogen and CO2FEEDSTOCKSPROCESSING TECHNOLOGIESPRODUCTSFUEL PRODUCT SLATEUtility/contribution in aid of constructionHost site/third-party investmentUtility incentive paymentsIncreasing vehicle sizeOverall TRL of route:7 E-methane 100%E-methaneOverall TRL of route:7TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT211.3 SUMMARYHow are e-fuels produced?E-fuels are a type of low carbon fuel produced from combining hydrogen(produced via electrolysis of water using renewable electricity)with captured CO2 from industrial processes or from the air.There are many e-fuel production technologies being developed today which can produce a range of drop-in and non-drop-in fuels that can be used to replace fossil fuels consumed in ICEs.How mature are e-fuel technologies and what are the key technical challenges?E-fuel technologies are currently at early stages of development,generally having TRLs of 6 or lower,with the exception of e-methanol synthesis and methanation.Several of the key processing steps are still only at the pilot stage today,but several developers are planning first commercial facilities in the next few years which could help overcome key technical challenges.MethanationMethanol synthesisFermentationAlchohol-to-hydrocarbonsFT synthesis upgradingCo-electrolysisRWGSPartial RWGSSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productSyngasGreenhydrogenand CO2Vehicle manufacturing and assemblyWell-to-wheelUTILITY INCENTIVEFEEDSTOCKSE-FUELSTECHNOLOGIESE-FUELSTECHNOLOGIESPRODUCTSDrop-ine-fuelsE-ethanol*E-methanol*PRODUCTSDrop-ine-fuels*E-ethanol and e-methanol are not drop-in fuels but can be further converted into drop-insTABLE 2.SUMMARY OF E-FUEL PRODUCTION TECHNOLOGIESPRODUCTION TECHNOLOGYTRLPRODUCTSKEY TECHNICAL CHALLENGESFT synthesis-based routes6Jet fuel,gasoline(from naphtha upgrading),diesel High energy and/or electricity consumption to produce required syngas Maintaining stable reactions Low lifetime of reaction catalysts E-methanol synthesis7Methanol Few major technical challenges but high energy consumption required for hydrogenation reactionEthanol via pRWGS and fermentation5Ethanol Limited development of pRWGS Relatively low ethanol yields due to slow rate of biological reactionAlcohol-to-hydrocarbons6-7Jet fuel,diesel,gasoline Integration of multiple processing technologies for efficient and stable e-fuels production E-methane via methanation7Methane Few major technical challenges but low e-methane yields for biological methanation FIGURE 1-9.E-FUEL PRODUCTION TECHNOLOGIES AND PRODUCTSTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT22E-fuels can be used to decarbonize a range of transport sectors and vehicles.Drop-in e-fuels are chemically similar to their fossil counterparts and are compatible with todays ICEs,powering vehicles,aircraft and vessels.Non-drop-in e-fuels can be blended up to a limit in some of these vehicles but beyond this,modifications to engines and infrastructure are required.There also alternative technologies and powertrains that could compete with e-fuels to decarbonize the road transport sector,each with different technical characteristics,end-use infrastructure requirements and technological maturities.Some of these options are in commercial use on-road today,such as BEVs.Outside of the road sector,e-fuels can also be used to decarbonize other transport modes including rail,shipping and aviation.Their reliance on e-fuels as a decarbonization option could impact supply availability to the road sector.SECTION 2.How can e-fuels be used in transport?What alternative options are there?E-SAFE-dieselE-gasolineE-methane1E-ethanolE-naphtha2E-methanolSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVVehicle manufacturing and assemblyUTILITY INCENTIVEDROP-IN FUELSNON-DROP-IN FUELS1 E-methane is considered a drop-in fuel as it is chemically similar to natural gas,but its use is limited by the availability of NGVs and fueling infrastructure.2 Naphtha is a hydrocarbon molecule,which can be further processed into gasoline for use in ICEVs.SHIPPINGROADRAILAVIATIONFIGURE 2-1.E-FUELS CAN DECARBONIZE MULTIPLE TRANSPORT SECTORSTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT23This chapter evaluates the technical suitability of e-fuels,and alternative decarbonization options across vehicle types in the road sector,as well as in aviation,shipping and rail.Broader infrastructure needs are also discussed to identify challenges users may face with technology adoption.10(DOE)(2012),Vehicle Weight Classes&Categories.Available from:link11 DOE(2024),Average Annual Vehicle Miles traveled by Major Vehicle Category.Available from:link12 Federal Highway Administration(2022),National Household Travel Survey.Available from:link2.1 WHICH ROAD TRANSPORT VEHICLES CAN USE E-FUELS?The U.S.road sector can be categorized into three vehicle fleets,light,medium and heavy-duty vehicles,each with different technical and fuel requirements shown in Table 3.10,11,12Drop-in fuels such as e-gasoline,e-diesel and e-methane are suitable for LDVs,MDVs and HDVs.These fuels can be used by themselves or as blends with fossil fuel with no modifications to engines,fuel tanks or fueling infrastructure,provided that their production pathways and the fuels themselves meet ASTM International fuel standards.They can be used directly in U.S.LDV fleets which are primarily gasoline ICE vehicles,and diesel and compressed natural gas(CNG)vehicles that are more commonly seen in medium and heavy-duty vehicle fleets.Non-drop-in e-fuels can be used directly in gasoline ICEVs up to a certain volume but limited by a blend wall seen below and are suitable for LDVs.At high blends,significant modifications areSECTION 2:KEY QUESTIONS Which road transport vehicles can use e-fuels?How do e-fuels compare to other decarbonization options in road transport?How could the uptake of alternative technologies affect e-fuel demand in road transport?What other transport modes can use e-fuels?TABLE 3.DEFINITIONS AND CHARACTERISTICS OF ROAD TRANSPORT VEHICLE FLEETSVEHICLE CATEGORYDEFINITION10 VEHICLE TYPESTECHNICAL AND FUEL REQUIREMENTSLight-duty vehicle(LDV)Maximum weight under 10,000 lbs(Class 1-2)Most passenger cars,vans and pickups,motorbikes.Lowest annual mileage,11 most used for short trips(50 kW)in the US,with a further 120,000 public slow chargers 22 Hydrogen Insights(2024),Shell to permanently close all of its hydrogen refueling stations for cars in California.Available from:link(up to 7 kW).For HDVs,the operational impact of lower ranges could be more severe than for LDVs and MDVs,given their higher energy requirement,higher mileages and fewer available public rapid charging points.Whilst the number of BEVs in the U.S.is currently relatively small,this is expected to grow over time and affect the long-term potential demand for e-fuels in road transport.FCEVs have the potential to be used in a similar way to ICEVs,with comparable range and refueling speeds.However,whilst there are 145,000 gas stations across the U.S.,there are only 54 publicly available HRSs,53 of which are in California(this number has recently declined due to recent closures of several Shell HRSs in California).22 Outside of California,large logistics hubs might be able to create enough hydrogen demand to have hydrogen delivered directly to the depot.This would be most suitable for repetitive routes as there currently would be no alternative locations to refuel outside of the depot.This option would not be accessible to smaller hubs or private consumers,who would need to wait for the development of a public refueling network.FCEV uptake is currently very low and is not expected to significantly impact the potential demand of e-fuels before 2040 at earliest.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT30NGVs can be used in a similar manner to ICEVs,with comparable range and refueling speeds.Whilst there are only 1,400 NG refueling stations in the U.S.(down from nearly 1,600 in 2019),large depots can also compress NG from the gas network to refuel the depot fleet.However,this is not an option for smaller depots or private users,who will need to rely on the public refueling network.This is highlighted by the significant uptake of NGVs for buses and trash trucks in the U.S.,which have predictable operations and operate from a depot,and negligible uptake for private cars.As the number of refueling stations is decreasing rather than increasing,it is unlikely that the deployment of NGVs will increase sufficiently to impact potential demand for e-fuels before 2040 at earliest.23 American Petroleum Institute(2024),Service Station FAQs.Available from:link24 DOE,Alternative Fuels Data Center:E85(Flex Fuel).Available from:link25 DOE,Alternative Fuels Data Center:Alternative Fueling Station Counts by State.Available from:linkPOWER-TRAINREQUIRED INFRA-STRUCTURECURRENT INFRASTRUCTURE REFUELING/RECHARGING TIMEVEHICLE/FUEL SUPPLYFIT WITH USER NEEDSConventional ICEV&HEVGas/diesel refueling stationsOver 145,000 gas stations.23 FFVStations with E15 or E85 pumpsOver 4,200 E85 stations.24 PHEVSlow charge points(up to 7 kW).Gas/diesel refueling stationsOver 145,000 gas stations.Recharging can be done at homes with a garage or driveway.5 minutes(gasoline)2-10 hours for battery chargingVehicle supply could be limited by production capacity battery supply.Can be used as an ICEV,plug in at home to reduce emissions.BEVSlow charge points(up to 7 kW)for general useRapid charge points(50-150 kW)for en-route charging.Higher power for MDVs and HDVsSlow charging can be done at homes with a garage/driveway,or depot for commercial vehicles.120,000 slow public chargers and 40,000 rapid chargers in the U.S.,quarter of which are in CA.255-10 hours(slow charging)30-60 minutes from 10%to 80%charge(fast charging)Electricity is widely available.Vehicle supply to the U.S.is currently limited,but is growing rapidly in both the U.S.and globally.For many uses,can fit user requirements with no changes.For long-haul uses,extra stops to recharge will be required.FCEVHydrogen refueling stations53 of 54 public HRS are in CA.25Up to 15 minutesHydrogen supply is currently limited.Vehicle supply limited by production capacity.Usage could be like ICEV,but required infrastructure is lacking beyond CA.NGVNatural gas refueling stations1,400 NG refueling stations in the U.S.,25 vehicles can also be refueled at depots with delivered gas or through the gas network.Rapid refueling possible under 15 minutesNG is widely available.Significant vehicle supply is limited to certain vehicles(e.g.buses,trash trucks).Similar performance to ICEV.TABLE 9.COMPARISON OF PRACTICAL CONSIDERATIONS FOR POWERTRAINSWidely available.5 minutesTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT312.3 HOW COULD THE UPTAKE OF ALTERNATIVE TECHNOLOGIES AFFECT E-FUEL DEMAND IN THE ROAD TRANSPORT SECTOR?New sales of vehicles in the U.S.are currently dominated by conventional ICEVs for both cars and MDV/HDVs,as shown in Figure 2-2.The proportion of sales of non-ICE vehicles is expected to increase in coming decades,but given the current average vehicle is 12.2 years old,26 it is likely there will still be many ICE vehicles still on the road into the 2030s and 2040s.Some powertrains had negligible sales in certain road transport segments in 2022,for example NGV for passenger cars,HEV and PHEV for medium and heavy-duty vehicle.Whilst these technologies are technically suitable,there has been minimal sustained interest from manufacturers to develop and sell these vehicles.Although ambitions have been set in the U.S.to achieve 50%EV sales by 2030,29 the ability to achieve this non-legally binding goal is highly uncertain given the technical and infrastructure challenges which could impact uptake rate across all road transport segments.This uncertainty is reflected by the large range of vehicle stock forecasts in the U.S.Across all scenarios,light-duty ICEVs are expected to continue to play a role in road transport in 2040(Figure 2-3).This means that there could be a role for e-fuels as a decarbonization solution in road transport,given their flexibility to be used in ICEVs as other options ramp up,as well as in other modes.26 S&P Global Mobility(2022),Average Age of Vehicles in the U.S.increases to 12.2 years,according to S&P Global Mobility.Available from:link27 National Automobile Dealers Association(2023),NADA Market Beat:2023 New Light-Vehicle Sales Reach 15.46 Million Units.Available from:link28 S&P Global Mobility(2023),Fuel for Thought:The commercial vehicle fleet accelerates toward ZEV(zero emission vehicles)adoption.Available from:link29 The White House(2023),FACT SHEET:Biden-Harris Administration Announces New Private and Public Sector Investments for Affordable Electric Vehicles,Available from:link New York 6%New Jersey 4%Illinois 3%Pennsylvania 3%Michigan 3%Ohio 3%Washington 3%Georgia 2%North Carolina 2%Massachusetts 2%Arizona 2%Virginia 2%0%More than 25 years21 to 25 years16 to 20 years11 to 15 years6 to 10 years0 to 5 yearsCAR SALES 202283.3%7.2%7.6%1.9%MEDIUM AND HEAVY-DUTY VEHICLE SALES 202298.1%0.8%1.1%FIGURE 2-2.U.S.CAR27 AND HDV28 SALES IN 2022 BY POWERTRAINNote:powertrains that are not shown had 50 50:100%LTS-Lower transportation scenarioRepresents a scenario in which decarbonization challenges emerge in the transport sector.2030:30 50:70%Annual Energy Outlook(AEO)2023Projection using a market-based approach,while subject to regulation and standards.It accounts for economic competition across the various energy fuels and sources.2030:7 50:18%TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT332.4 WHAT OTHER TRANSPORT MODES CAN USE E-FUELS?The rail,shipping and aviation industry also face the need to decarbonize,and all could also use low carbon fuels.The role that e-fuels will play in each of these will depend on the specific technical requirements of the transport modes,the maturity of alternative decarbonization technologies,and the availability of other low carbon fuel options such as biofuels.Given that the production capacity of e-fuel could be limited in the near future,e-fuel supply for the road sector could also be impacted by demand for e-fuels in these other transportation sectors.This is discussed in more details in Section 4.2.4.1 RAIL SECTORMost passenger and freight trains are powered by diesel in the U.S.,with direct electrification installed on less than 1%of all rail tracks,compared to 30-40%globally 33.Low carbon fuel options Low carbon diesel is an alternative that could be used in rail transportation.As with MDVs and HDVs,other 33 Environmental and Energy Study Institute(2018),Electrification of U.S.Railways:Pie in the Sky,or Realistic Goal?Available from:linklow carbon fuels are less suited to replace diesel as engine modifications are required to accommodate blends including ethanol or methanol.Alternative powertrains options The most common alternative to diesel trains is direct line electrification,where the train is directly powered by overhead wires or an electrified third rail.Development of alternative powertrains that use hydrogen is underway,though they will face range challenges for long-distance routes as they require large and heavy energy storage.RAIL SECTOR ROLE OF E-FUELSWithout significant investments into line electrification,the use of liquid fuels for rail transportation is likely to continue in the U.S.,which may be a potential market for e-diesel.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT342.4.2 AVIATION SECTORTodays aircraft fleet relies on liquid fossil jet fuel,which has a high energy density and allows for fast refueling.Low carbon fuel options Sustainable aviation fuels(SAF),can be blended with fossil jet as drop-in liquid jet fuels due to having similar chemical properties and energy density to fossil jet.SAF can be produced from biomass,or from renewable electricity,e-SAF using production pathways very similar to the ones for producing road e-fuels(e.g.FT synthesis),some with additional processing steps(i.e.alcohol-to-jet via ethanol or methanol).Today,there are two e-SAF routes(FT synthesis and alcohol-to-jet via ethanol)are currently qualified by ASTM International for use in existing aircraft engines and fueling infrastructure up to a blend limit of 50%by volume.Alternative powertrain options For aviation,alternative powertrains using hydrogen and electricity are technically challenging.This is because aircraft are both highly size and weight sensitive,so the use of heavier or larger energy storage systems is likely to be limited to smaller,short-range aircraft.AVIATION SECTOR ROLE OF E-FUELSThere is likely to be significant use of low carbon fuels over the next 30 years in aviation because alternative technologies for aviation such as hydrogen and electricity have much lower energy density,which could limit their use in aviation to short-haul flights only.In addition,a long aircraft lifetime and fleet turnover time will mean the aviation sector continues to rely on liquid fuels compatible with existing engines and infrastructure,therefore making e-fuels and other low carbon fuels critical for decarbonization.As a result,many planned commercial e-fuels are configured to maximize e-SAF production(see Section 4),with a smaller portion of road fuels produced as co-products.This could impact e-fuels supply to the road sector before e-fuel production capacities become more widely available.This dynamic is assessed further within the context of policy in Section 6.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT352.4.3 SHIPPING SECTORLike aircraft,vessels also require fuels with high energy density,with most using heavy fuel oil(HFO).Low carbon fuel The main alternative fuel options for shipping being explored:Liquefied methane or LNG,which is a drop-in fuel that can be used in existing LNG vessels and bunkering infrastructure with no major modifications or impacts on range.Methanol,which is a liquid fuel that can be used in pure methanol vessels or dual fuel vessels compatible with methanol.Green hydrogen and ammonia,which are also produced from renewable electricity and would be used as liquid fuels in new vessel types.These have not been considered in this study because they are not produced from captured CO2 as other e-fuels.All of these fuels require different engines,vessels,bunkering infrastructure,and safety standards to existing HFO vessels,which are currently limited,particularly for methanol.However,LNG and methanol vessels represent over 70%of the global vessel order book as of 2023 and there is growing interest from ports and regulatory bodies in developing infrastructure and standards 34.Alternative powertrain options For shipping,the technical potential of alternative powertrains depends on the range required.For short trips(e.g.local ferries,river vessels),hydrogen or battery electric could be options.However,range could be limited for electric boats and cost for hydrogen fuel cell ships could be less competitive compared to other liquid fuel options such as ammonia due to high storage costs,thus limiting their ability as decarbonization options for deep-sea shipping.34 DNV(2023),Alternative Fuels Insight.Available from:link SHIPPING SECTOR ROLE OF E-FUELSThough hydrogen and electric boats are viable decarbonization options for short trips,liquid fuels are likely to be used in deep-sea shipping for many more decades due to their high energy density,which could represent a key market for e-fuels.Despite infrastructure challenges,there could still be strong growth in demand for liquid fuels and e-fuels in the shipping sector.In addition to biofuels,this demand could also be met with liquid hydrogen and ammonia produced via renewable electricity,which are not used in road ICEVs fleets.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT362.5 SUMMARYWhich road transport vehicles can use e-fuels?E-fuels are highly compatible with existing ICEVs and hybrid vehicles across all vehicle categories(i.e.LDVs,MDVs,and HDVs).Drop-in fuels such as e-gasoline,e-diesel and e-methane can be used directly at high blends in existing engines and fuel distribution infrastructure with no modifications.Non-drop-in fuels can be similarly used,but only up to a low blend wall.Higher blends of e-ethanol and e-methanol can be used in FFVs,but these require different distribution and fueling infrastructure,which could limit their uptake.How do e-fuels compare to alternative technologies and powertrains in the road transport sector?In road transport,there are a variety of technically suitable powertrains which are already commercially available.Other powertrain types are being developed in all transport sectors,though the level of suitability between road transport segments depends on the energy storage requirements on the vehicle as well as other technical requirements of the vehicle and supporting infrastructure.Like e-fuels,biofuel technologies can produce drop-in and non-drop-in fuels for transport.There are no differences in the vehicle and infrastructure modifications required for a given fuel type produced from biomass or e-fuel feedstocks.However,biofuels face upstream supply challenges due to feedstock availability,potential sustainability concerns for some feedstocks,and in some cases immature supply chains.It is estimated that non-food biofuel production could reach 50 billion gallons by 2040.Electrification of LDVs via BEVs is a popular decarbonization solution as they not only meet the driving needs of an average user from a range perspective,but are also significantly more efficient than ICEVs,which could reduce overall energy demand.However,the charging infrastructure required to support electrification is less developed compared to e-fuels,which can use existing liquid fuel distribution supply chains.This limits current uptake,though is rapidly improving.There are no differences in the vehicle and infrastructure modifications required for a given fuel type produced from biomass or e-fuel feedstocks.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT37Comparatively,fewer alternative powertrain options are available for MDVs and HDVs due to requirements for range and charging efficiency.BEVs are currently available for short-range use,whilst long-range options are currently limited but could be available within five years.Similarly,FCEV options are also limited at present with more development expected in the near future.NGVs are already in use in commercial vehicles but face infrastructure challenges as the number of CNG refueling stations for NGVs has declined over the past decade.Growth of infrastructure has also been slow for hydrogen refueling in recent years.BEVs could be widely adopted in road transport in the future,along with some niche uses of FCEVs,which could reduce long-term demand for e-fuels.Uptake of hybrid vehicles will likely be constrained to LDVs and NGVs to MDV and HDVs but will complement e-fuel demands.There is potential for HEVs and NGVs in the short term,however,it is expected that they have limited potential in the long-term as zero-emission technology capabilities improve and reduce in price.POWERTRAINSCAN USE E-FUELS?LDVSMDV/HDVSConventional ICEVDominant powertrain technology today.Dominant powertrain technology today.Flexible fuel vehicle(FFV)Commercially available.Minimal interest from manufacturers.Hybrid electric vehicle(HEV)Widely commercially available.Plug-in hybrid electric vehicle(PHEV)Widely commercially available.Minimal interest from manufacturers.Battery electric(BEV)Widely commercially available.Hydrogen fuel cell electric(FCEV)Some commercial options,but less developed than alternatives.Commercial options possible within 5 years,especially for high-intensity,long-range use.Natural gas vehicle(NGV)Minimal commercial availability or development.Widely used in some sectors.TABLE 11.AVAILABILITY OF ALTERNATIVE POWERTRAINS ACROSS ROAD TRANSPORT SEGMENTSBuses:Commercially available,but limited market share.MDV:Commercially available,with the number of models expected to increase.Other MDV/HDVs:Minimal interest from manufacturers.HDV:Available for shorter range use.Long range options currently limited but could be available within 5 yearsTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT38How could the uptake of alternative technologies affect e-fuel demand in the road transport sector?Conventional ICEVs dominate current sales in both LDV,MDV and HDV sectors.Many of these vehicles are likely to still be on the roads at least into the 2030s and early 2040s.The decarbonization pathway for road transport in the U.S.is highly uncertain,but most vehicle stock projections expect that ICEVs will continue to be available in 2040,making low carbon fuels including e-fuels,potentially important decarbonization options.What other transport modes can use e-fuels?Outside of road transport,low carbon fuels are identified as the main decarbonization solution in rail,shipping and aviation in the U.S.due to infrastructure and/or technology limitations shown in Table 12.This could drive policymakers to prioritize low carbon fuel supply for these hard-to-abate sectors as seen in later chapters on policy(Section 6),thus reducing availability for road.POWERTRAIN AND FUELSCAN USE E-FUELS?RAILSHIPPINGAVIATIONLow carbon fuelsElectricityLine electrification is most common alternative power source.Batteries could bridge sections which arent electrified.Examples of use for short trips in Europe (up to 25 nautical miles).Very unlikely to be used for deep-sea shipping.Battery electric aircraft limited in size and range.HydrogenHydrogen could bridge sections which arent electrified or operate on non-electrified routes.Possible for short trips,though significant storage space needed for deep-sea shipping.Possible,but range limited by the volume and weight of hydrogen storage needed.CNG or LNGTechnically possible,but no significant current use or development.LNG regularly used in shipping,requires non-fossil LNG to significantly reduce GHG emissions.Possible,but range limited by the volume and weight of natural gas storage needed.TABLE 12.TECHNICAL SUITABILITY OF POWERTRAINS IN OTHER TRANSPORT SECTORS TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT39The environmental performance of low carbon fuels is a critical factor considered in policies focused on transport decarbonization.A fuels lifecycle greenhouse gas(GHG)emission is a key element of this,representing the total GHG emissions generated along the whole fuel supply chain expressed on a CO2 or CO2e(CO2 equivalent)basis.In some markets,this figure,often called the carbon intensity(CI),drives a fuels eligibility for policy support and market value.E-fuels,when used in LDVs,has the potential to achieve up to 75%GHG emissions reduction and 92%reduction when used in HDVs as CNG or compressed e-methane in the near-future.This could be further increased to reach 99%in the future.In addition to the GHG emissions,this section also assesses other environmental impacts of e-fuel production and use.The lifecycle GHG emissions are then compared with other low carbon transportation options to understand which have the highest decarbonization potential.SECTION 3.What are the GHG benefits of e-fuels and how do they compare to other options?SECTION 3:KEY QUESTIONS How do e-fuels lead to GHG savings?What are the well-to-wheel GHG savings of e-fuels now and in the future?How does the well-to wheel GHG savings of e-fuels compare to alternative technologies and drivetrains?What are the other environmental impacts of e-fuels production and use?TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT40GHG emissions shown in this analysis reference the Greenhouse Gases,Regulated Emissions,and Energy Use in Technologies(GREET)model developed by Argonne National Laboratory as far as possible.At the time of the report,given there is no agreed and published methodology for calculating the GHG emissions of e-fuels in the U.S.,and GREET has not been updated to include all the e-fuel pathways considered in this report,an internal ERM GHG model was used to calculate the well-to-wheel emissions for all the production pathways considered in this report,using an energy allocation approach across all fuel products.This model aligns closely with e-fuel GHG calculation methodologies established under relevant policies in Europe like the Renewable Energy Directive(RED)and the Renewable Transport Fuel Obligation(RTFO),which include emissions arising from feedstock,fuel processing,fuel transport and distribution,and fuel combustion.They do not account for emissions that arise from the construction of infrastructures(e.g.solar panels,wind farms)as this emission is expected to be negligible when amortized across a projects lifetime.3.1 HOW DO E-FUELS LEAD TO GHG SAVINGS?The lifecycle GHG emissions of a fuel,or its well-to-wheel emissions,represent emissions that occur during the entire value chain of fuel production,distribution and use.(Figure 3-1)The combustion of e-fuels does not generate net positive emissionsUnlike fossil fuels,the combustion emissions of e-fuels are considered to be zero.This is because:When using CO2 captured from existing industrial sources,it is assumed that this would have been released to the atmosphere anyway.Using this CO2 in e-fuel production effectively recycles this CO2,which is ultimately released at the tailpipe.With DAC,the CO2 is taken directly from the atmosphere,which is released again at the tailpipe.This does not create any additional CO2 emissions.Note that from a carbon accounting perspective,this assumes that the point source CO2 emitters have not claimed any emissions reductions as a result of the CO2 capture as part of any policy compliance programs,such as with emissions trading schemes.However,there are currently no rules in place in the U.S.specifying this requirement.In Europe,carbon accounting rules under the EU Emissions Trading Scheme state that the point source emitter must continue to count,and pay for these emissions,as they will ultimately be released to the atmosphere.E-fuel value chains do not have zero emissionsNevertheless,the well-to-wheel GHG emissions of e-fuels are not zero because emissions can arise from the fuel production process,stemming from the following value chain steps.(Table 13)MethanationMethanol synthesisFermentationAlchohol-to-hydrocarbonsFT synthesis upgradingCo-electrolysisRWGSPartial RWGSSYSTEM WEIGHT BREAKDOWNSTotal Cost of OwnershipRicardo input to be used to define weight inputUTILITY DISTRIBUTION NETWORKService connectionSupply infrastructureCharger equipmentMETERCONDUCTOR(BORING/TRENCHING)EV CHARGEREVPANELUTILITY PAD-MOUNTED TRANSFORMERSYSTEM LEVEL GHGBEVPowertrainRaw material to finished productICEVHEVBEVSyngasGreenhydrogenand CO2Vehicle manufacturing and assemblyWell-to-wheelFEEDSTOCK SOURCINGFUELPRODUCTIONTRANSPORTDISTRIBUTIONCOMBUSTIONDrop-ine-fuels*E-thanol and e-methanol are not drop-in fuels but can be further converting into drop-insFIGURE 3-1.LIFECYCLE/WELL-TO-WHEEL GHG EMISSIONS OF E-FUELSTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT41E-fuels produced using renewable electricity could achieve significant GHG savings as their energy content will come from nearly zero emission sources such as wind or solar.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT42E-fuels achieve the highest GHG savings when produced using additional renewable electricityE-fuels produced using renewable electricity could achieve significant GHG savings as their energy content will come from nearly zero emission sources such as wind or solar.However,concerns over the significant renewable electricity generation capacity required to enable production of e-fuels has raised concerns over the role of e-fuels in decarbonizing the transport industry.Concern 1:E-fuels demand for renewable electricity could divert it from existing uses.This is a problem because increasing electricity demand overall could lead to a net increase in GHG emissions across the economy,if fossil fuel is used to meet this additional demand.Concern 2:E-fuels are a less efficient way to decarbonize the transport sector as renewable electricity can be used directly in BEVs with fewer energy losses in the supply chain.This is shown in Figure 3-2,which compares potential uses of renewable electricity and the emissions reduced per kWh,calculated on a lifecycle basis for displaced fuels,not including embodied emissions in infrastructure.A higher value signifies more emissions savings per unit of renewable electricity used.Of the applications shown,the highest emissions reductions in the U.S.result from displacing coal electricity generation,followed by powering BEVs,followed by displacing natural gas electricity generation,then FCEVs,then e-fuels produced using renewable energies(i.e.for both hydrogen and fuel production).TABLE 13:SOURCES OF EMISSIONS FROM THE LIFECYCLE OF E-FUELSPRODUCTION VALUE CHAINSOURCES OF EMISSIONSElectricity for e-fuel productionThe GHG impact is only negligible if e-fuel is produced from renewable electricity meeting incrementality,deliverability and temporal correlation(see below).Grid electricity could be used to supplement for hours where renewable electricity is not available.However,this would impact the GHG emissions of the final fuel.CO2 captureEnergy is expended to capture,condition and transport CO2 feedstocks,which can come from fossil or renewable sources.Energy(heat&electricity)sources for fuel processingE-fuel synthesis processes often take place under high temperature and pressure conditions.The energy requirements for this could be met by fossil or renewable sources.Fuel transportation and distributionThe transport of e-fuels to their final users can be carried out via pipelines or trucks,which could generate GHG emissions if using fossil fuels.FIGURE 3-2.LIFECYCLE EMISSIONS AVOIDED USING RENEWABLE ELECTRICITY LOREM IPSUMRgCO2e avoided per kWhRenewable electricity(kWh)gCO2e avoided per kWhrenewable electricityDIESEL POOLGASOLINE POOLDisplace coalin gridBEVDisplace naturalgas in gridFCEVE-gasoline$54,568$69,262200,000 MILES(average US electricity mix)19,000 MILES(states with low carbon electricity)20302050204020112014201320152012201620172018203020502040203020502040Diesel ICEDiesel hybrid(4.8 kWh)Diesel PHEV(38 kWh)BEV(345 kWh)Diesel ICEDiesel PHEV(38 kWh)BEV(Optare)(92 kWh)BEV(Wrightbus)(150 kWh)BEV(BYD)(324 kWh)26.629.232.835.839.441.439.941.241.311004006008001,0001,200See Appendix B for assumptions.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT43However,as discussed in Section 2,technical and infrastructure requirements could limit which vehicles can be electrified and how quickly BEVs or other solutions are adopted.BEVs are the highest efficiency route from renewable electricity to miles travelled,but there is likely to be continued demand for liquid fuels while BEVs are rolled out,and in sectors harder to electrify.More broadly,these concerns stem from the view that renewable electricity is a limited resource,for which e-fuels production could compete with other important end uses.In practice,the technical potential of renewable electricity is unlikely to be a constraint(this is covered in more detail in Section 4-3).The more important question relates to diversion of the limited renewable electricity generation capacity already in place(concern 1).As a result,policymakers in the U.S.and EU are aiming to implement rules to ensure e-fuels projects a re developed from additional renewable electricity capacity,to avoid negative impacts on the wider electricity system.35 DOE(2023),National Transmission Needs Study.Available from:linkKEY CONSIDERATIONS TO ENSURE SUSTAINABLE DEVELOPMENT OF E-FUELSTo minimize the risk of e-fuels generating negative impacts on the wider electricity system,hydrogen and e-fuel policies,including very recently the Clean Hydrogen Production TC(45V),require renewable electricity used in green hydrogen production to meet 3 sustainability criteria:incrementality,deliverability and temporal correlation.These 3 pillars are designed to ensure the renewable electricity to produce hydrogen comes from additional capacity,rather than from existing capacity with competing demand.This includes preventing claims that renewable electricity is being used for hydrogen production in hours or locations when renewable electricity is not available.1.Incrementality:Clean power generators that began commercial operations within three years of a hydrogen facility being placed into service are considered new sources of clean power.Generation resulting from a generators newly added capacity(“uprates”)are also considered new sources of clean power.2.Deliverability:Clean power must be sourced from the same region as the hydrogen producer,as derived from Department of Energy(DOE)s 2023 National Transmission Needs Study.353.Temporal Correlation:New,deliverable clean power will generally need to be matched to production on an hourly basis meaning that the claimed generation must occur within the same hour that the electrolyzer is operating.The proposed rules allow annual matching until 2028 when hourly tracking systems are expected to be more widely available.Renewable electricity meeting these sustainability criteria could be directly supplied to hydrogen plants through co-location or sourced from Power Purchase Agreements or other purchasing schemes.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT44E-fuels producers relying on tax credits(TCs)for hydrogen production will be required to meet these rules.However,these criteria are not currently included within the rules for the 45Z Clean Fuels Production credit,for which no specific guidance currently exists for the calculation of e-fuels GHG emissions in the U.S.This means that an e-fuels producer not claiming hydrogen TCs would not necessarily need to meet these important criteria.3.2 WHAT ARE THE WELL-TO-WHEEL GHG SAVINGS OF E-FUELS NOW AND IN THE FUTURE?The lifecycle GHG emissions of e-fuels are largely determined by the amount of energy required for fuel production,which is dictated by the processing chemistry of production pathways.Production plant configuration for key technology blocks such as carbon capture,electrolyzer,etc.can also significantly impact fuel emissions.This includes design choices such as the source of CO2 and energy(i.e.electricity and heat)used,which could be influenced by policy requirements and commercial viability.This section assesses the lifecycle(i.e.well-to-wheel)GHG emissions of e-fuel pathways covered in Section 1 and discusses key differences across the technologies under three scenarios and operating parameters as defined in Table 14.36 EIA:AEO,(2023),U.S.Energy-Related Carbon Dioxide Emissions(2022).Available from:linkTABLE 14.GHG EMISSION ASSESSMENT SCENARIO PARAMETERSPARAMETERSDESCRIPTIONELECTRICITY FOR H2 PRODUCTIONCO2 SOURCEELECTRICITY FOR FUEL PROCESSINGHEAT FOR FUEL PROCESSINGBase caseAdditional renewable energy sources that meet incrementality,deliverability and temporal correlation requirements are costly,so this type of renewable electricity is only used for hydrogen production.Other processes use grid electricity(using 2022 U.S.electricity generation CI)36 and natural gas where heat is required.This scenario is representative of e-fuels production configuration in the near future,if policy does not put requirements on other electricity use in the production process.Renewable electricityPoint source CO2 from cement plantsHeat:Heat integration from fuel processing,supplemented with natural gasElectricity:Grid electricityGrid electricityNatural gasLow GHG emissions caseRenewable energy is competitive with grid electricity and natural gas,or is required by policy,and so is used for all operations.This scenario shows the maximum GHG saving potential of e-fuels.Renewable electricityDAC using renewable electricityHeat:Heat integration from fuel processing,supplemented with natural gasElectricity:Renewable electricityRenewable electricityRenewable energy(Electricity or hydrogen)Grid electricity caseSupplying uninterrupted additional renewable electricity could be costly,therefore,it is likely that e-fuel plants will supplement with other grid electricity for part of the time to ensure continuous fuel production.This will have an impact on GHG emission of the fuel.This scenario is used to evaluates what the maximum CI the average electricity can be in order to produce e-fuels that meet the 50 kgCO2e/mmBTU(or 47.4gCO2e/MJ)threshold set under the 45Z Clean Fuel Production TC.Partial grid electricityPoint source CO2 from cement plantsHeat:Heat integration from fuel processing,supplemented with natural gasElectricity:Grid electricityGrid electricityNatural gasTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT453.2.1 BASE CASE EMISSIONSIn the base case,most e-fuels suitable for road transport can generate GHG emission savings when additional renewable electricity is used only for hydrogen production.This is representative of early e-fuels plants,which are likely to rely on natural gas and grid electricity for process energy.Aside from the ETJ pathway,all pathways produce e-fuels with well-to-wheel emissions that are lower than the fossil fuel baseline emissions of gasoline of 93 gCO2e/MJ(Figure 3-3).The most GHG reduction potential is seen with e-methane,which could potentially achieve more than 90%GHG savings when used in CNG vehicles.Drop-in fuels produced through RWGS FT,methanol to gasoline or jet pathways could achieve the highest GHG savings of around 70-75%.However,under a conservative carbon yield assumption(the carbon yield of converting CO2 to ethanol via pRWGS and syngas fermentation steps is assumed to be 75%for this study.Some developers claim it to be as high as 90%,but this has yet to be proven),e-fuels produced via ETJ exceeds the GHG emissions of its fossil comparator in the base case mainly due to its reliance on natural gas as a heat source.For alcohols,e-methanol in the base case could generate about 75%GHG savings whereas e-ethanol is shown to only achieve around 15%GHG savings.An internal GHG assessment model to calculate the lifecycle emissions saving potential of each fuel pathway following key assumptions stated above under each scenario.The GHG emissions for each pathway are broken into four categories:hydrogen production,CO2 capture,fuel synthesis and fuel transport and distribution.FIGURE 3-3.WELL-TO-WHEEL GHG EMISSIONS FOR E-FUEL PATHWAYS FOR NEAR-FUTURE PRODUCTION CONFIGURATIONS.gCO2e/MJE-FUEL PRODUCTION PATHWAYSRWGS-FTMTGMTJETJE-ethanolE-methanolE-methane$54,568$69,262200,000 MILES(average US electricity mix)19,000 MILES(states with low carbon electricity)20302050204020112014201320152012201620172018203020502040203020502040Diesel ICEDiesel hybrid(4.8 kWh)Diesel PHEV(38 kWh)BEV(345 kWh)Diesel ICEDiesel PHEV(38 kWh)BEV(Optare)(92 kWh)BEV(Wrightbus)(150 kWh)BEV(BYD)(324 kWh)26.629.232.835.839.441.439.941.241.3110406080100E-gasoline,E-dieselE-alcoholsE-CNGH2 productionCO2 CaptureFuel ProcessingTransport and distributionFossil ComparitorTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT46Hydrogen productionHydrogen production is assumed to have negligible GHG emissions when renewable electricity that meets incrementality,deliverability and temporal correlation is used.Fuel processingDownstream from hydrogen production,fuel processing also consumes energy which is used to sustain e-fuel synthesis processes that take place under high temperature and pressure conditions,and to support auxiliary operations throughout the plant.In the base case,the energy demand from fuels synthesis is assumed to be met by natural gas and grid electricity.Some pathways generate waste heat,such as RWGS FT and methanol synthesis which are exothermic reactions.This waste heat is reused to reduce natural gas demand.Conversely,the ethanol and ethanol to jet pathways have the highest natural gas demand and no waste heat is produced during fuel synthesis,resulting in high emissions.CO2 captureThe base case assumes CO2 is captured from industrial or biogenic point source waste gas streams with low CO2 concentrations,such as flue gas from cement plants.Emissions associated with CO2 capture is related to the level of heat integration available to each pathway and its CO2 requirements.Separation of CO2 from low concentration streams requires heat,which is assumed to come from downstream e-fuel production if excess heat is available from fuel synthesis.This is achieved through the co-location of CO2 source and the e-fuel production plant.In pathways where excess heat is unavailable,natural gas is used to meet head demand,which leads to additional emissions.This results in the RWGS FT pathway having the lowest emissions associated with CO2 capture,assuming waste heat can be utilized for this process.Energy required for CO2 capture is also determined by the pathways CO2 requirements.Comparatively,ethanol pathways require approximately 40%more CO2 than RWGS FT and methanol pathways.Transport and distribution supply chainThe transport and distribution logistics vary by production pathway and fuel properties.Liquid fuels can be transported via trucks or pipelines,whereas gaseous fuels(e-methane)require additional compression before being delivered to refueling stations.This contributes to higher GHG emissions in e-methane pathways.For all other pathways,transport and distribution emissions account for a negligible part of lifecycle GHG emissions compared to CO2 capture and fuels processing.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT473.2.2 LOW GHG EMISSIONS CASEIn the low case all energy used during fuel production comes from renewable sources.It is assumed that DAC will be used to source CO2 and that it will also use renewable electricity.Similar to hydrogen production,these renewable sources should also come from additional capacities to minimize system wide negative GHG impacts.However,without a GHG methodology,it is currently not known whether this will be required.This scenario also assumes that fossil natural gas consumption is replaced by renewable heat sources such as green hydrogen or renewable natural gas.E-fuel pathways under this low emission scenario generates 97 to 99%GHG savings compared with fossil fuels(Figure 3-4).Here,the main source of emission arises from fossil fuel consumed in the downstream transport and distribution of fuels,which can be reduced further as the fleets37 EIA(2023),Electricity:Total Electricity Generation by Fuel:Renewable Sources.Available from:link38 International Renewable Energy Agency(2023),Country Rankings.Available at:linkdecarbonize.This emission for CNG is higher as additional energy is required to compress this fuel.The ability to achieve this GHG reduction potential is dependent on renewable energy availability and affordability.Renewable energy availability and affordabilityRenewable electricity and heat sources such as green hydrogen or renewable natural gas are currently supply constrained.In terms of renewable electricity,supply is projected to grow significantly from the 890 TWh that is available today.37,38 This electricity could support the production capacity of green hydrogen which can be used as a clean heat source for e-fuel production.Competition for this supply,however,will dictate its price.This price,together with the product value,will determine whether it will be economically viable to use renewable energy for all processes.FIGURE 3-4.WELL-TO-WHEEL GHG EMISSIONS FOR E-FUEL PATHWAYS REPRESENTING FUTURE PRODUCTION CONFIGURATIONS.gCO2e/MJE-FUEL PRODUCTION PATHWAYSRWGS-FTMTGMTJETJE-ethanolE-methanolE-methane$54,568$69,262200,000 MILES(average US electricity mix)19,000 MILES(states with low carbon electricity)20302050204020112014201320152012201620172018203020502040203020502040Diesel ICEDiesel hybrid(4.8 kWh)Diesel PHEV(38 kWh)BEV(345 kWh)Diesel ICEDiesel PHEV(38 kWh)BEV(Optare)(92 kWh)BEV(Wrightbus)(150 kWh)BEV(BYD)(324 kWh)26.629.232.835.839.441.439.941.241.3110406080100E-gasoline,E-dieselE-alcoholsE-CNGH2 productionCO2 CaptureFuel ProcessingTransport and distributionFossil ComparitorTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT48Currently,policy is the main driver to reduce the GHG emissions of fuels.As explained in detail in Section 6,most policies set GHG thresholds to determine the eligibility of fuels and some policies offer additional support for fuels with high GHG emission savings.This means that e-fuel producers could be motivated to source renewable energy for fuel processing to meet the aforementioned GHG threshold,in order to benefit from certain clean fuel policies.This could be desirable to pathways with poor GHG emission performances such as e-ethanol or e-ethanol-to-jet as shown in the base case scenario.However,the willingness to purchase additional renewable energy beyond what is required(i.e.renewable electricity for hydrogen)is highly influenced by the economics of sourcing cost and additional policy support.The interaction between the two will be investigated further in Section 6.3.2.3 PARTIAL GRID ELECTRICITY CASEAt the time of this report,the definition of e-fuels and the GHG methodology to be used for them has not been established under any fuel policies in the U.S.,such as the 45Z Clean Fuel Production TCs or California LCFS.Therefore,it is unclear how sourcing grid electricity would impact the GHG emissions of the resulting e-fuels.If the average U.S.electricity emission factor is used to calculate the lifecycle emissions of e-fuels,its CI must be below approximately 36 gCO2e/kWh to meet the GHG threshold for drop-in fuels set under the 45Z Clean Fuel Production TC(50 kgCO2e/mmBTU or 47.4 gCO2e/MJ.39 In other words,around 10%of the electricity used in electrolyzers in e-fuels production could come from the grid today,while still meeting the definition of low carbon fuels.This could be different if alternative GHG calculation methodologies are implemented.39 This analysis builds off the assumptions of the base case scenario and assumes the energy sources for fuel production come from natural gas and grid electricity,and is applicable to the RWGS FT,and methanol-to-gasoline and-jet(MTG/J)pathways.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORTTRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT49TABLE 15.CURRENT AND 2040 GREENHOUSE GAS EMISSIONS FACTORS FOR ENERGY SOURCES FUEL TYPECURRENT EMISSIONS FACTOR(gCO2e/kWh)EMISSIONS FACTOR IN 2040(gCO2e/kWh)SOURCE/ASSUMPTIONGasoline and Diesel335.1335.1Renewable Fuel Standard fossil comparatorE-gasoline and E-dieselHigh:345.0Average:159.8Low:84.9High:2.5Average:2.3Low:2.3Values from pathways in Section 3.2.Average taken as average for the four diesel/gasoline pathways.Bio-gasolineHigh:218.7Average:165.2Low:85.1High:218.7Average:165.2Low:85.1Renewable gasoline made from forestry residues or vegetable oil(pathways approved by the California Low Carbon Fuel Standard(CA LCFS),2023)Renewable DieselHigh:214.3Average:141.2Low:53.2High:214.3Average:141.2Low:53.2Renewable diesel made from waste oil or vegetable oil(pathways approved by the CA LCFS,2023)Grid electricityHigh:722.1Average:362.1Low:106.1High:303.4Average:152.2Low:44.6EPA eGrid data for 2023,EIA AEO 2023 for 2040 average,with high and low reduced proportionally from 2023(reference case)linkRenewable electricity00Production emissions of solar panels/wind turbines not consideredHydrogenHigh:120.0Average:60.0Low:0High:120.0Average:60.0Low:02023:Range of emissions intensity of hydrogen to be classed as“clean hydrogen”.(DOE)linkMethane284.4284.4As reported by the CA LCFS(2023)E-methaneHigh:28.7Average:26.1Low:23.5High:11.6Average:10.5Low:9.5Average value from Section 3.2.High and low values 10%higher/lower than average.Landfill BiogasHigh:83.0Average:53.0Low:30.0High:83.0Average:53.0Low:30.0Emissions intensity of biogas from landfill(pathways approved by the CA LCFS,2023)Manure BiogasHigh:-543Average:-1127Low:-1919High:-543Average:-1127Low:-1919Emissions intensity of biogas from manure(pathways approved by the CA LCFS,2023)3.3 HOW DO THE WELL-TO-WHEEL GHG EMISSIONS OF E-FUELS COMPARE TO ALTERNATIVE TECHNOLOGIES?Using the above GHG emissions analysis,this section compares the current and 2040 well-to-wheel emissions per mile travelled for e-fuels,biofuels and other vehicle powertrains introduced in Section 2.2.Emissions associated with vehicle manufacturing are not considered here because they are considered to be insignificant relative to emissions from fuel use see Appendix E for further details.The emissions factors used in this section are listed in Table 15.TRANSPORTATION ENERGY INSTITUTE|EVALUATING THE VIABILITY OF COMMERCIALLY DEPLOYING E-FUELS IN ROAD TRANSPORT503.3.1 HOW DO EMISSIONS PER MILE COMPARE TODAY?Emission in LDVs The GHG performance of vehicles can vary significantly as seen in Figure 3-5.Here,the range represents the varying degree of GHG savings that could be achieved by different production methods and/or feedstocks.For example,the top-end of e-gasoline represents e-fuels produced via e-ETJ pathways,and the bottom-end refers to GHG savings that could be achieve via RWGS FT routes.The line within each box represents the average emissions across the different production pathways and/or energy sources considered for e-fuels and the other energy sources.The key observations are summarized below.E-gasoline from most production pathways could achieve significant GHG savings(i.e.up to 75%lower GHG emissions per mile compared to fossil gasoline)when produced using additional renewable electricity.Some pathways may lead to a net increase in emissions given likely plant configuration in the near future.E-gasoline in a HEV can generate further savings of up to 85%of GHG emissions compared to a gasoline ICE car(75%less compared to fossil gasoline in a HEV),due
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Charging ahead:accelerating the roll-out of EU electric vehicle charging infrastructureAPRIL 2024TABLE OF CONTENTSEXECUTIVE SUMMARY 02THE EUROPEAN PLUG-IN LANDSCAPE 05 AFIR 05 Public charging points:a long way to go 05 Get connected:Type 2 and CCS connectors dominate in Europe 07 Fast or slow?Its a two-speed race 08 Out of sync:charging point deployment and BEV uptake 09 Distribution of charging points 10 Electric cars per charger 11 Other indicators 11 Are we there yet?The long,slow journey to public charge point rollout 12 Charge point operators(CPOs)13A GLOBAL COMPARISON 13 China 13 US 14CLOSING THOUGHTS 15EXECUTIVE SUMMARYTo meet ambitious CO2 targets for cars and vans,sales of electrically chargeable vehicles(ECVs)will need to pick up massively in all EU countries.However,ECV sales only represent part of the story.Appropriate charging infrastructure is required for both types of ECVs:battery electric vehicles(BEVs)and plug-in hybrids(PHEVs).The OECD says access to charging for ECVs is“a significant concern,”1 and the IEA underlines the critical importance of public charging infrastructure for widespread adoption,noting that growth in EV sales relies on accessible and affordable private and public charging infrastructure.2The EUs 2016 low-emission mobility strategy called for EV charging to be as easy as filling a conventional vehicle tank,so that EV drivers can travel seamlessly across the EU.3 This means that the public charging network needs to be able to support all electric car drivers in the way that the traditional refuelling network supports combustion engine car drivers,ie it should be distributed evenly along motorways and major roads,in towns and villages,right across the EU.This ACEA Automotive Insights report examines the status of public charging infrastructure for light-duty ECVs across Europe4,taking a snapshot of the situation at the end of 2023.1.https:/www.oecd-ilibrary.org/environment/how-green-is-household-behaviour_2bbbb663-en2.https:/www.iea.org/reports/global-ev-outlook-2023/trends-in-charging-infrastructure#3.https:/op.europa.eu/webpub/eca/special-reports/electrical-recharging-5-2021/en/4.This report is about public charging points for electrically chargeable cars and vans,located in public places for public use.It does not discuss private charging points such as home and off-street charging,workplace charging,or hotels and private car parks.It also does not cover hydrogen refuelling stations across the EU,required for fuel-cell electric vehicles which are also zero-emissions.Finally,it also not consider charging infrastructure for heavy-duty vehicles.310 key takeaways1 There were 632,423 public charging points available across the EU at the end of 2023,and around 3 million BEVs on the road.2 In 2023,a total of around 153,000 new public charging points was installed.3 The European Commission is calling for 3.5 million charging points by 2030 to support the level of vehicle electrification necessary to reach the proposed 55%CO2 reduction for passenger cars.5 Reaching this target would require the installation of nearly 2.9 million public charging points in the next seven years.Thats almost 410,000 per year,or 7,900 per week.4 ACEAs projections suggest a significantly higher demand,estimating the necessity of 8.8 million charging points by 2030.Reaching this would require 1.2 million chargers to be installed per year,or 22,438 per week.5 Over the past seven years,sales of BEVs have outpaced the growth of the charging point network by more than threefold.Between 2017 and 2023,electric car sales increased over 18 times,while the number of public chargers in the EU grew merely sixfold during the same period.6 While some countries are powering ahead when it comes to infrastructure rollout,the majority are lagging behind.Indeed,just three EU countries covering over 20%of the EUs surface area the Netherlands,France,and Germany are home to almost two-thirds(61%)of all EU charging points.The other third(39%)of all chargers is distributed throughout 24 member states,covering almost 80%of the regions surface area.7 There is a strong correlation between public charging point availability and BEVs sales.The list of top five countries with the highest BEV sales is broadly similar to that of the countries with the most chargers:Germany,France,the Netherlands and Italy feature on both top 5 lists.8 Charging speed is also a major issue across the continent,as fast chargers(with a capacity of more than 22kW)make up a fraction of the EU total.Only around one in seven of all chargers(13.5%)is capable of fast charging.The majority are normal chargers,with a capacity of 22kW or less(including many common-or-garden,low-capacity power sockets).9 At the end of 2023,there were 29 BEVs per fast charger in the EU,and 53 BEV PHEVs per fast charger.10 Governments across the EU need to ramp up investments in charging infrastructure,and should swiftly implement the Alternative Fuels Infrastructure Regulation(AFIR)bearing in mind that it sets minimum requirements only.At the same time,the European Alternative Fuels Observatory(EAFO)must ensure a robust monitoring system that incentivises member states to deploy infrastructure faster.5.https:/ec.europa.eu/commission/presscorner/detail/en/SPEECH_22_77854THE EUROPEAN PLUG-IN LANDSCAPEA comprehensive public charging network will be essential to support the anticipated surge in EV demand as the European Union phases out the sale of vehicles with internal combustion engines.Under the European Green Deal and the European Commissions Fit for 55 legislative package,the EU is targeting carbon neutrality by 2050,and a 55%reduction in emissions by 2030.The CO2 regulation for cars and vans sets a 100%CO2 reduction target for 2035.To meet these ambitious targets,sales of electrically-chargeable vehicles(ECVs)including battery electric(BEVs)and plug-in hybrid electric vehicles(PHEVs)will need to pick up massively.The availability of public charging infrastructure is essential for this to happen.AFIRThe Alternative Fuels Infrastructure Regulation(AFIR)is a new law governing public charging point deployment across Europe.This provides for specific targets that will have to be met in 2025 and 2030.In terms of passenger cars and light commercial vehicles,AFIR aims to:increase the level of power needed for public charging;align the implementation timeline of the Trans-European Transport(TEN-T)core network with that of the TEN-T comprehensive network,while increasing the overall power installed per charging point;introduce a density parameter for charging points;andstimulate the deployment of fast charging stations.AFIR requires that from 2025,fast recharging stations of at least 150kW must be installed every 60 km along the EUs main transport corridors,the so-called Trans-European Transport Network(TEN-T).It is important to note that AFIR sets“minimum requirements”only,and that its targets remain well below what would is necessary to meet CO2 targets.Public charging points:a long way to goAt the end of 2023,there were 632,423 public charging points across Europe.This falls far short of the number needed.The European Commission is calling for 3.5 million charging points by 2030 to support the level of vehicle electrification necessary to reach the proposed 55%CO2 reduction for passenger cars.ACEAs estimates indicate a much higher demand:8.8 million charging points will be needed by 2030,increasing to 18.8 million by 2035.There is a significant difference between the Commission and ACEA estimations of the number of charging points needed by 2030 due to several factors:the Commission underestimates the number of vehicles on EU roads that will need a charger by 2030:their estimate is 30 million,versus 65 million as estimated by Strategy&and Fraunhofer ISI and used in ACEA calculations.6 ACEA figures include battery-electric vans,which are primarily charged using the same infrastructure as cars,as well as plug-in hybrid electric vehicles,whereas the Commission only counts battery-electric cars;56.https:/www.isi.fraunhofer.de/content/dam/isi/dokumente/cce/2023/2023-12-20_Strategy_Fraunhofer ISI - Fleet Electrification Study.pdfCHARGING POINTS PER COUNTRY,PLUS PERCENTAGE OF EU TOTAL 2023CountryChargers%of EU totalCountryChargers%of EU totalAustria 18,637 2.9%Italy41,1146.5lgium 44,363 7.0%Latvia5350.1%Bulgaria1,6240.3%Lithuania1,3130.2%Croatia1,0740.2%Luxembourg2,3230.4%Cyprus3290.1%Malta1010.0%Czechia4,6640.7%Netherlands144,45322.8nmark23,0723.6%Poland6,1021.0%Estonia6830.1%Portugal7,3061.2%Finland11,2471.8%Romania2,7540.4%France119,25518.9%Slovakia2,3800.4%Germany120,62519.1%Slovenia1,6080.3%Greece3,1660.5%Spain30,3854.8%Hungary3,3190.5%Sweden37,1665.9%Ireland2,8250.4%EU 632,423 100%the Commission assumes significantly lower vehicle energy consumption compared to recent real-world monitoring figures(14.8 kWh/100 km for battery-electric vehicles(BEV)and 19.2kWh/100km for plug-in hybrid electric vehicles(PHEV),versus 20 kWh/100km for BEV and PHEV by ACEA);and the European Commission acknowledges that the Alternative Fuels Infrastructure Regulation(AFIR)requirements represent the minimum coverage needed,and will be insufficient to enable the CO2 targets for cars and vans to be met.Number of charging points(end-2023)632,423New installations in 2023153,027Charging points required to reach 3.5 million by 2030,as of end-2023(European Commission requirements)2,867,577Charging points required to reach 8.8 million by 2030,as of end-2023(ACEA real estimates)8,167,577Number of charging points installed by 2030 based on new installations in 20231,550,585(With a target of 3.5 million charging points,this leaves a shortfall of 1.9 million.7.2 million with a target of 8.8 million charging points)Annual installations requiredTo reach 3.5 million:409,654(or 7,878 per week)To reach 8.8 million:1.2 million(or 22,438 per week)SOURCE:EAFO SOURCE:ACEA,EAFO,EUROPEAN COMMISSION 6To reach 3.5 million by 2030,nearly 2.9 million public charging points will need to be installed in the next seven years,equivalent to almost 410,000 per year,or 7,900 per week.For context,just 153,027 new public EV charging points were installed in 2023.This should increase to 1.2 million per year,or 22,438 per week,if we consider ACEAs 2030 target of 8.8 million charging points.Based on the number of installations in 2023,the public charging network will stand at just 1.6 million units by 2030.These numbers assume that those public charging points already in place are maintained and remain in place.Get connected:Type 2 and CCS connectors dominate in EuropePublic charging points7 in Europe are typically equipped with one of two charging connector types:Type 2 is the predominant connector,with the Combined Charging System(CCS)occupying most of the remaining market share.The Type 2 connector has a universal socket capable of delivering up to 22 kW for slow and fast charging.CCS connectors have a combined AC and DC port used for fast or ultra-fast charging,with a maximum power output of up to 350 kW and the capability to fully charge a BEV in 15 minutes.Total number of publicly accessible AC and DC recharging points across the EU,according to the AFIR classification at end-2023 Slow DC charging point(P 50kW)Fast DC charging point(50kW P 150kW)Ultra-fast DC charging point(P 150kW)Slow AC charging point(P 22kW)7.Recharging points can contain several connectors;recharging stations can house several recharging points;and recharging pools are usually home to several recharging stations.However,only one connector per recharging point can be active for recharging at a time.For more detail:https:/alternative-fuels-observatory.ec.europa.eu/general-information/recharging-systemsAC CHARGING POINTS Total number of publicly accessible AC charging points,according to the AFIR classificationDC CHARGING POINTS Total number of publicly accessible DC charging points,according to the AFIR classification202020202021202120222022202320230020,000100,000200,000300,000400,000500,000600,00040,00060,00080,000100,0007SOURCE:EAFO SOURCE:EAFO Fast or slow?Its a two-speed raceTypically,AC chargers are used for slow charging and are best suited to home and workplace charging,as well as public spaces such as supermarkets and leisure facilities.DC chargers are most commonly used for fast charging,usually on motorways and main highways,allowing drivers on long journeys to charge quickly en route rather than overnight.But public fast chargers are not exclusive to long distance and motorway driving;their presence can help to alleviate range anxiety,and act as an enabler for those without private charging options to consider to buy an ECV.Both AC and DC chargers are suitable for public charging.AC chargers dominate,but of the 632,423 charging points available across the EU at the end of 2023,only around one in seven(13.5%)is capable of fast charging(with a capacity of more than 22kW).The majority are normal chargers with a capacity of 22kW or less.PUBLIC CHARGING POINTS IN THE EU BY COUNTRY AND TYPE(AC/DC)2023CountryAC DCCountryAC DCAustria15,2293,408Italy35,1955,919Belgium41,9032,460Latvia296239Bulgaria1,165459Lithuania1,039274Croatia675399Luxembourg2,143180Cyprus30623Malta1010Czechia3,3891,275Netherlands140,5613,892Denmark20,8962,176Poland4,4771,625Estonia339344Portugal5,5821,724Finland8,5082,739Romania1,817937France100,76718,488Slovakia1,690690Germany97,70422,921Slovenia1,346262Greece2,950216Spain24,9315,454Hungary2,742577Sweden32,4134,753Ireland2,355470EU550,51981,904SOURCE:EAFO 8 AC DCOut of sync:Charging point deployment and BEV uptakeThe rate of installation of charging points is clearly slower than the sales of battery electric cars.In 2023,BEVs represented 14.6%of EU new car sales,with plug-in hybrids accounting for 7.7%,according to ACEA data.The share of battery electric cars is expected to reach almost 30%of the European market by 2025 and to exceed 70%by 2030.8 Over the past seven years,sales of BEVs have outpaced the growth of the charging point network by more than threefold.Between 2017 and 2023,electric car sales increased over 18 times,while the number of public chargers in the EU grew merely sixfold during the same period.Charging points Battery electric carsPUBLIC CHARGING POINTS IN THE EU BY TYPE(AC/DC)CHARGING POINTS DEPLOYMENT VERSUS SALES OF BATTERY ELECTRIC CARS8.https:/www.acea.auto/news/electrification-trends-worldwide/0100,000200,000300,000400,000500,000600,000700,0000200,000400,000600,000800,0001,000,0001,200,0001,400,0001,600,0002017201820192020202120222023Charging points:18-fold increase since 20172020 Q12020 Q22020 Q32020 Q42021 Q12021 Q22021 Q32021 Q42022 Q12022 Q22022 Q32022 Q42023 Q12023 Q22023 Q32023 Q4Battery electric cars:18-fold increase since 2017Charging points:6-fold increase since 20179SOURCE:EAFO SOURCE:ACEA,EAFO Distribution of charging pointsThe strategic placement of charging infrastructure is essential to ensure all customers across Europe feel sufficiently supported in choosing an EV as their next vehicle.However,just three EU countries Netherlands(144,453 charging points),France(119,255)and Germany(120,625)are home to almost two-thirds(61%)of all EU charging points.These countries make up 22%of the entire EU surface area.The Netherlands the country with the highest share of infrastructure has over 52 times more charging points than Romania(2,754),which is roughly seven times bigger.The other 39%(over one third)of all chargers are scattered throughout the remaining 78%of the regions surface area.In 2023,the top five countries with the most EV charging points in the EU were the Netherlands,Germany,France,Belgium,and Italy.The five countries with the fewest public charging points in 2023 were Croatia,Estonia,Latvia,Cyprus,and Malta(among Europes smallest countries).TOP 5:countries with MOST charging pointsTOP 5:countries with LEAST charging points Netherlands144,453 Croatia1,074 Germany120,625 Estonia683 France119,255 Latvia535 Belgium44,363 Cyprus329 Italy41,114 Malta101DISTRIBUTION OF ELECTRIC CAR CHARGING POINTS ACROSS THE EU 61%of all charging points are concentrated in only three EU countries02,0005,00025,00050,000150,000Number of charging points,202319#%SOURCE:EAFO 10SOURCE:EAFO Electric cars per chargerThere are approximately 3 million BEVs on the road in the EU for 632,423 public charging points.That equates to approximately 5 BEVs per public charging point.Of course,as the number of BEVs increases,the ratio of BEVs per charging points will increase,bearing in mind that BEVs are forecast to account for 30%of the market by 2025,and 70%by 2030.It is important to note that PHEVs also use public charging points,increasing the number of vehicles per charger.The EU recommends one public charge point for 10 BEVs.Public fast chargers,especially those located along motorways,enable longer journeys,and can address range anxiety,a barrier to EV adoption.At the end of 2023,there were 29 BEV cars on road per fast charger in the EU,and 53 BEV PHEV cars per fast charger.Other indicators Looking at other indicators,it is evident that the BEV share is heavily correlated with the availability of charging points.Several countries boasting the highest share of BEV cars on the road also rank among the top five in other indicators,such as the number of charging points per 1,000 inhabitants or per 10 km of road.For instance,Denmark,leading the EU countries in BEV adoption,also ranks second in the number of charging points per inhabitant,with almost four per 1,000 inhabitants,and fourth in the number of charging points per 10 km of road,with over three.BEV cars per fast charger BEV PHEV cars per fast chargerNUMBER OF ELECTRICALLY CHARGEABLE CAR PER FAST CHARGER(P 22KW)By country,2023020406080100120140160LuxembourgIrelandBelgiumHungarySwedenNetherlandsGermanyFinlandEuropean UnionFranceGreecePortugalPolandSloveniaAustriaDenmarkCyprusRomaniaSpainLithuaniaLatviaCroatiaCzechiaItalySlovakiaEstonia11SOURCE:EAFO BEV cars on the road(%share,2022)New BEV cars sold(%share,2023)Charging points per 1,000 inhabitants(2023)Charging points per 10 km of road(2023)EU 1.2%EU 14.6%EU 1.4EU average 1.3TOP FIVE COUNTRIES Denmark 4.0%Sweden 4.0%Netherlands 3.7%Luxembourg 3.1%Austria 2.1%Sweden 38.7nmark 36.3%Finland 33.8%Netherlands 30.8%Luxembourg 22.5%Netherlands 8.2 Denmark3.9 Belgium3.8 Luxembourg 3.6 Sweden3.6 Luxembourg 8.0 Netherlands 7.7 Portugal5.1 Denmark3.1 Belgium2.9BOTTOM FIVE COUNTRIES Czechia 0.2%Slovakia 0.2%Poland 0.2%Cyprus 0.1%Greece 0.1%Italy 4.2%Poland 3.6%Czechia 3.0%Croatia 2.8%Slovakia 2.7%Croatia0.3 Bulgaria0.2 Malta0.2 Poland0.2 Romania0.1 Latvia0.1 Estonia0.1 Poland0.1 Hungary0.2 Lithuania0.2In terms of public charging points per 1,000 inhabitants,against an EU average of 1.4,Netherlands is first with 8.2,followed by Denmark(3.9),Belgium(3.8),and Luxembourg and Sweden each with 3.6.Many of the same countries appear near the top of the list of countries with the highest number of public charging points per 10 km of road;with 1.3 being the EU average.Luxembourg has 8.0,followed by the Netherlands(7.7),Portugal(5.1),Denmark(3.1),and Belgium(2.9).Are we there yet?The long,slow journey to public charge point rollout There are numerous reasons why public charge point deployment varies locally,nationally,and regionally.Red tape,permits,and planning permission are major hurdles to installation.So too are the capacity and resilience of existing power grids.In terms of physical deployment,existing service areas on major arterial routes are ideal for fast charger installation.By contrast,crowded urban areas where congestion is an issue and parking is at a premium present challenging conditions for locating slow chargers.Democratising EV adoption requires equity in charging point placement,ensuring the availability of EV charging in all neighbourhoods rural and urban,and not just in wealthier areas.Charge point safety is critical,too charge point users should feel safe stopping to charge,with well-lit and covered charging points installed in secure public locations.And they must be accessible to all,not just to able-bodied EV drivers.SOURCE:ACEA,EAFO,EUROSTAT 12Charge point operators(CPOs)In its Global EV Outlook 2023,the International Energy Agency(IEA)noted that an agreement between the European Investment Bank and the European Commission would make over 1.5 billion available by the end of 2023 for alternative fuel infrastructure,including electric fast charging.9Public charging points are managed and maintained by charge point operators(CPOs).The EV charging industry has yet to mature,with the number of CPOs still growing and evolving.The charging market remains fragmented,with a high number of small national players,many of them start-ups.Margins are low,and the return on investment is even lower.The next few years are likely to see considerable growth in charging points and considerable consolidation in CPOs,with charging eventually becoming a commodity.Against this backdrop of uncertainty,automakers are collaborating on infrastructure with other automakers,utility companies,and other stakeholders.Traditionally,fuelling has been outside the realm of the vehicle manufacturer,but with the success of EV sales so heavily dependent on the infrastructure,manufacturers have felt the need to accelerate its deployment.However,the roles and responsibilities of public and private stakeholders nationally and locally should be clearly defined to avoid hindering infrastructure rollout and delaying maintenance.A global comparison ChinaEuropes charging point infrastructure pales into insignificance when compared to Chinas,where the public charging network accounts for almost two thirds of the global public charging infrastructure and is growing rapidly.9.https:/www.iea.org/reports/global-ev-outlook-2023/trends-in-charging-infrastructureCHARGING INFRASTRUCTURE IN CHINA By country,202300.20.40.60.81.01.21.41.61.82015201620172018201920202021202213SOURCE:INTERNATIONAL ENERGY AGENCY(IEA)However,comparisons between Europe and China are largely academic.Chinas considerably greater network of public charging points supports BEVs with smaller batteries than are used in Europe.Chargers also deliver lower power output in China than in Europe;this supports affordable mainstream cars with smaller batteries,but is less suited to higher end vehicles which benefit from fast-charging technology.USIn the US,various provisions in the Inflation Reduction Act(IRA)support the deployment of EV charging infrastructure through incentives for consumers,businesses,and manufacturers.These include tax credits of up to$7,500 per vehicle through 2032;credits up to 30%of the cost of specific alternative fuel vehicle refuelling property,including electric vehicle charging infrastructure;incentives to enable automakers to meet the demand for electrically chargeable vehicles and charging infrastructure;and requirements via the complementary Bipartisan Infrastructure Law which promote the domestic production and installation of charging infrastructure.As of May 2023,the US had over 138,100 charging outlets for battery and plug-in electric vehicles,indicating a substantial foundation for the ongoing expansion of the electric vehicle charging network.CHARGING INFRASTRUCTURE IN CHINA Number of charging stations as of 31 December 2022PUBLIC ELECTRIC VEHICLE CHARGING STATIONS AND OUTLETS IN THE US Number of public electric vehicle charging stations and charging outlets in the US as of May 2023(in units)Charging stationsCharging outlets020,00040,00060,00080,000100,000120,000140,00053,393138,111ChinaRest of the world1.2 million1.8 million14SOURCE:BLOOMBERG,OXFORD INSTITUTE FOR ENERGYSOURCE:US DEPARTMENT OF ENERGYCLOSING THOUGHTS10.https:/www.acea.auto/fact/electric-commercial-vehicles-tax-benefits-and-purchase-incentives-2023/https:/www.acea.auto/fact/electric-cars-tax-benefits-purchase-incentives-2023/11.https:/ Range remains a key consideration for consumers accustomed to the long ranges of vehicles with internal combustion engines,despite average daily commuting distances in Europe of typically no more than 40 km.Coupled with range is an expectation of a charging network as dense as the existing fuel station network.And that includes being able to charge quickly.How can we charge ahead?The deployment of public charging points in Europe can be accelerated in a number of ways.These include for instance:Swift AFIR implementation:Member states should swiftly implement the Alternative Fuels Infrastructure Regulation(AFIR)bearing in mind that it sets minimum requirements,which will be insufficient by themselves to enable the CO2 targets for cars and vans to be met.At the same time,the European Alternative Fuels Observatory(EAFO)must ensure a robust monitoring system that incentivises member states to deploy infrastructure faster.Incentives and support:Although there are a number of European initiatives to support infrastructure roll-out,22 EU member states(80%)do not offer any incentives for infrastructure development or installation.10Grid updates:According to McKinsey,substantial upgrades to utility grids are necessary for the expansion of EV charging stations and increased renewable energy capacity,at an estimated cumulative cost of over 240 billion by 2030.11 Power companies and regulators unprepared for a surge in EV adoption could hinder the deployment of EV charging stations.Innovation:Technological innovation could help to accelerate the deployment of EV charging infrastructure,as CPOs and utilities enable functions such as vehicle-to-grid,bi-directional flow,smart grid,and grid balancing solutions,as well as rapidly increased charging speeds.Improved customer experience:Beyond the deployment of the charging infrastructure itself,CPOs must significantly improve the customer experience.This includes an end to multiple charging point apps,simplification of payment,and the provision of real-time information about charge point reliability and availability.Smoother processes:Red tape,permits,and planning permission are major hurdles to installation of charging points.The public charging network should be treated as critical infrastructure,and the roles and responsibilities of public and private stakeholders clearly defined.There may currently be enough public charging points to support todays fleet of ECVs,but the network will quickly become insufficient.It is essential to prepare now for future growth and the continued adoption of ECVs and that requires increased infrastructure investment.15ACEAEuropean AutomobileManufacturers Association 32 2 732 55 THE EU AUTOMOBILE INDUSTRY12.9 million Europeans work in the auto industry (directly and indirectly),accounting for 6.8%of all EU jobs 8.3%of EU manufacturing jobs some 2.4 million are in the automotive sector Motor vehicles are responsible for 392.9 billion of tax revenue for governments across key European markets The automobile industry generates a trade surplus of 101.9 billion for the European Union The turnover generated by the auto industry represents over 7%of the EUs GDP Investing 59.1 billion in R&D per year,automotive is Europes largest private contributor to innovation,accounting for 31%of the EU totalACEA represents europes 15 major car,van,truck and bus manufacturers
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Policy Pathways Towards a More Sustainable Cruise SectorWorking DocumentThe Blue Tourism Initiative project partners:Policy Pathways Towards a More Sustainable Cruise Sector(Working Document)Authors:Giulia Balestracci(Eco-Union),Angelo Sciacca(IDDRI),Jrmie Fosse(Eco-Union),Julien Rochette(IDDRI)Coordinator:Angelo Sciacca(IDDRI)Reviewers and Contributors:Roberta Milo,Rosario Galn(IUCN-Med),Dylis McDonald(CANARI),Paul Baraka(CORDIO East Africa),Ioannis Pappa(GSTC),Pascal Viroleau(Vanilla Islands),Arnau Terrisse(Plan Bleu),Chloe Martin(Plan Bleu),Ross Klein,Narendra RamgulamRecommended citation:Balestracci,G.,Sciacca,A.,Fosse,J.and Rochette,J.(2024).Policy pathways towards a more sustainable cruise sector.Edited by Blue Tourism Initiative.Layout:A.ChevallierPublication date:September 2024Cover photo:Bahamas,Fernando Jorgewww.BlueTourismInitiative.orgAbout the Blue Tourism InitiativeThe Blue Tourism Initiative is a global multi-stakeholder innovation program focused on the environmental management,governance,and planning of coastal and maritime tourism in three marine regions:the Mediterranean,the Western Indian Ocean and the Caribbean.The project supports the participatory development of sustainable blue tourism initiatives through policy actions and a multi-stakeholder approach to inform the scalability of sustainable blue tourism in other regions.The objectives of the Blue Tourism Initiative are to:1.Assess the current global and regional situation of blue tourism,focusing on challenges and opportunities,and recommend directions for sustainable blue tourism development.2.Support and monitor the implementation of sustainable blue tourism initiatives in the Mediterranean,Western Indian Ocean,and the Caribbean.3 Integrate sustainable blue tourism management and governance at the regional policy level,share best practices,and raise awareness among key local,national,and regional stakeholders.IDDRI is an independent think tank based in Paris(France)at the interface of research and decision-making that investigates sustainable development issues requiring global coordination.Eco-Union is an independent Think and Do Tank based in Barcelona(Spain),whose objective is to accelerate the ecological transition of the Euro-Mediterranean region.CORDIO East Africa is a nonprofit research Organisation based in Kenya focus on the sustainable use and management of coastal and marine resources in the Western Indian Ocean.IUCN Centre for Mediterranean,established in Malaga(Spain),works to bridge gaps between science,policy,management and action in order to conserve nature and accelerate the transition towards sustainable development in the Mediterranean.CANARI(Caribbean Natural Resources Institute)is a non-profit institute headquartered in Trinidad and Tobago,facilitating stakeholder participation in the stewardship of renewable natural resources in the Caribbean.This publication was produced with the financial support of the French Facility for Global Environment(FFEM).The contents of this document do not necessarily reflect the views of the funder.SummaryCruise tourism is a significant component of coastal and marine tourism.1 Despite the sharp decline during the COVID-19 pandemic,2 the sector rebounded in 2023 with 31.7 million passengers,surpassing 2019 levels by 7%.Addi-tionally,projections estimate that the cruise sector will reach 40 million passengers annually by 2027.3 Cruise tourism frequently attracts attention due its impacts on sea,air,and land4 as well as by its controversial relationship with desti-nation communities,who experienced in the first place the externalities of the cruise tourism development,5.6Furthermore,the market power of cruise industry in numerous regions and destinations drive intense competition and conflicts among stakeholders,who often have different cost-benefit perceptions and goals.7 This tension can hinder the development of a more sustainable cruise sector by obstructing necessary cooperation among actors.The sector also faces regulatory gaps from the global to the national and local levels,with weak monitoring and enforcement compli-ance mechanisms-left to the charge of the national author-ities,who face limitations in applying these mechanisms,hindering the sustainability of the sector.Many cruise ships are registered in flag States that are responsible for ensuring 1 Balestracci,G.,Sciacca,A.(2023):Towards sustainable blue tourism:trends,challenges,and policy pathways.Edited by Blue Tourism Initiative.2 Radic,A.,Law,R.,Lck,M.,Kang,H.,Ariza-Montes,A.,Arjona-Fuentes,J.M.,&Han,H.(2020):Apocalypse now or overreaction to coronavirus:The global cruise tourism industry crisis.Sustainability,12(17),6968.3 Cruise Lines International Association(2024):State of the Cruise Industry Report.4 Syal,R.(2022):Shippings dirty secret:how“scrubbers”clean the air-while contaminating the sea.The Guardian.5 Asero,V.,&Skonieczny,S.,(2018):“Cruise Tourism and Sustainability in the Mediterranean.Destination Venice”.InTech.;Schemmer,J.,(2022):“Social Resistance and Spatial Knowledge:Protest Against Cruise Ships in Venice”.NTM Zeitschrift fr Geschichte der Wissenschaften,Technik und Medizin,30(3),377-406.6 Klein,R.A.,(2013):“Responsible Cruise Tourism:Issues of Cruise Tourism and Sustainability”.Memorial University of Newfoundland,Canada7 Kim,S.B.,Marshall,L.H.,Gardiner,R.,&Kim,D.Y.(2021):Conflicts in communities and residents attitudes toward the impacts of cruise tourism in the Bahamas.Journal of Travel&Tourism Marketing,38(9),956-973.cruise compliance to regulations8 but these countries often have weak environmental and safety standards.With 80%of tourism occurring in coastal and marine areas,cruise tourism must swiftly adopt more sustainable practices to align with global Climate9 and Biodiversity targets10 and contribute to the Sustainable Development Goals(SDGs),in particular SDGs 6,7,12,13,14,15,17.11 This transition requires improved collaborative governance at the institutional level that is socially,geographically,and politically inclusive,informing cohesive and coherent sustainability strategies and policies.Specifically,regional intergovernmental and intersectoral cooperation can leverage existing frameworks to strengthen monitoring mechanisms,share expertise and utilise innovative technologies.This report,based on desk research and stakeholder consulta-tions,examines the global state of cruise tourism.It provides relevant updated market data,in terms of passengers volumes,main destinations,and type of vessels.After discussing the main multidimensional impacts generated by this industry,the report provides a critical outline of the cruise sector govern-ance with the description of its key actors,and the main inter-national and regional regulatory frameworks.Particular atten-tion is given to the Mediterranean,Caribbean,and Western Indian Ocean,regions with main cruise destinations.Challenges to a more sustainable cruise sector have been iden-tified as a basis to recommend priority policy and governance actions that can enable the cruise sectors transition to a fairer,more responsible and sustainable industry.This report intends to serve as a wake-up call for increased regional and global cooperation,advocating for a coordinated approach in regu-lating,monitoring,and maximising the benefits of the sector.8 Tonazzini,D.,Fosse,J.,Morales,E.,Gonzlez,A.,Klarwein,S.,Moukaddem,K.,Louveau,O.(2019):“Blue Tourism.Towards a sustainable coastal and maritime tourism in world marine regions”.Edited by eco-union.Barcelona9 United Nations(2015):The Paris Agreement.10 The Kunming-Montreal Global Biodiversity Framework.Particularly,TARGETS 4,7,14,15 and 16.11 United Nations Department of Economic and Social Affairs(2024):Sustainable Development Goals.Mexique.E.Lawrence/Unsplash1 Table 1.Policy Pathways Towards a More Sustainable Cruise Sector M.Vega/UnsplashChallenge 1.Global regulatory and governance gaps Pathway 1.Identify and fill Global Regulatory and Governance Gaps1.1.A comprehensive review of global regulatory frameworks is needed to identify existing gaps and loopholes.This review should account for the distinct characteristics and needs of different regions.1.2.Targeted action will be required to close these gaps by fostering effective communication and collaboration across all levelsboth horizontally(across sectors)and vertically(from local to global levels).Regulatory actions should be tailored to the specific conditions and challenges of each marine region.Challenge 2.Lack of collaboration and high competition among destinationsPathway 2.Promote Regional and Interregional Cooperation on Cruise Tourism2.1.Intergovernmental and multi-sectoral cooperation should be enhanced at the regional level to align policies across regions,ensuring consistency with commonly agreed sustainability goals for cruise tourism.2.2.International collaboration between regional cruise tourism bodies and other regional mechanisms should be supported to promote cohesive global actions.This cooperation should foster and incentivize sustainable practices within the cruise tourism sector.Challenge 3.National regulatory and governance gaps Pathway 3.Address National Regulatory Gaps3.1.Where needed,countries should embark in comprehensive reviews of their national regulatory frameworks to identify gaps and loopholes,ensuring alignment with regional and global actions and agendas.3.2.Actions should be taken to close regulatory gaps by mobilising the necessary resources and fostering cooperation.Engaging within regional cooperation mechanisms is essential to ensure policy consistency with neighbouring countries and prevent fragmented approaches.Challenge 4.Weak monitoring and enforcements Pathway 4.Improve Monitoring and Reporting Systems 4.1.Monitoring frameworks should be enhanced at both national and regional levels to ensure cohesive and consistent monitoring practices across regions.4.2.Reporting systems should also be strengthened at national and regional levels to promote uniformity and enforcement.Regional cooperation mechanismsexisting or newly developedshould support and ensure compliance with these reporting standards.Challenge 5.Limited adoption of clean technologies and sustainable behavioursPathway 5.Implement clean technologies and more sustainable behaviours by the industry and consumers5.1.Policy and non-regulatory actions should be fostered to support sustainable cruise ship technologies and emission reductions.5.2.Vessels certifications should become more ambitious and better aligned with international environmental standards.5.3.Sustainable behaviours of the industry and consumers through awareness and capacity building tools should be fostered.Policy Pathways Towards a More Sustainable Cruise Sector2 Summary 1Table of contents 3Abbreviations and Acronyms 41.Introduction 52.State of the Cruise Sector 63.Impacts of the Cruise Sector 83.1.Environmental Impacts 83.2.Economic Impacts 93.3.Social Impacts 104.Cruise Sector Governance 114.1.Markets Actors 114.2.Regulatory and Cooperative Frameworks 125.Challenges and Opportunities for Sustainable Cruise Governance 185.1.Challenges for SCT 185.2.Regulatory and Governance Opportunities 215.3.Non-Regulatory Opportunities 216.Policy Pathways for a More Sustainable Cruise Sector 24Bibliography 29Table of contentsList of figuresFigure 1.Global Cruise Passengers 6Figure 2.Passenger Volume per Region(2023)6Figure 3.Major Source Regions and Respective Passenger Volume Comparison 2023-2019 7Figure 4.Passenger Volume Comparison 2023-2019 7Figure 5.Cruise Capacity Projections 7Figure 6.Environmental,Economic,and Social Externalities of Cruise Tourism 8Figure 7.Waste Streams from Cruise Ships 9List of tablesTable 1.Policy Pathways Towards a More Sustainable Cruise Sector 2Table 1.Estimate Worldwide Cruise Line Market Share for 2024 11Table 2.Actors of the Cruise Sector Governance*12Table 3.Countries Permitting Open-Loop Scrubber Discharge 19Table 2.Policy Pathways Towards a More Sustainable Cruise Sector 243 Abbreviations and AcronymsCSER Corporate Social and Environmental ResponsibilityCFCs ChlorofluorocarbonesCLIA Cruise Lines International Association CMOU Cruise Memorandum of Understanding COLREGS Convention on the International Regulations for Preventing Collisions at Sea;CO2 Carbon DioxideGDP Gross Domestic ProductGSTC Global Sustainable Tourism CouncilHELCOM Helsinki CommissionILO International Labour OrganisationLEED Leadership in Energy and Environmental Design IMO International Maritime OrganisationMARPOL International Convention for the Prevention of Pollution from ShipsMSSD Mediterranean Strategy for Sustainable DevelopmentNGOs Non-governmental organisationNOx Nitrogen OxidesPPP Public-private partnerships PVC Polyvinyl chlorideSDGs Sustainable Development GoalsSECA Sulphur Emission Control AreaSOLAS International Convention for the Safety of Life at SeaSOx Sulphur OxidesSTCW International Convention on Standards of Training,Certification and Watchkeeping for SeafarersUN United Nations,EU European Union UNEP/MAP United Nations Environment Programme/Mediterranean Action PlanWWF World Wildlife FundPolicy Pathways Towards a More Sustainable Cruise Sector4 1.Introduction Cruise tourism is one of the most profitable segments of coastal and marine tourism.12 Ocean cruising is rapidly expanding,and it represents the largest tourism sub-sector in terms of gross added value and employment.The cruise industry has attracted increasing attention due to its signifi-cant growth and swift recovery following crises such as the 2008-09 financial crises,geopolitical challenges(i.e,the impact of the Arab Spring on Mediterranean cruising)and the negative aftermath of the Costa Concordia accident in Italy,which affected the image of the sector.Even after the COVID-19 pandemic,the cruise industry has demonstrated its financial and market resilience with recorded continued growth.13 While major cruise companies celebrate this economic success,concerns from civil societies,local communities and public stakeholders persist regarding the adverse impact of cruise activities on the environment,society,and the local economies.A primary challenge remains enhancing the sectors sustainability across all its dimensions and inherent to its transnational operations,which pose hurdles from a regu-latory,monitoring,and more broadly,governance perspec-tive.Furthermore,the intense competitive environment that characterises the cruise industry further exacerbates these 12 Balestracci,G.,Sciacca,A.(2023):“Towards sustainable blue tourism:trends,challenges,and policy pathways.”Edited by Blue Tourism Initiative.13 Notteboom,T.,Pallis,A.,&Rodrigue,J.P.(2022):“Port economics,management and policy”.Routledge.challenges,potentially impeding collaborative efforts neces-sary for advancing sustainable practices.This report focuses on providing a diagnosis of the cruise industry,examining its economic,environmental,and social impacts,and identifying the main challenges and policy opportunities for improving sustainability within the sector.Emphasising the urgency,this report underscores the need for the cruise industry to increasingly align with global climate14 and biodiversity targets,15 and Sustainable Development Goals(SDGs).16 Against this backdrop,the report supports enhanced collaborative governance models and an increased regional cooperation as pivotal strategies to foster the growth of sustainable approaches across the cruise industry,aligning with global sustainability targets and ensuring the equitable distribution of its benefits.14 United Nations,(2015):“The Paris Agreement.”15 CBD,(2022):“The Kunming-Montreal Global Biodiversity Framework”.Particularly,TARGETS 4,7,14,15 and 16.16 United Nations Department of Economic and Social Affairs(2024):Sustainable Development Goals.In particular a more sustainable cruise industry would better align with several SDGs that are centred on on environmental protection,social well-being,and responsible economic growth(i.e.,SDG 6:Clean Water and Sanitation,SDG 7:Affordable and Clean Energy,SDG 12:Responsible Consumption and Production,SDG 13:Climate Action,SDG 14:Life Below Water,SDG 15:Life on Land,SDG 17:Partnerships for the Goals)(see appendix)Sainte-Lucie.O.Eagle/Unsplash5 2.State of the Cruise Sector Over the past 15 years,the cruise sector has undergone a signif-icant transformation,experiencing consistent annual growth averaging 7%until the onset of the COVID-19 pandemic.17 From 2009 to 2019,the number of cruise passengers nearly doubled,underscoring a significant rise in the sectors popularity and accessibility.18 This growth was propelled by substantial infrastructural advancements and an expanding global traveller base.Despite a brief slowdown following the 2009 financial crisis,the cruise industry outpaced other trans-port or tourism sectors in growth.However,the COVID-19 pandemic represented a major setback for the industry,19 leading to swift travel restrictions,enforced quarantines,and port closures.20 These containment measures had a particu-larly significant impact for coastal businesses reliant on the cruise sector,resulting in substantial income loss.21 None-theless,the sector displayed financial and market resilience by rebounding strongly,achieving 31.7 million passengers in 2023,surpassing 2019s levels by 7%.Future projections indi-cate continued growth,with forecasts predicting 40 million annual passengers by 2027(Figure1).17 European Commission,Directorate-General for Maritime Affairs and Fisheries(2023):“Good practices for sustainable cruise tourism Final report”,Publications Office of the European Union.18 Fosse,J.,Tonazzini,D.,Morales,E.,Gonzlez,A.,Klarwein,S.,Moukaddem,K.,&Louveau,O.(2019):“Sustainable blue tourism:towards a sustainable coastal and maritime tourism in world marine regions”.Eco-union.19 Notteboom,T.,Pallis,A.,&Rodrigue,J.P.(2022):“Port economics,management and policy“.Routledge.20 Cruise Lines International Association,(2022):“State of the Cruise Tourism Outlook 2022”.21 da Silva,A.L.R.,(2021):“An overview of the impact of COVID-19 on the cruise industry with considerations for Florida”.Transportation Research Interdisciplinary Perspectives 10:100391.Regional data on passenger volumes provides a closer exam-ination of the cruise sectors resilience to external shocks.Figure 2 compares passenger volumes between 2023 and 2019,revealing increases in every region except for Asia and China.The Caribbean is the most visited cruise destination worldwide,welcoming nearly 13 million passengers in 2023,an increase of nearly 1 million compared to 2019.Following closely,the Mediterranean recorded 5.5 million passengers in 2023,non-Mediterranean Europe saw 3 million passengers,and Asia had 2.6 million passengers in 2023.22 Cruise tourism destinations are very diverse,ranging from small islands in the Caribbean,large Mediterranean cities such as Barcelona in Spain and Venice in Italy,to remote rural communities in the Arctic,whose popularity as cruise destina-tions is on the rise due to melting ice(Figure 3).23 In 2023,the United States led globally as the top source market with 16.9 million passengers.Following were Germany with 2.5 million passengers and the UK with 2.2 million passengers.However,22 Ibid.23 Lau,Y.yip,Kanrak,M.,Ng,A.K.Y.,&Ling,X.(2023):“Arctic region:analysis of cruise products,network structure,and popular routes”Polar Geography,46(23),157169.0510152025303540 29,7 5,84,8 20,4 31,7 34,7 37,1 38,8 39,7107%of 2019 passengervolume201920202021202220232024F2025F2026F2027F(in millions,2019-2023 and forecast until 2027).Figure 1.Global Cruise Passengers Source:Cruise Lines International Association,2024(Cruise Lines International Association,(2024):“State of the Cruise Industry Report.)03691215Passenger volume 2023 2019Caribbean/Bahamas/Bermuda Mediterranean Asia China Non-Med Europe Alaska Australia/New Zealand/Pacific West Coast/Mexico/California/Pacific Coast South AmericaPanama Canal AfricaMiddle East Transatlantic 12,9 7.3(in millions).0,4 3.1%0,350,54 4.6%0,51,1 34%0,81,4 24.1%1,21,3 8.4%1,2 1,7 35.8%1,2 3 6.6%2,8 2,6-35.6%4 5,5 23%4,4Source:Cruise Lines International Association,(2024).Cruise Lines International Association,(2024):“State of the Cruise Industry Report.”Figure 2.Passenger Volume per Region(2023)Policy Pathways Towards a More Sustainable Cruise Sector6 Asian markets,notably China,saw a substantial decline due to the COVID-19 crisis,experiencing a 92crease in passenger volume.24Recent economic growth of the sector has been significantly shaped by increasing vessel capacity over the past 15 years(Figure 4),and economic affordability by consumers.25 Larger vessels have become more prevalent in the market,gradually displacing mid-size cruises.26 Moreover,global cruise capacity is expected to grow by at least 10%from 2024 to 2028,with continuous expansion in cruise ship berths(Figure5).Concur-rently,there has been a surge in the construction of very small vessels catering the luxury markets,highlighting a dual trend in industry growth.Globally,the luxury sector is projected to grow from 4%in 2019 to 6%by 2028,driven by the construc-tion of 45 new luxury vessels between 2020 and 2028.27 24 Cruise Lines International Association.(2024):“State of the Cruise Industry Repor.”25 da Silva,A.L.R.,(2021):“An overview of the impact of COVID-19 on the cruise industry with considerations for Florida”Transportation Research Interdisciplinary Perspectives 10:100391.26 Goodger,D.Savelli,C.,(2023):“Luxury cruising the new normal”.Oxford Economics.27 Ibid.Figure 3.Major Source Regions and Respective Passenger Volume Comparison 2023-2019GlobalNorth americaEuropeAsiaAutraliaSouth AmericaPassenger volume 2023 2019 31,7 29,7(in millions).0,99 6,6%0,931,34-1,0%1,352,3-37,7%3,7 8,2 6,5%7,7 18,1 17,5,4 6,8%Source:Cruise Lines International Association,(2024).Cruise Lines International Association,(2024):“State of the Cruise Industry Report.”Figure 4.Passenger Volume Comparison 2023-2019 Source:Cruise Lines International Association(2024).Cruise Lines International Association,(2024):“State of the Cruise Industry Report.”Passenger volume 2023 2019United StatesGermanyUnited KingdomChinaAustraliaCanadaItalyBrazilSpainFrance(in millions).19,9 19,22,5-3%2,6 2,2 15%1,9 0,15-92%1,9 1,2 1%1,2 1-1,2 24%0,950,74 30%0,58 0,59 6%0,550,57 6%0,54201620172018201920202021202220232024F2025F2026F2027F2028F483 524 540 582 590 604 625 656 677 701 730 737 745(number of cruis ship berths;in thousand).Figure 5.Cruise Capacity ProjectionsSource:Cruise Lines International Association,(2024).Cruise Lines International Association,(2024):“State of the Cruise Industry Report”D.Bagg/Unsplash2.State of the Cruise Sector 7 3.Impacts of the Cruise SectorThe externalities of the cruise industry are multi-dimensional and should inform areas of action to foster a more sustain-able and equitable sector(Figure 6).Despite their diversity,cruise destinations share common sustainability challenges,particularly in relation to ensuring sustainable port opera-tions,waste management and benefits to local communities.This section delves into the impacts of cruise tourism across environmental,economic,and social dimensions.3.1.Environmental Impacts Cruise ships are an important source of marine pollution28 with an estimated waste generation between 2.6 to 3.5 kg/person/day.29 One of the main sustainability issues in the cruise sector is its heavy reliance on fossil fuels and emission of toxic substances,such as sulphur oxides(SOx),nitrogen oxides(NOx),particulate matter(PM),and carbon dioxide(CO2).These emissions contribute to acid rain,ocean acidi-fication,and climate change,all of which negatively impact marine life and ecosystems.30 It has been estimated that a passenger on a cruise emits twice more CO2 than someone who flies and rents a hotel.31 Furthermore,despite being a small segment of the shipping industry,cruise ships opera-tional proximity to coastal areas and prolonged stays in port cities substantially deteriorate local air quality with direct effects on the health and well-being of resident communi-ties.32 For example,in Barcelona,a study has shown a 3.8%increase in Nitrogen Dioxide levels above mean values for every additional cruise ship.33 This issue is exacerbated by weak regulatory standards governing marine fuels,which lag behind those of other transport modes,amplifying the indus-trys environmental footprint.34 Moreover,cruise ships severely impact marine ecosystems through wastewater discharge35(Figure 7),introducing harmful bacteria,excessive nutrients,and persistent chem-icals into the ocean.In this regard,despite new engines being built to run on liquified natural gas(which has its own shortcomings regarding the leakage of unburned methane,known“methane slip”),36 many cruise ships still use scrubbers 28 Cari,H.,&Mackelworth,P.,(2014):“Cruise tourism environmental impactsThe perspective from the Adriatic Sea.”Ocean&coastal management,102,350-363.29 US EPA United States environmental Protection Agency,(2008):“Cruise Ship Discharge Assessment Report.”US EPA Oceans and Coastal Protection Division.Washington30 Hall,C.M.,Wood,H.,&Wilson,S.,(2017):“Environmental reporting in the cruise industry.In Cruise ship tourism”(pp.441-464).Wallingford UK:CABI;European Commission,Directorate-General for Maritime Affairs and Fisheries(2023):“Good practices for sustainable cruise tourism Final report.”Publications Office of the European Union.31 Comer,B,.(2022):“What if I told you cruising is worse for the climate than flying?”International Council of Clean Transportation.32 Lloret,J.,et al.,(2021):“Environmental and Human Health Impacts of Cruise Tourism:a review”.33 Oxford Economics,(2023):“Environmental impact of cruise traffic within Barcelona.”Cruise Line Association.34 Transport&Environment,(2023):“The Return of the Cruise”.35 European Commission,Directorate-General for Maritime Affairs and Fisheries,(2023):“Good practices for sustainable cruise tourism Final report.”Publications Office of the European Union.36 Comer,B.,(2022):“What if I told you cruising is worse for the climate than flying?”International Council of Clean Transportation.to redirect pollution from air to water37.However,scrubbers discard waters often contaminated with polycyclic aromatic hydrocarbons linked to cancers and reproductive dysfunc-tion in marine mammals.38 Ships,in general,can emit 10 giga-tonnes of scrubber wash water in a year,with high concentra-tion areas being the Caribbean,around Europe,and the Strait of Malacca.15%of scrubber emissions are associated with the cruises.39 This highlights the need for stricter regulations and innovative solutions to mitigate the impacts of scrubber emissions and the shortcomings of liquified natural gas cruise ship engines.Another relevant hazardous waste that should not be discharged at sea is the ash generated by the cruise ship,not yet regulated at the international level.40Additionally,the large amounts of solid waste generated-such as plastics(single-use items like utensils and packaging mate-rials),food waste,and other refuse-threaten marine animals through ingestion or entanglement and disrupt ecosystems.For example,a study of cruise ships in the Caribbean has shown that each can generate around 266m3 of solid waste.41 In some cases,sewage sludge is dewatered and then incin-erated.In other cases,sludge is dumped at sea.Most juris-dictions permit sludge to be dumped within three miles of shore.However,food and other waste not easily incinerated is ground or macerated and discharged into the sea.Waste management operations include incineration,legal discharge 37 Osipova,O.,Georgeff,E.&Comer,B.,(2021):“Global scrubber washwater discharges under IMOs 2020 fuel sulfur limit.”International Council on Clean Transportation.10-12.38 Georgeff,E.,Mao,X.,&Comer,B.,(2019):“A whale of a problem?Heavy fuel oil,exhaust gas cleaning systems,and British Columbias resident killer whales.”International Council on Clean Transportation.39 Osipova,L,Georgeff,E.&Comer,B.,(2021):“Ship scrubber washwater:How much,whats in it,and where its dumped.”International Council on Clean Transportation.40 Klein,Ross A.,(2009):“Getting a Grip on Cruise Ship Pollution”.Friends of the Earth.41 Kotrikla,A.M.,Zavantias,A.,&Kaloupi,M,.(2021):“Waste generation and management onboard a cruise ship:A case study”Ocean&Coastal Management,212,105850.Greenhouse gas emissions due to reliance on fossil fuels Local air quality degradation due to operational proximity and prolonged stays in port cities Marine ecosystem degradation due to waste generation,habitat destruction,noise pollution,and collisions with marine lifeENVIRONMENTALStrain on local infrastructure and resources,including congestion and overcrowding,and waste management challengesRising costs for locals combined with limited financial revenues Increased pollution and environmental concerns leading to higher public health risks Limited economic multipliers for local economies due to low purchasing power of cruise passengers)Dependency on seasonal tourism,resulting in fluctuations in revenue,income instability,and economic vulnerability Public financial burden resulting from tourism infrastructure maintenance costs ECONOMICSOCIALFigure 6.Environmental,Economic,and Social Externalities of Cruise TourismSource:elaborated from Tonazzini,D.,et al.(2019):“Sustainable blue tourism:towards a sustainable coastal and maritime tourism in world marine regions.”Eco-union.Policy Pathways Towards a More Sustainable Cruise Sector8 at sea and disposal at ports.However,there is often a lack of adequate land waste facilities at the destination,which hinders proper waste management and the prevention of marine and coastal pollution.42 Solid waste and some plas-tics are incinerated on board,with the incinerator ash being dumped into the ocean.Incinerator ash and the resulting air emissions can contain furans and dioxins,both found to be carcinogenic,as well as heavy metal and other toxic resi-dues.For this reason,Annex V of MARPOL recommends,but does not require,that ash from incineration of certain plas-tics not be discharged into the sea.43 Moreover,underwater noise pollution from ships(which may range from 180 to 200 decibel)44 interferes with the communication,navigation,and feeding of marine animals,particularly cetaceans like whales and dolphins.45In addition,physical damage from anchoring or accidental groundings in fragile areas like coral reefs46and seagrass beds47 can significantly impact the marine environment.For example,the construction and expansion of cruise terminals and associated infrastructures lead to land-use changes,habitat destruction,and alterations to coastlines.Dredging,a common practice to accommodate larger vessels48 can 42 Ibid43 Klein,Ross A.,(2009):“Getting a Grip on Cruise Ship Pollution”.Friends of the Earth.44 Jalkanen,J.P.,Johansson,L.,Andersson,M.H.,Majamki,E.,&Sigray,P.,(2022):“Underwater noise emissions from ships during 20142020”.Environmental Pollution,311,119766.45 Erbe,C.,Marley,S.A.,Schoeman,R.P.,Smith,J.N.,Trigg,L.E.,&Embling,C.B.,(2019):“The effects of ship noise on marine mammalsa review.Frontiers in Marine Science,6,606.46 Burke,L.,&Maidens,J.,(2004):“Reefs at Risk in the Caribbean;Small,M.,&Oxenford,H.A.,(2022):“Impacts of cruise ship anchoring during COVID-19:Management failures and lessons learnt.”Ocean&Coastal Management,229,106332.47 Watson,S.J.,Rib,M.,Seabrook,S.,Strachan,L.J.,Hale,R.,&Lamarche,G.,(2022):“The footprint of ship anchoring on the seafloor.”Scientific Reports,12(1),7500.48 Ganic,E.,(2021):“Nassau Cruise Port:Dredging,land reclamation underway.“disrupt local ecosystems,increase noise pollution,cause physical disturbances,and raises the risk of collisions with marine life.49 The dismantling of cruise ships,also known as shipbreaking or ship recycling,poses significant environmental risks,particu-larly due to the hazardous materials found in these vessels.Ships are composed of various toxic substances,including asbestos,heavy metals,paints,oil,plastics,PVC pipes,glass wool,and even radioactive waste.50 During dismantling,residual fuel,oil,and chemicals remaining in the ships tanks can leak,causing pollution in surrounding areas.In recent decades,most decommissioned cruise ships have been sent to shipbreaking yards in developing countries,especially in South Asian ones,including Bangladesh,India,and Pakistan.These countries often lack the infrastructure for safe and environmentally sound shipbreaking.As a result,waste materials accumulate on land and eventually enter the marine environment through tidal and subtidal zones,damaging the physico-chemical properties of seawater and sediments,leading to coastal and marine degradation.Additionally,many shipyards in these countries lack proper facilities for recycling,resulting in improper disposal of non-recyclable materials.Due to the inadequate infrastructure and unsafe disposal practices in these developing countries,cruise ship deconstruction represents significant environmental hazards,contributing to soil and marine pollution.51 3.2.Economic Impacts The economic impact of the cruise sector is multifaceted and substantial,even though it represents just 2%of inter-national travel.In 2022,with 20.4 million cruise passengers,the cruise industry contributed$138 billion in total economic impact globally,supporting 1.2 million jobs worldwide and$43 billion in wages.52 For instance,in the Caribbean,cruise tourism accounted for 20%of the GDP in 2022,attracting over 780,000 stopover visitors.This sector is expected to grow by 10-15%by the end of 2024,reaching 35.8 million cruise visits.53 In Europe,the cruise sector contributes$44 billion to the regional economy and supports approximately 315,000 jobs.54 These figures underscore the role of cruise tourism in the global economy.However,evidence suggests that cruise tourism primarily benefits a few stakeholders,with limited positive impact on 49 European Commission,Directorate-General for Maritime Affairs and Fisheries,(2023):“Good practices for sustainable cruise tourism Final report.”Publications Office of the European Union.50 Occupational Safety and Health Administration(OSHA),(2001):“Ship Breaking Fact Sheet.US Department of Labor.“51 Demaria,F.,(2010):“Shipbreaking at AlangSosiya(India):An ecological distribution conflict.”Ecological Economics.52 Cruise Lines International Association,(2024):“State of the Cruise Industry Report”53 Caribbean Tourism Organisation,(2024):“Caribbean Tourism Experiences Strong Growth in 2023,Recovery to Continue into 2024”.Bridgetown,Barbados.54 Cruise Lines International Association,(2023):“State of the Cruise Industry Report”.Figure 7.Waste Streams from Cruise ShipsSource:Cogea,(2017).“Study on differentiated port infrastructure charges to promote environmentally friendly maritime transport activities and sustainable transportation”.GRAY WATER Cabin sinks&showers,Laundry,Galley BLACK WATER Toilets&Urinals,Medical Facility Wash,Basins&Drains BILGE WATERMachine&Engine Oil Collection,Lubricated Seals Water,Other liquids SLUDGE Used Lube Oil,Fuel Sludge GARBAGE Paper,Plastic Cans,Glass Food waste SPECIAL WASTES Chemicals,Light Bulbs,Batteries,Used paints,etc.3.Impacts of the Cruise Sector9 local employment and economic activity.55 Evidence also shows low economic multipliers56 for cruising,as the money spent by cruise tourists tends to remain confined to ports,terminals and related infrastructure rather than circulating widely in the local economy.This can be attributed to the rela-tively modest purchasing power of cruise passengers,which averages 30%lower than land tourists.57 This is since most goods and services are readily available on board,leading to reduced spending in local destinations.The seasonal nature of cruise tourism poses additional challenges for destination communities.Fluctuations in visitor numbers create peaks of intense activities and periods of decreased economic engage-ment.During peak seasons,ports may struggle to handle the influx of cruise ships,causing congestion and strain on local infrastructure.Conversely,off-peak periods bring decreased revenue for local businesses,exacerbating economic insta-bility and vulnerability.58 Furthermore,the infrastructure costs associated with accom-modating cruise tourism can impose significant financial burdens on local governments.The construction,operation and maintenance of ports,terminals,and supporting infra-structure require substantial investments,often straining limited budgets and resources that may not be entirely covered by head tax or dockage fee paid by cruise compa-nies,forcing governments to allocate funds from their budgets to cover these expenses,potentially diverting finan-cial resources from other purposes.For example,in Key West,a popular cruise destination in the USA,dockage fees by law can only be used for services and to support the improvement of port facilities.However,these fees cover only a minimum part of the incurred expenses,impacting the financial sustain-ability of port operations.59 3.3.Social Impacts From a social perspective,cruise tourism can result in both positive and negative social externalities.On the positive side,cruise tourism can lead to job creation in port cities and desti-nations,including jobs in hospitality,retail,transportation,and tour services,leading to local business growth thanks to an increased tourist spending supporting local restaurants,shops,and markets.For example,cruise tourism in Fiji gener-ated over 4000 full time jobs in 2018(approximately 1%of the 55 Macneill,T.,&Wozniak,D.,(2018):“The economic,social,and environmental impacts of cruise tourism”.In Tourism Management,66,pp.387-404;Seidl,A.,Guiliano,F.,&Pratt,L.,(2006):“Cruise tourism and community economic development in Central America and the Caribbean:The case of Costa Rica”.PASOS.Revista de Turismo y Patrimonio Cultural,4(2),213-224.56 The economic multiplier effect refers to the way spending in one sector can lead to increased economic activity and spending in other sectors.In the context of cruising,a low multiplier indicates that the money spent by cruise tourists does not circulate extensively through the local economy.57 Brida,J.G.,&Zapata,S.,(2010):“Cruise tourism:economic,socio-cultural and environmental impacts.”International Journal of Leisure and Tourism Marketing,1(3),205-226.58 Kizielewicz,J.,&Lukovi,T.,(2015):“Negative impact of cruise tourism development on local community and the environment.”Information,Communication and Environment:Marine Navigation and Safety of Sea Transportation,6(3),243-250.59 Krogh,R.,(2022):“Key West Doesnt Want Your Big Cruise Ships.”Outside;Honey,M.(2020):The Economics of Cruise Tourism in Key West:Behind the Cruise Industrys Propaganda Veil.working age population),60 and approximately 9000 annual employment opportunities in Barcelona and its surrounding61.Also,the cruise sector encourages the development of infra-structure such as ports,roads,and public facilities,benefiting both tourists and residents.62On the other hand,one significant issue is the strain on local infrastructure and resources caused by the temporal and spatial concentration of cruise activities with the influx of tourists arriving simultaneously during seasonal peaks(e.g.unmanageable levels of waste pressuring waste infra-structure;congestion of transportation methods impacting quality of life of residents63).The surge in tourist numbers can also drive-up prices of goods and services,making them less affordable for local communities.64 Cruise tourism can contribute to cultural displacement in destinations,often resulting in a perceived loss of authenticity by residents who react to the erosion of their everyday life.For example,Vene-tians have protested for years against the presence of cruise ships or for better regulations.65 Moreover,the limited contribution of cruise tourists to the local economy makes destination communities more vulner-able and sensitive to economic challenges and fluctuations66 With tourists spending minimal time ashore,local businesses often experience limited financial gains,leading to unequal distribution of benefits and leaving communities reliant on seasonal and precarious employment.67 Additionally,pollution from cruise ships and crowded tourist areas poses a threat to public health by degrading air and water quality.This pollu-tion increases the risk of respiratory ailments and other health issues among residents,compounding the negative social impacts of cruise tourism on destination communities.68 60 International Finance Corporation(2019):“Assessment of the Economic Impact of Cruise Tourism in Fiji.”61 Cruise Lines International Association,(2018):“Contribution of Cruise Tourism to the Economies of Europe 2017”62 Fosse,J.,Tonazzini,D.,Morales,E.,Gonzlez,A.,Klarwein,S.,Moukaddem,K.,&Louveau,O.,(2019):“Sustainable blue tourism:towards a sustainable coastal and maritime tourism in world marine regions.”Eco-union.63 Baumann,A.C.,(2021):“On the path towards understanding overtourismcruise tourism and the transportation infrastructure.”World Leisure Journal,63(1),5-13.64 Klein,Ross A.,(2011):“Responsible cruise tourism:Issues of cruise tourism and sustainability”.Journal of Hospitality and Tourism Management 18,no.1(2011):107-116.65 Schemmer,J.,(2022):“Social Resistance and Spatial Knowledge:Protest Against Cruise Ships in Venice”.NTM Zeitschrift fr Geschichte der Wissenschaften,Technik und Medizin,30(3),377-406.66 Macneill,T.,&Wozniak,D.,(2018):“The economic,social,and environmental impacts of cruise tourism.”In Tourism Management,66,pp.387-40467 Seidl,A.,Guiliano,F.,&Pratt,L.,(2006):“Cruise tourism and community economic development in Central America and the Caribbean:The case of Costa Rica”.PASOS.Revista de Turismo y Patrimonio Cultural,4(2),213-224.68 Ibid.A.Reyes/UnsplashPolicy Pathways Towards a More Sustainable Cruise Sector10 4.Cruise Sector Governance The governance of the cruise industry is cross-border and multi-level,including within nations.Key players in the industry,such as major corporations and international regulatory organ-isations,shape the operational standards and practices within the sector while the cruises should also comply with interna-tional,regional,national and local policies and laws.4.1.Markets ActorsThe cruise sector comprises a diverse range of market actors that collectively shape its operations and governance.In addi-tion to passengers,who influence market and industry prac-tices through their preferences,and crew members,who are essential to the operation of cruise ships both at sea and on land,the sector comprises various other actors,such as:Cruise lines:The cruise sector comprises more than 50 cruise lines and 250 ships.69 Nonetheless,major corporations dominate the cruise market,with a few large companies holding significant market shares.Carnival Corporation,for instance,is estimated to control about 37%of the global market,followed by Royal Caribbean Cruises LTD with 24%and Norwegian Cruise Line Hold-ings with 14%.These corporations operate multiple brands and collectively generate substantial revenue,driving the industrys economic engine(e.g.in 2023,Carnival raised over$24 billion in revenue)(Table 1).70 Currently,these three corporations still account for 75%of the global market share.71 Additionally,there are minor luxury and niche operators,smaller companies focusing on luxury experiences,adventure cruises,or specific destinations,such as Seabourn,Silversea,and Ponant.72 The current market structure and in particular the concentration of cruise companies may raise issues in relation to limiting the differentiation of offers,strengthening economic link-ages with destination operators and development of more sustainable brands and practices.73 Tourism organisations:While considering the cruise industry as a tourism sub-sector,it is important to mention the role of national and regional Tourism Boards.These entities promote cruise destinations and manage tourism strategies to attract cruise lines.Additionally,tour opera-tors and guides provide shore excursions,tours,and other experiences for cruise passengers,thereby contributing to the local economy.Industry associations:One relevant actor within the cruise tourism landscape is the Cruise Lines International Asso-ciation(CLIA).As the worlds largest cruise industry trade 69 da Silva,A.L.R.,(2021):“An overview of the impact of COVID-19 on the cruise industry with considerations for Florida”Transportation Research Interdisciplinary Perspectives 10:100391.70 Cruise Market Watch,(2024):“2024 Worldwide Cruise Line Market Share.”.71 da Silva,A.L.R.,(2021):“An overview of the impact of COVID-19 on the cruise industry with considerations for Florida”Trransportation Research Interdisciplinary Perspectives 10:100391.72 Cruise Market Watch,(2024):“2024 Worldwide Cruise Line Market Share.”73 The Tribune,(2022):“Competition law could help cruise challenges.”association,CLIA represents over 95%of global cruise capacity and 54000 travel agents,with 15000 of the largest travel agencies in the world as voluntary members.CLIA serves as the primary political advocate for the industry,focusing on advocacy,training,and industry standards.It aims to align the interests of cruise lines with regulatory bodies by promoting policies that support the growth of cruise tourism and by supporting sustainability actions.For example,CLIA members are committed to reduce carbon emissions by 40%by 2030 compared to 2008 levels and pursue net-zero carbon neutral cruising globally by 2050.74Port destinations play a critical role in the global cruise sector,serving as vital hubs for the economic,environ-mental,and social dynamics of the cruise and shipping industry.These destinations act as economic gateways for the cruise sector,facilitating passenger disembarkation,excursions,and services like shopping,dining,and tours,shaping the full cruise passenger experiences on-land.The economic impact of these ports extends beyond the cruise terminal,as a part of collecting port fees and taxes,they negotiate the complex relationships between global cruise companies and local economies,representing an opportunity for local revenue generation.Also,to accom-modate the growing size and volume of cruise ships,port destinations continually invest in infrastructures(expan-sion and modernization),but also improving roads,trans-portation services,and amenities that support the influx of cruise tourists.75 Furthermore,port destinations are,in principle,also responsible for managing and mitigating the environmental impacts of cruise ships.Shipbuilders construct cruise ships,with major shipyards located in Germany(Meyer Werft),Italy(STX Europe and Fincantieri)and France.Supplier companies provide goods and services necessary for cruise operations,including food and beverages,fuel,cleaning supplies,and entertainment.The the Energy Efficiency Design 74 European Commission,Directorate-General for Maritime Affairs and Fisheries,(2023):“Good practices for sustainable cruise tourism Final report.”Publications Office of the European Union.75 Santos,M.,Radicchi,E.,&Zagnoli,P.,(2019):“Ports role as a determinant of cruise destination socio-economic sustainability.”Sustainability,11(17),4542.Table 1.Estimate Worldwide Cruise Line Market Share for 2024Name and number of passengersRevenue,inBillions%RevenueCarnival12.921.000$24.6837,3%Royal Caribbean7.740.900$15.8023.9%Norwegian2.819.300$9.3114.1%All Others6.665.900$16.3524.7%Grand Total30.147.100$66.16100%Source:Authors elaborated from Cruise Market Watch(2024):“2024 Worldwide Cruise Line Market Share.”4.Cruise Sector Governance 11 Index(EEDI),76 promoted by the IMO,aimed at reducing CO2 emissions prescribing a minimum level of efficiency per tonne mile for all vessels constructed after 2013,with an initial CO2 reduction level by 10%compared to a base-line.77 Requirements are tightened every five years to stay ahead of technological improvements.In that context,large size bulkers registered improved hull designs,which positively influenced the EEDI78.Shipbuilders are increasingly building eco-friendly vessels that reduce fuel consumption and maximise fuel efficiency to meet envi-ronmental IMO Conventions standards,79 while also incor-porating innovative technologies to further minimise their environmental footprint.80 However,the marine transport including cruise sector remains heavily dependent on fossil fuel,including LNG,and is not yet on the track to comply with the Paris climate goals.81 As described in this section,the sector comprises various actors,each influencing regulatory frameworks and practices in distinct ways.This collective influence not only shapes industry standards but also the degree of environmental protection and social justice.4.2.Regulatory and Cooperative Frameworks The regulatory frameworks for cruise tourism comprise multiple stakeholders at various levels,increasing the neces-sity for effective collaboration.This section provides an overview of relevant frameworks at the global,regional,and national and local levels(Table 1).4.2.1 International Framework and related ConventionsAt the global level,the International Maritime Organization(IMO)is the United Nations agency responsible for“safe,secure,and efficient shipping on clean oceans.While several conventions have been adopted by the 160 IMO Member States that apply to cruise ships,their effectiveness often hinges on the commitments and capacities of individual nations to enforce and adhere to these frameworks:The International Convention for the Safety of Life at Sea(SOLAS).This convention is regarded as the most relevant international treaty concerning the safety of merchant ships.The first version of this treaty was adopted in 1914,in response to the Titanic disaster,and the last version in 1974.The main objective of the SOLAS Convention is to 76 International Maritime Organization,(2024):Improving the energy efficiency of ships.77 Tonazzini,D.,Fosse,J.,Morales,E.,Gonzlez,A.,Klarwein,S.,Moukaddem,K.,Louveau,O.(2019)“Blue Tourism.Towards a sustainable coastal and maritime tourism in world marine regions.”Edited by eco-union.Barcelona78 OECD(2018):“Shipbuilding Market Developments Q2-2018.”79 Lee,T.,Nam,H.,(2017):“A Study on Green Shipping in Major Countries:In the View of Shipyards,Shipping Companies,Ports,and Policies.”The Asian Journal of Shipping and Logistics.Volume 33,Issue 4,December 2017,Pages 253-26280 Adams,S.-A.,Font,X.and Stanford,D.(2017):“All aboard the corporate socially and environmentally responsible cruise ship:A conjoint analysis of consumer choices”,Worldwide Hospitality and Tourism Themes,Vol.9 No.1,pp.31-43.81 NABU,(2023):“Cruise Ranking 2023”specify minimum standards for the construction,equip-ment and operation of ships,compatible with their safety standards.Flag States are responsible for ensuring that ships under their flag comply with the requirements of the SOLAS Convention.To ensure such compliance,a number of certificates are prescribed by the Convention to help confirm safety standards are met by the ships.Moreover,State Parties to the SOLAS Convention can inspect ships of others if there are clear grounds for believing that the ship and its equipment do not substantially comply with the Conventions requirements.This is referred to as“port State control procedure”.82 However,while countries are tasked with ensuring compliance,different factors can impact the rigour of inspections conducted by countries.Moreover,the port State control procedure can fall short due to available resources at port destinations.82 IMO,(2019):“International Convention for the Safety of Life at Sea(SOLAS)”.Table 2.Actors of the Cruise Sector Governance*Examples of regulatory authoritiesExamples of frameworks and regulations InternationalInternational Maritime Organisation(IMO),International Labour Organisation(ILO),United Nations(UN)SOLAS,COLREGS,BASEL convention,and MARPOL conventionsRegionalEuropean Union,Regional seas programmes,HELCOM,Caribbean Maritime Organization(CMO),Organization of Eastern Caribbean States(OECS),South African Maritime Safety Authority(SAMSA),Port Management Association of Eastern and Southern Africa(PMAESA)European Green Deal,MSDD,CMOU,Barcelona,Nairobi,Helsinki,Cartagena conventionsNational and localNational governments,maritime authorities,national environmental agencies and health departmentsNational regulations on maritime safety,pollution prevention,and labour standards;local regulations governing port operations and environmental protection measures.Source:Authors(2024).*UNEP/MAP:United Nations Environment Programme/Mediterranean Action Plan,HELCOM:Helsinki Commission,SOLAS:International Convention for the Safety of Life at Sea;COLREGS:Convention on the International Regulations for Preventing Collisions at Sea;MARPOL:International Convention for the Prevention of Pollution from Ships,MSSD:Mediterranean Strategy for Sustainable Development,CMOU:Cruise Memorandum of Understanding.Policy Pathways Towards a More Sustainable Cruise Sector12 The Convention on International Regulation for Preventing Collision at Sea(COLREGS)(1974).This Convention establishes 10 Rules to provide guidance on determining safe speed for ships,assessing the risk of collision between vessels,and the conduct of vessels operating in or near traffic separation schemes.83 Yet,the challenges lie in ensuring that all vessels,particularly in busy and congested waters,consistently adhere to these regulations,which require effective monitoring and enforcement mechanisms.The International Convention on Standards of Training,Certification and Watchkeeping for Seafarers(STCW)(1995).This Convention was the first to establish basic requirements on training,certification and watchkeeping for seafarers at the international level.Previously,these requirements were established by individual governments.Instead,the Convention sets minimum standards which countries are obliged to meet or exceed.This Conven-tion regulates in detail general provisions,master,deck and engine departments,radiocommunication and radio personnel,special training requirements for personnel on certain types of ships,emergency procedures,occu-pational safety,medical care and survival functions,alternative certification,and watchkeeping.84 While this Convention mandates that countries meet or exceed the standards,the variability in national implementation raises questions about the overall effectiveness of the training provided to crew members,impacting the overall safety across the cruise tourism sector.The International Convention for the Prevention of Pollu-tion from Ships(MARPOL)(1998).85 This international convention covers the prevention of marine pollution by ships from operational or accidental causes.The United Nations Environment Programme(UNEP)has identi-fied cruise tourist ships as one of the principal pollution sources of marine ecosystems.86 The most significant feature of MARPOL is that all ships engaged in interna-tional navigation must have a Waste Management Plan,as for the collecting,storing,processing,and disposing of waste.MARPOL regulates several aspects of ship and port operations,including oil related hazardous emissions(Annex I),air emissions of NOx,SOx,VOCs,on-ship incin-eration and CFCs(Annex VI),and wastewaters(Annex IV).Also,it imposes the requirements for ports to provide facilities to treat ship-generated residues and garbage 83 IMO,(2019):“Convention on International Regulation for Preventing Collision at Sea(COLREGS)”.84 IMO,(2019):“International Convention on Standards of Training,Certification and Watchkeeping for Seafarers”(STCW).85 IMO,(2019):“International Convention for the Prevention of Pollution from Ships(MARPOL)”The International Convention for the Prevention of Pollution from Ships(MARPOL)includes regulations aimed at preventing and minimising pollution from ships-both accidental pollution and that from routine operations-and currently includes six technical Annexes.Special Areas with strict controls on operational discharges are included in most Annexes.In particular,the Annexes are dedicated to:Annex I Regulations for the Prevention of Pollution by Oil(1983),Annex II Regulations for the Control of Pollution by Noxious Liquid Substances in Bulk(1987),Annex III Prevention of Pollution by Harmful Substances Carried by Sea in Packaged Form(1992),Annex IV Prevention of Pollution by Sewage from Ships(2003),Annex V Prevention of Pollution by Garbage from Ships(1988),and Annex VI Prevention of Air Pollution from Ships(2005).86 Cari,H.,&Mackelworth,P.,(2014):“Cruise tourism environmental impactsThe perspective from the Adriatic Sea”.Ocean&coastal management,102,350-363.that cannot be discharged into the sea87(e.g.,Directive 2019/883 on port reception facilities).Yet,despite these regulations,many ports lack the necessary infrastructure to treat generated waste,potentially undermining the objective of the Convention.The International Labour Organization(ILO),a specialised agency of the United Nations focusing on labour-related issues,is also relevant for cruise shipping.Its most rele-vant convention is the Marine Labour Convention(2006)which applies to all commercially operated ships except for fishing vessels.The Convention addresses the welfare of seafarers,including decent living conditions,minimum wages,maximum hours of work,health and safety protec-tion,accommodation requirements,food provisions and medical care.Nevertheless,the application of these standards often varies,raising concerns about the actual living conditions experienced by crew members.While international conventions provide a crucial framework for establishing overarching goals and standards for the cruise tourism sector,their implementation is critically dependent on the commitment and capacities of flag and port States.Without robust enforcement mechanisms and genuine polit-ical will,the potential benefits of these conventions may remain largely unfilled(see Chapter 5).4.2.2 Regional Agreements and Cooperation Mechanisms Regional agreements are key to govern the cruise tourism sector and promote coherence in policy and management actions at regional level.The developments below provide an overview of relevant regional frameworks and related agree-ments for the Caribbean,Mediterranean and the Western Indian Ocean.4.2.2.1 CaribbeanAs the most popular cruise destination in the region,the Caribbean region setup different cooperation mechanisms and regional agreements that apply to the shipping industry,including the cruise sector.These include:The Caribbean Community(CARICOM)through its member arrangement on Single Market and Economy(CSME)facilitates the free movement of goods,services,capital,and people,impacting the cruise industry by promoting a unified market.The Caribbean Tourism Organization(CTO)develops sustainable tourism policies,such as the Caribbean Sustainable Tourism Policy Framework.This framework focuses on preserving natural resources,promoting cultural heritage,and enhancing community involvement in tourism.The Caribbean Shipping Association(CSA)focuses on promoting the interests of Caribbean shipping,improving maritime safety,environmental protection,and industry standards.87 Pallis,A.A.,Papachristou,A.A.,&Platias,C.,(2017):“Environmental policies and practices in Cruise Ports:Waste reception facilities in the Med”.SPOUDAI-Journal of Economics and Business,67(1),54-70.4.Cruise Sector Governance 13 The Association of Caribbean States(ACS)launched the Sustainable Tourism Zone of the Greater Caribbean(STZC)to promote sustainable tourism practices,including in the cruise sector,to protect the regions natural and cultural resources.The Caribbean Community and Common Market(CARI-FORUM)engages in dialogue and agreements with various international partners through the Economic Part-nership Agreement(EPA).88 These agreements facilitate trade and investment,impacting the cruise tourism sector by enhancing infrastructure,fostering economic growth,and improving regulatory standards.The Convention for the Protection and Development of the Marine Environment of the Wider Caribbean Region(Cartagena Convention)aims to safeguard the Carib-bean Sea from pollution.The Conventions Regional Activity Centers(RACs)focus on various aspects of envi-ronmental protection.Specifically,the RAC-Rempeitc(Regional Marine Pollution Emergency,Information,and Training Center for the Wider Caribbean)assists coun-tries to implement international conventions created to reduce pollution from ships,while RAC-Spaw(Specially Protected Areas and Wildlife)aims to protect endangered species and habitats.The Organization of Eastern Caribbean States(OECS)is a regional organisation comprising several Eastern Carib-bean countries.It aims to promote economic integration,harmonise policies,and foster cooperation among its member States.The OECS covers various areas,including maritime safety,environmental protection,and tourism development.Specifically,it promotes maritime safety and environmental protection through regional initiatives aligned with international standards and fosters collabora-tive projects including port infrastructure improvements and marine pollution control.Under the OECS the Eastern Caribbean Regional Ocean Policy(ECROP)was adopted that sets a framework for the sustainable use of ocean resources,including those related to the cruise industry.The Caribbean has established a strong foundation for sustainability through regional cooperation and agreements such as CARICOM,the Cartagena Convention and OECS.Yet,specific challenges remain in the cruise sector,particularly in ensuring equitable benefits and environmental sustaina-bility.Enhanced cruise-specific,multi-stakeholder collabora-tion is essential to securing a more sustainable future for the industry in the region.4.2.2.2 MediterraneanAs the second most popular region for cruise tourism,the Mediterranean region has developed a significant number of frameworks that regulate the industrys operations.Regula-tory efforts are mainly bolstered by UNEP/MAP through agree-ments such as the Barcelona Convention and its Protocols.Key organisations and agreements include:Barcelona Convention:formally known as the Conven-tion for the Protection of the Mediterranean Sea Against 88 Barbados Ministry of Foreign Affairs and Foreign Trade,(2020):“The CARIFORUM EU Economic Partnership Agreement”.Pollution,is a regional environmental agreement that aims to protect the Mediterranean Sea from pollution.The Barcelona Convention regulates the cruise sector primarily through broader measures(f.i.MARPOL),aimed at preventing pollution and protecting biodiversity via standards on pollution control,waste management,and emissions.This is particularly achieved through its various protocols,which target marine,air,and land-based pollution sources.The protocol concerning Coopera-tion in Preventing Pollution from Ships and,in Cases of Emergency,Combating Pollution of the Mediterranean Sea(1995),specifically addresses pollution from ships,including operational pollution caused by cruise liners.The Protocol for the Protection of the Mediterranean Sea against Pollution from Land-Based Sources and Activities applies to cruise ships,particularly in relation to waste brought ashore for disposal.Another example of how the Barcelona Convention indirectly affects cruise ships is the Hazardous Wastes Protocol that imposes restriction on emissions and waste management practices.UNEP/MAP:Initiated by the United Nations Environment Programme(UNEP),the Mediterranean Action Plan(MAP)is a comprehensive framework for regional cooperation.It supports the implementation of the Barcelona Conven-tion and its Protocols and promotes sustainable develop-ment in the Mediterranean.This MAP involves monitoring and controlling pollution,protecting biodiversity,and ensuring sustainable resource use,benefiting both ship-ping and cruise sectors.The RACs most relevant for the cruise sector include:The Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea(REMPEC):focuses on enhancing regional cooperation in preventing and responding to marine pollution incidents.The Regional Activity Centre for Specially Protected Areas(RAC/SPA):dedicated to the protection of biodiversity and the management of specially protected areas,the RAC provides guidelines for sustainable tourism and eco-friendly practices.The Regional Activity Centre for Sustainable Consumption and Production promotes cleaner production and sustain-able consumption patterns through guidelines for various industries,including tourism.Plan Bleu dedicated to supporting the transition towards a green and blue economy,working as Mediterranean Observatory on environment and sustainable develop-ment.The Mediterranean Strategy for Sustainable Develop-ment(MSSD)is a comprehensive framework aimed at promoting sustainable development across the Mediter-ranean region within the Barcelona Convention.Specifi-cally,the MSSD serves as a strategic guidance document for regional cooperation,emphasising the integration of environmental considerations into socio-economic devel-opment.MedCruise Association is an association representing Mediterranean cruise ports.It promotes the interests of its members by enhancing the cruise experience and Policy Pathways Towards a More Sustainable Cruise Sector14 marketing the Mediterranean as a premier cruise desti-nation.It plays a role in facilitating collaboration among ports,cruise lines,and other stakeholders to sustain cruise tourism and improve infrastructure and services.The Mediterranean Memorandum of Understanding(MoU)on Port State Control is a formal agreement among 11 Mediterranean countries to enforce international mari-time safety,security,and environmental standards.It establishes obligations for port inspections and compli-ance monitoring to ensure safe and environmentally friendly maritime operations.The Agreement on the Conservation of Cetaceans in the Black Sea,Mediterranean Sea and Contiguous Atlantic Area(ACCOBAMS)provides guidance for the protection of cetaceans,particularly interesting for tourism,but also vulnerable to disturbance,collisions and noise.ACCO-BAMS promotes a code of conduct to minimise distur-bances to cetaceans during tourism activities,empha-sising safe vessel practices and noise reduction.Similarly to the Caribbean,the Mediterranean region has implemented robust frameworks to regulate cruise tourism,primarily through the Barcelona Convention and UNEP/MAP initiative.While these initiatives focus on pollution control and biodiversity protection,there is still scope to enhance collab-oration between ports,cruise operators and environmental bodies to safeguard the Mediterraneans environmental and socio-economic balance.4.2.2.3 Western Indian OceanAs an emerging destination for cruise tourism,the Western Indian Ocean region presents some regulatory mechanisms affecting the shipping and cruise industry,including:Indian Ocean Rim Association(IORA)is a regional inter-governmental organisation established in 1997 to promote cooperation and sustainable development within the Indian Ocean region.Comprising 22 member States and 10 dialogue partners,IORA has four main objectives:fostering regional integration,enhancing maritime safety and security,promoting economic growth,and addressing environmental challenges in the Indian Ocean.IORA oper-ates through various working groups and task forces that focus on specific sectors such as maritime safety,fisheries management,tourism,and environment.It also promotes cooperation in maritime safety,search and rescue opera-tions,marine pollution response,and port management practices.The Nairobi Convention for the Protection,Management and Development of Coastal and Marine Environment of the Western Indian Ocean(WIO)region is a regional agreement aimed at fostering cooperation among WIO countries to safeguard the marine and coastal environ-ment.Adopted in 1985,its objectives include preventing,reducing,and controlling pollution from land-based sources,as well as protecting and managing coastal and marine biodiversity.The Convention encourages sustain-able development practices that balance environmental conservation with socio-economic needs.For the ship-ping and cruise sector,the Nairobi Convention supports the development of sustainable ports through scenario analysis89 and toolkits90 on the development of sustain-able ports facilities and operations in the blue economy context.Additionally,Article 12 of the Amended Nairobi Convention for the Protection,Management and Devel-opment of the Marine and Coastal Environment of the Western Indian Ocean(2015)91 mandates Parties to collab-orate in addressing pollution emergencies,leading to initiatives such as the Regional Oil Spill Preparedness in Eastern Africa and the Western Indian Ocean.92 As an emerging cruise destination,the WIO has established some frameworks which address maritime safety,environ-mental protection,and port sustainability.However,further efforts are needed to develop cruise-specific guidelines and strengthen regional cooperation to ensure the sustainability of the sector while balancing the economic and environ-mental priorities of the region.The regulatory landscape governing the cruise tourism sector varies significantly across regions,leading to varying levels of regulations and degrees of attention to sustainability of the sector.This regulatory disparity among regions can create international inconsistencies and loopholes,poten-tially undermining effective oversight of global cruise activi-ties.These risks should be mitigated through strengthening cooperation among regions,specific to cruise tourism,and that would allow a more aligned interplay among interna-tional,regional,national and destination-level regulations and sustainability targets.Moreover,whilst regional agreements and frameworks demonstrate active regional cooperation,both intergovern-mental and multi-sectoral,the absence of region-specific cooperation mechanisms focused on cruise tourism may undermine the needed dedication to foster a more regional cohesive regulatory environment for cruise tourism that should increasingly regulate for and incentivise sustainable cruise operations.4.2.3 National and Local Regulations National and local regulations play a crucial role in shaping the operational framework of cruise tourism and impact of the cruise sectors worldwide.These regulations are developed within the individual countrys legislation and are enforced by national governments and local authorities.National govern-ments,maritime authorities,national environmental agencies and health departments design and implement national regu-lations on maritime safety,pollution prevention,and labour standards,in line with international conventions.The exam-ples below illustrate how national and local authorities have applied regulations to mitigate the negative externalities of cruise tourism.89 United Nations Environment Programme,Nairobi Convention Secretariat and Council for Scientific&Industrial Research,(2023):“Towards Sustainable Port Development in the Western Indian Ocean.Scenario Analysis.”UNEP,Nairobi,Kenya90 Ibid.91 United Nations Environment Programme,(2015):The Amended Nairobi Convention for the Protection,Management and Development of the Marine and Coastal Environment of the Western Indian Ocean(Amended Nairobi Convention):Mahe,Seychelles.92 United Nations Environment Programme/Nairobi Convention and the International Maritime Organization,(2020):“Regional Oil Spill Preparedness in Eastern Africa and the Western Indian Ocean:Background Document.”4.Cruise Sector Governance 15 Box 1.National and Local Cruise Tourism Regulations Examples from the Caribbean regionPassenger Head Tax-Port FeesIn the late 1990s,CARICOM countries,with the support of the Caribbean Tourism Organisation(CTO),attempted to implement a regional“head tax”of around$20 per cruise passenger to manage the economic and environ-mental impact of cruise tourism.However,industry disa-greements over the tax rate led to the initiatives collapse,with countries pursuing their own policies instead.Today,nations like The Bahamas and the British Virgin Islands charge a$15 head tax,reinvesting the revenue into tourism infrastructure.Some countries,like Aruba and the British Virgin Islands,also impose environmental protec-tion fees to fund conservation projects.93Environmental regulationBahamas and Barbados,require cruise ships to comply with strict regulations regarding ballast water and waste discharge.It is illegal for cruise ships to discharge untreated sewage,greywater,or oily waste into their waters.Their waste must be treated on board or discharged at desig-nated facilities in ports.As a community-driven innovative initiative,a Barbados Marine Spatial Plan94 has also been implemented in Barbados to manage marine resources and reduce pollution,and regulate environmental issues also related to cruise industry activities.Green Port InitiativesSt.Lucia and St.Vincent and the Grenadines are actively participating in the Caribbean Green Economy Initiative,95 which promotes sustainable port operations.This includes reducing the environmental impact of cruise ships through measures such as waste reduction,energy efficiency,and the promotion of eco-friendly shore excursions.Examples in Europe Venice Over the past decade,the number of cruise ships visiting Venice annually grew significantly,with their size doubling,raising concerns on environmental degra-dation,prompting calls for a sustainable development plan.96 In 2021,the Italian government banned cruise ships and other large vessels from the Venice Lagoon,redirecting them to the nearby industrial port of Margh-era.97 Additionally,cruise ships are required to use cleaner fuels and advanced technologies to minimise emissions.The enforcement of these measures is overseen by the Venice Port Authority and Italian environmental agen-cies.Nevertheless,despite this regulatory effort,critics argue that shifting large cruise ships to the industrial port 93 Government of Virgin Islands,(2018):“Visitors to the Virgin Islands are being reminded of the Environmental and Tourism Levy.”94 Barbados Marine Spatial Plan95 UNEP,(2024):“Assisting Caribbean States Sustainable Development through Green Economy(ACSSD-GE)”96 Figueroa D.,(2021):“Italy:Cruise Ships Banned from Venice Lagoon,Waterways Declared National Monument.”The Library of Congress.97 Ibid.of Marghera does not entirely solve the environmental issues,as it merely relocates the pollution.Moreover,ensuring compliance with cleaner fuels and advanced technologies is challenged by limited enforcement resources.There are also concerns about the economic impact on Venices tourism sector and the adequacy of infrastructure at Marghera to handle the redirected cruise traffic efficiently.98AmsterdamA decision was approved by Amsterdam city council,aimed to ban large cruise ships from the citys central terminal to reduce pollution and manage the flow of tourists and in line Amsterdams sustainability goals and reduce the negative impact of cruise tourism on the envi-ronment and local infrastructure .99 The city has reached an agreement on steps to begin limiting the number of cruise ship calls at the port as of 2026.It is part of a larger plan to ultimately remove the cruise terminal from the city and manage the influx of tourists into the city.According to the recently disbanded Amsterdam Cruise Port founda-tion,the city was receiving as many as 150 cruise calls each year and handling over 300,000 passengers.In 2026,the new limit will be a maximum of 100 calls annually.Norway Norway has devised an ambitious strategy to cut emissions from cruise ships.The country welcomed nearly 5 million cruise ship passengers in 2023,100 with ships collectively consuming approximately 170 million litres of fuel annu-ally,contributing around 3 percent of Norways total green-house gas emissions.While most fuel is burned at sea,approximately 20 percentequivalent to nearly 34 million litresis consumed while ships are in port or navigating fjords.101 To address these concerns,2022,the Ministry of Climate and Environment tasked the Norwegian Maritime Authority(NMA)to devise plans for achieving zero emis-sions from cruise ships,tourist boats and ferries in fjords.From 2026,only ships powered by alternative fuels will be permitted to visit the countrys fjords,aiming to safeguard its unique natural landscapes from the adverse effects of marine diesel oil and unchecked tourism.Even liquefied natural gas(LNG),previously considered a cleaner option,will no longer meet the standards for cruise ships oper-ating in Norwegian fjords.102Source:Authors(2024)98 Giuffrida A.,(2022):“Cruise passengers shuttled into Venice by motor boat to dodge big ships ban.”The Guardian.99 CruiseCritic,(2023):“Amsterdam Votes to Ban Cruise Ships;Additional Steps Still Required.”100 Hanley S.,(2024):“Norway Moves Aggressively To Curb Cruise Ship Emissions.”Clean Technica.101 Ibid.102 Ibid.Policy Pathways Towards a More Sustainable Cruise Sector16 These case studies show the importance of national and local authorities in complementing existing international and regional frameworks regulating the cruise impact.None-theless,countries have different capacities and resources to enforce regulations and ensure compliance,which has contributed to the diffusion of the phenomenon of flags of convenience.This practice allows cruise ships to register in countries that often have more lenient regulatory frame-works,complicating or limiting enforcement mechanisms and transparency efforts103 The prevalence of flags of conven-103 Negret,C.F.L.,(2016):“Pretending to be Liberian and Panamanian;Flags of Convenience and the Weakening of the Nation State on the High Seas”.J.Mar.L.&Com.,47,1.7.ience underscores the challenges associated with regulating the cruise sector at national level and in having a cohesive and collaborating regulatory and,more broadly,governance mechanism at the level of marine regions.Such shortcom-ings are exacerbated by the high competitiveness character-ising the industry,leading States and cruise lines to prioritise economic gains over stringent regulatory compliance,leading to regulatory arbitrage and lapses in safety and environmental standards.104104 Ford,J.H.,&Wilcox,C.,(2019):“Shedding light on the dark side of maritime tradeA new approach for identifying countries as flags of convenience”.Marine Policy,99,298-303.Boat in Caribe.S.Bush/Pexel4.Cruise Sector Governance 17 5.Challenges and Opportunities for Sustainable Cruise GovernanceGiven the significant environmental,social,and economic externalities linked to the cruise sector,there is a pressing need for public and private decision-makers to prioritise sustaina-bility within the sector.This entails aligning international efforts aimed at reducing greenhouse gas emissions and protecting biodiversity.This section outlines related challenges and oppor-tunities in fostering a more sustainable cruise tourism sector.5.1.Challenges for SCTThe cruise sector faces challenges that hinder its sustaina-bility.From a supply side,while many leading cruise compa-nies acknowledge the urgent need to transition towards more sustainable practices,the pursuit of short-term financial gains often takes precedence over long-term sustainability objectives.105 This can lead to decisions that prioritise imme-diate financial benefits over broader environmental and social considerations.A short-term approach may allow cruise lines to maximise profits in the near term,potentially undermining long-term environmental conservation efforts.106 As a result,this underscores the importance of a cruise governance that increasingly favours cooperation and sustainability.Govern-ance and regulatory challenges are of two kinds:i)in the current design of regulations,at different levels,with gaps,fragmentation and inconsistencies across jurisdictions;ii)in the implementation phase of the regulations,at different levels,due to weak enforcements.5.1.1.Regulatory Gaps The cruise sector is subject to varying regulatory frameworks across jurisdictions.This can create degrees of inconsistencies across the regulatory cruise landscape,limiting the needed coherence and uniformity.107 While international organisa-tions,such as the IMO,establish a baseline and standards for safety and environmental protection,due to their international scope,individual countries remain responsible for interpreting and implementing these standards.As a result,different coun-tries can have stricter or weaker regulations,leading to a complex web of rules.For instance,national regulations pay different degrees of attention on aspects of sustainability,leading to different efforts by cruise lines on implementing eco-efficiency practices.108 This can potentially make compli-ance challenging for cruise lines operating in the itineraries.105 Jones,P.,Comfort,D.,&Hillier,D.,(2019):“Sustainability and the worlds leading ocean cruising companies”.Journal of Public Affairs.106 Avagyan,A.,(2022):“Addressing the Criticism on Flags of Convenience:Should Flags of Convenience Be Abolished for the Cruise Industry?”Southwestern Journal of International Law 28,129-147107 Boy,C.,&Neumann,S.(2012):“Regulatory frameworks of the cruise industry.”The business and management of ocean cruises.CABI,Wallingford/Cambridge,30-45.108 Sun,R.,Ye,X.,Li,Q.,&Scott,N.,(2024):“Assessing the eco-efficiency of cruise tourism at the national Level:Determinants,challenges,and opportunities for sustainable development”.Ecological Indicators,160,111768.Jamaica,Mauritius,and Turkey exemplify varying levels of effort in regulating the sustainability of the cruise sector,largely due to differences in the application and enforcement of international conventions.Jamaica has struggled with enforcing waste management regulations for vessels,particu-larly in smaller ports,where limited monitoring capacity has allowed some ships to discharge sewage into the ocean.109 Although the country has adopted MARPOLs pollution prevention standards,its enforcement is weaker compared to stricter regions like the U.S.and EU.Nonetheless,Jamaica has made progress in marine protection through the establish-ment of marine protected areas(MPAs)and regulations aimed at controlling pollution from cruise ships.Mauritius has faced challenges in enforcing shipping regu-lations,particularly regarding waste management and oil spill responses.The 2020 MV Wakashio oil spill exposed110 significant gaps in the countrys environmental and safety regulation implementation.Despite adhering to international conventions,Mauritius maritime industry is still developing its capacity for monitoring and compliance.Turkey,which experiences high maritime traffic through the Bosporus Strait,also faces challenges in enforcing environ-mental and safety regulations.While the government has made efforts to regulate air pollution from ships and adheres to MARPOL Annex VI,enforcement is inconsistent,particu-larly outside EU waters.Turkeys oversight of ballast water management and oil spill preparedness has been criticised,highlighting the countrys limited capacity to control illegal discharges and emissions compared to stricter EU enforce-ment in the Mediterranean.Other countries like The Bahamas,Seychelles,and Greece have adopted proactive measures,often exceeding minimum IMO requirements to ensure stricter environmental protection and safety compliance.These disparities create a fragmented regulatory landscape,where enforcement and compliance vary based on each countrys priorities and capabilities.In all cases,the varying degrees of enforcement highlight the challenges countries face in aligning their national legisla-tion with international sustainability standards for the cruise sector,with differing levels of compliance based on resources and capacity,resulting in inconsistent approaches among countries.Moreover,not all potentially harmful impacts of cruise tourism are regulated at global level.For example,limited global regu-lations on grey water discharge to the sea is one area that needs further attention.Local bans on the discharge of grey-water have been set by individual States,e.g.Bahamas and Barbados.Although it is less contaminated than sewage,grey water contains components of concern.111 Regulatory gaps can be identified at the jurisdiction and port levels.The most relevant gaps lie in the enforcement of safety and environ-mental regulations by flag States.Attention has been given to the discharge of wash water from open-loop scrubbers 109 World Bank,(2019):“Marine Pollution in the Caribbean:Not a Minute to Waste.”110 Scarlett,et al.(2021):“MV Wakashio grounding incident in Mauritius 2020:The worlds first major spillage of Very Low Sulfur Fuel Oil.”111 Andersson,K.,et al.,(2016):“Shipping and the Environment.Springer Berlin Heidelberg.”Policy Pathways Towards a More Sustainable Cruise Sector18 impacting ecosystems112 with countries taking steps in regu-lating the discharge and some not indicating gaps in their regulatory framework on open loop scrubbers.Below is a list of countries that,as per June 2024,did not have regulations in open loop scrubbers:112 Picone,et al.,(2023):“Impacts of exhaust gas cleaning systems(EGCS)discharge waters on planktonic biological indicators.”113 North Standard,(2024):“No Scrubs:Countries and Ports where Restrictions on EGCS Discharges apply.”Table 3.Countries Permitting Open-Loop Scrubber DischargeCountryOpen-Loop Scrubber RegulationHong Kong While a ban on EGCS(Exhaust Gas Cleaning System)wastewater is not explicitly stated,Hong Kong regulation L.N 135 of 2018 allows an exemption from the use of non-compliant fuel if authorities are satisfied with the abatement technology employed to reduce sulphur dioxide emissions.New Zealand Maritime New Zealand has issued non-statutory guidance on the use of exhaust gas cleaning systems(scrubbers)for ships,ports,and regional authorities.While not legally binding,the guidance encourages ships operating in New Zealand waters to engage with relevant authorities and,as a precaution,avoid discharging scrubber effluent near shore.Suggested measures include using compliant low-sulphur fuel in sensitive environments or operating scrubbers in closed-loop mode,retaining effluent until disposal at the next available port facility.United States(Hawaii)The State of Hawaiis Clean Water Branch issued a Blanket Section 401 Water Quality Criteria(WQC),covering 27 categories of effluent discharge from applicable vessels,including Exhaust Gas Cleaning System(EGCS)wash water.These discharges,incidental to normal vessel operations,must receive the best available control or treatment before entering Hawaiis waters.United Arab Emirates Abu Dhabi Ports has confirmed that,under national legislation,both closed and open-loop exhaust gas cleaning systems are permitted within port limits,with certain restrictions.These systems must comply with IMO/MARPOL Annex VI requirements and standards.Source:Elaborated from NorthStandard(2024)113These gaps have direct effects on limiting pollution locally.In addition to the importance of having a comprehensive regula-tory framework at national level,it is crucial to integrate these regulations into regional mechanisms fostering cohesion and to allow countries to scale up their enforcement ability at national level.Regional frameworks have the potential to be effective by boosting local self-reliance,addressing the effects of high competition on sustainability transitions,and counterbalancing the market power of the cruise industry.Non-mandatory guidelines for cruise sustainability114 covering a variety of operational aspects of cruise operations,while being valuable,do not always compensate for the lack of mandatory rules.For example,a study conducted by the EU concluded that important gaps still exist in the regulation of food waste,grey water,under and over water noise,black carbon,scrubber wash water,and mammal collisions.115 This is shown by MARPOL Annex V which allows for the discharge of garbage,food waste,cargo residues(classified as non-harmful to the marine environment),cleaning agents and additives(classified as non-harmful to the environment)contained in wash water,and carcasses of animals.116 Restric-tions are set for certain special areas designated by IMO,such as the Mediterranean Sea,the Baltic Sea,the Black Sea,the Red Sea,the Gulfs,the North Sea,the Wider Caribbean Region and the Antarctic area.Nevertheless,this material might cause local impacts on the environment in areas with dense ship traffic.5.1.2.Weak Monitoring Enforcement Regulatory inconsistencies and gaps,as discussed earlier,reveal a broader issue of weak enforcement and compliance mechanisms that undermine the effectiveness of existing regulations.Even when regulations are established,enforce-ment weaknesses often render them ineffective due to several contributing factors.One significant issue is the prevalence of the“Flag of Convenience(FoC)”(Box 2),where many cruise ships are registered in countries that offer more lenient regu-lations rather than operating under the jurisdiction where they primarily sail.This practice leads to weaker regulatory over-sight and enforcement by Flag States(or FoC),resulting in lax adherence to international standards.Moreover,while Port States have the authority to inspect foreign ships and enforce compliance with international and national regulations,resource constraints and varying national priorities can lead to inconsistent enforcement across different ports.117 While many national and port authorities are responsible for moni-toring cruise ship compliance when docked,they often lack the technology,financial resources,or jurisdiction to continu-ously track environmental compliance,especially concerning air pollution,waste disposal,and ballast water management.This limits their ability to effectively enforce stringent stand-ards.118 Furthermore,many ports rely on the cruise industry for revenue and tourism,creating potential conflicts of interest 114 Plan Bleu,(2022):“Guidelines for the sustainability of cruising and recreational boating in the Mediterranean region.”115 European Commission,Directorate-General for Maritime Affairs and Fisheries.(2023):“Good Practices for Sustainable Cruise Tourism”-Final report.Publications Office of the European Union.116 MARPOL,Annex V.“Prevention of Pollution by Garbage from Ships.”117 Ibid.118 Tonazzini,D.,Fosse,J.,Morales,E.,Gonzlez,A.,Klarwein,S.,Moukaddem,K.,Louveau,O.(2019):“Blue Tourism.Towards a sustainable coastal and maritime tourism in world marine regions”.Edited by eco-union.Barcelona5.Challenges and Opportunities for Sustainable Cruise Governance19 that may result in leniency in enforcement.This inconsistency highlights the need for cruise-specific regional coopera-tion to improve enforcement and facilitate resource sharing effectively.Examples of challenges in enforcing cruise regulations or more sustainable practices include Key West,Florida,and Venice,Italy.Key West has experienced difficulties in enforcing local regulations on cruise ships,particularly regarding passenger limits.The city has struggled to manage the size and number of cruise ships visiting its port,leading to overcrowding and strain on local resources.119 Similarly,Venice has faced signif-icant challenges in enforcing regulations on cruise ships due to high tourist traffic and lack of alternative infrastructures120.Regulations designed to limit the size and frequency of cruise ships entering the citys historic canals have seen inconsistent enforcement.These examples illustrate how enforcement challenges,exacerbated by weak compliance mechanisms and varying regulatory priorities,can undermine efforts to manage cruise tourism sustainably.They highlight the need for more robust regional cooperation and effective enforce-ment strategies to address these persistent issues.Given the global operations of cruise ships,combined with the widespread use of flags of convenience,ensuring compli-ance with regulatory requirements becomes even more challenging,compromising efforts to promote sustainability,protect the environment,and ensure the safety and well-being of workers and passengers aboard cruise ships.121 Box 2 provides a detailed explanation of the role of“flag of conveni-ence in context of cruise tourism and its sustainability.Box 2.Flags of Convenience(FoC)in the Cruise IndustryThe practice of registering ships under a“Flag of Conven-ience”(FoC)occurs when a cruise company registers its vessels in a foreign country with more lenient regulations than those of the companys home nation.These coun-tries,often referred to as“Flag States”provide various incentives such as lower taxes,minimal regulatory over-sight,and weaker labour laws,making them attractive to businesses seeking to reduce operational costs.122 One of the primary benefits for cruise companies to use FoC is to take advantage of lower taxes in the flag state.Many of these countries offer tax breaks to attract ship registrations.This allows cruise companies to reduce their tax liabilities significantly,keeping more profits while avoiding the higher corporate taxes of their home coun-tries.123 FoC countries often have less stringent labour regulations.This allows cruise companies to circumvent more rigorous protections for workers that might be required under domestic law.For example,minimum wage standards,working conditions,and safety regulations are 119 The Maritime Executive,(2024):”Florida Permits Larger Cruise Ships in Key West Over Local Objections.”120 Euronews,(2023):“Ive lived in Venice for 8 years.Why are cruise ships still stopping here when theyve been banned?”121 Avagyan,A.,(2022):“Addressing the Criticism on Flags of Convenience:Should Flags of Convenience Be Abolished for the Cruise Industry?”.Southwestern Journal of International Law 28,129.122 Ibid.123 Boczek,B.A.,(1962):“Flags of Convenience:An International Legal Study,”Cambridge,MA and London,England:Harvard University Press,.often less strictly enforced.124 Many Flag States do not rigorously enforce international environmental standards related to waste disposal,emis-sions control,or pollution.As a result,cruise companies are able to engage in practices such as discharging waste into international waters or burning fuels that generate higher levels of pollution,all without significant penalties or oversight.125 In this sense,while FoC practices offer significant economic advantages to cruise companies,they come at a cost to sustainability,labour rights,and environmental protection.These gaps in regulation allow the cruise industry to continue practices that contribute to environmental degradation and social inequities.124 Negret,Carlos Felipe Llins.“Pretending to be Liberian and Panamanian;Flags of Convenience and the Weakening of the Nation State on the High Seas.J.Mar.L.&Com.47(2016):1.125 Demaria,F.,(2010):“Shipbreaking at AlangSosiya(India):An ecological distribution conflict.”Ecological Economics.B.Nelson/Unsplash.Policy Pathways Towards a More Sustainable Cruise Sector20 Despite the relevant challenges affecting the cruise sectors ability to shift towards more sustainable practices,there are promising opportunities to pursue.These opportunities focus on building upon existing regulatory frameworks and govern-ance mechanisms,enhancing the role of ports,and lever-aging technological developments alongside sustainability certifications.5.2.Regulatory and Governance Opportunities Existing global and regional organisations and related instru-ments,in collaboration with national entities,can guide regulatory assessments at various levels and identify actions to enable more sustainable cruise tourism operations,such as reducing emissions,improving waste management,and enforcing environmental regulations.They can also support the establishment of sector-specific governance mechanisms to oversee the cruise sectors environmental and operational practices.Existing frameworks,such as the MARPOL regula-tions,provide a solid foundation for expanding sustainability within the cruise sector.Since its inception in 2005 to address ship-related air pollution,MARPOL Annex VI has undergone amendments that have broadened its scope and tightened environmental standards.A notable example is the IMO 2020 regulation,which mandated a significant reduction in ships allowable sulphur content in fuel oil from 3.5%to 0.50%.126 Similarly,several regional and national authorities have imple-mented additional regulations and initiatives to complement the provisions of MARPOL Annex V.For example,efforts to reduce plastic pollution from ships,such as the EU Directive on Port Reception Facilities for the Delivery of Waste from Ships,127 provide opportunities for sharing best practices and scaling successful regulatory models across other regions or expanding initiatives to larger geographical areas.Addition-ally,existing international organisations can function as plat-forms to harmonise national regulatory frameworks and align them with common regional objectives.This can be achieved through global forums,policy roundtables,and collaborative initiatives.These organisations can also promote collabora-tion among stakeholders with varying interests.Moreover,intergovernmental organisations can develop and enforce strict regulations,identify gaps in existing policy,address loopholes,and facilitate knowledge sharing and collabora-tion.Regional bodies,such as the Organization of Eastern Caribbean States(OECS)or the EU,can enhance regional cooperation and tailor regulations to address specific regional challenges and needs.126 IMO,(2023):“The 2020 global sulphur limit-Frequently Asked Questions.”127 EUR-Lex,(2022):“Port facilities for waste from ships,including cargo residues”.5.2.1.Enhancing the Role of Ports DestinationsThe role of ports in enhancing the sustainability of the cruise industry is pivotal,as they serve as pivotal hubs where land and sea operations intersect.Ports offer numerous opportu-nities to pilot innovative solutions that mitigate environmental impacts.For instance,they can significantly reduce air pollu-tion and greenhouse gas emissions by providing shore power facilities,allowing ships to connect to the local electrical grid rather than running their engines while docked.This not only reduces emissions but also decreases noise pollution,bene-fiting local communities.Additionally,ports can implement advanced waste manage-ment systems to ensure the proper handling,recycling,and disposal of ship-generated waste,supporting the circular economy and reducing the environmental footprint of cruise operations.They also have the potential to act as centres of innovation by adopting and promoting the use of cleaner fuels,such as hydrogen,and facilitating the bunkering of these fuels.Moreover,ports can influence sustainable prac-tices by setting stringent environmental standards for visiting ships,driving the entire industry towards more sustainable practices.For example,the Venice Port Authority has imple-mented enforcement measures to ban cruise ships that do not use cleaner fuels and advanced technologies to minimise emissions.Through these efforts,ports play a crucial role in shaping the environmental performance and sustainability trajectory of the cruise sector.128 Furthermore,integrating local supply chains into the sustain-ability strategies of cruise destinations can enhance the envi-ro
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