2025年全球科技：无人驾驶出租车市场：商业化之路研究报告（英文版）

Note:Thefollowingisaredactedversionoftheoriginalreportpublished6May2025[34pgs].

GoldmanResearchSachs

EQUITYRESEARCH|May6,2025|6:21AMHKT

GlobalTechnology

Robotaxi

China'sRobotaximarket-theroadtocommercialization

With500,000Robotaxisexpectedtobeoperatingacross10+citiesinChinaby2030,webelievethequestionisnolongerifL4autonomoustechnologyisready,butoneofhowcompanieswillcommercializetherapidpaceofautonomousdevelopment.WeseeRobotaxisasoneoftheearliestandmostvisibleavenuesto

commercializationoftheautonomoustechnology,withgrowingconsumeracceptanceacrosslargeTier1cities,atighteningsupplyofhumandriversasthefleetsmatureanddriversretire,andwithGovernmentandinsuranceindustryasenablerstosupportgrowth.WeseebothasizeableTAMopportunityahead-US$47bnby2035,aswellasapathtoprofitability,modellingpositivegrossmarginsinearly2026forTier1cities.Keyfactorsto

watch:

1Decreasingcostsofhardwareandalgorithms:OurforecastforChina'sRobotaxiTAMof$47bnby2035Evs.$54mnin2025isdrivenbydecreasingcostsofhardwareandalgorithmsandloweringoperatingcostsforfleetowners.Theformfactorisaswingfactor:Robotaxishavethepotentialtotransformproductivityoftimespentincars,turningvehiclesintoentertainmenthubsorprivateworkspace,gainsthatmaysignificantlyincrease

consumerdemand.SupportiveGovernmentpolicies/licensing,andthedevelopmentofinsurancefortheindustryarebothneededtosupportgrowth.Accidentratesremainacrucialswingfactorforexpandingcustomeracceptanceandreputationrisk.

2Uniteconomicsturningprofitable,encouragingmoresuppliers:By2035E,weexpectrevenuesperRobotaxiinTier-1citiestoreach$31,000,higherthancurrentridehailingvehicles,duetolongeroperatinghoursand

efficientrouteplanning.Wemodelpositivegrossmarginatthevehiclelevelby2026E/2031E/2034EinT1/T2/othercities.

AllenChang

+8522978-2930

allen.k.chang@

GoldmanSachs(Asia)L.L.C.

VerenaJeng

+852-2978-1681

verena.jeng@

GoldmanSachs(Asia)L.L.C.

MarkDelaney,CFA

+1(212)357-0535

mark.delaney@

GoldmanSachs&Co.LLC

RonaldKeung,CFA

+852-2978-0856

ronald.keung@

GoldmanSachs(Asia)L.L.C.

GoldmanSachsdoesandseekstodobusinesswithcompaniescoveredinitsresearchreports.Asaresult,investorsshould

beawarethatthefirmmayhaveaconflictofinterestthatcouldaffecttheobjectivityofthisreport.Investorsshould

considerthisreportasonlyasinglefactorinmakingtheirinvestmentdecision.ForRegACcertificationandother

importantdisclosures,seetheDisclosureAppendix,orgoto

/research/hedge.html.Analysts

employedby

non-USaffiliatesarenotregistered/qualifiedasresearchanalystswithFINRAintheU.S.

ContributingAuthors

AllenChang

+852-2978-2930

allen.k.chang@

GoldmanSachs(Asia)L.L.C.

VerenaJeng

+852-2978-1681

verena.jeng@

GoldmanSachs(Asia)L.L.C.

MarkDelaney,CFA

+1(212)357-0535

mark.delaney@GoldmanSachs&Co.LLC

RonaldKeung,CFA

+852-2978-0856

ronald.keung@

GoldmanSachs(Asia)L.L.C.

KotaYuzawa

+81(3)4587-9863

kota.yuzawa@

GoldmanSachsJapanCo.,Ltd.

LincolnKong,CFA

+852-2978-6603

lincoln.kong@

GoldmanSachs(Asia)L.L.C.

TinaHou

+86(21)2401-8694

tina.hou@GoldmanSachs(China)

SecuritiesCompanyLimited

ThomasWang

+852-2978-1697

thomas.wang@

GoldmanSachs(Asia)L.L.C.

EricSheridan

+1(917)343-8683

eric.sheridan@

GoldmanSachs&Co.LLC

BenMiller

+1(917)343-8674

ler@GoldmanSachs&Co.LLC

XuanZhang

+852-2978-1478

xuan.zhang@

GoldmanSachs(Asia)L.L.C.

GoldmanSachsGlobalRobotaxi

TableofContents

ChinaRobotaxiTAMSnapshot3

ChinaRobotaxiTAMindetails

5

GlobalRobotaxiTAMscenarios

6

(1)Marketsize?700xChinaRobotaxiTAMgrowthinthenext10years6 (2)Penetration?25%by2035tofillthelabourgapoftaxidrivers7 (3)Elementsofsuccess?Technologyandexperience9

(4)Revenuesgeneration?Upto$31kpervehicleintier-1citiesby2035E9 (5)Costsreduction?Downto$19kpervehicleintier-1citiesin2035E10 (6)Uniteconomics?Profitmakingby2026E/31E/34EinTier-1/-2/othercities12 (7)Operatingleverage?Increasingoperatingprofitsasbusinessscales13 (8)Downsiderisk?Profitabilityissensitivetocompetition14 (9)Downsiderisks?Accidentscandamagereputation15 (10)WheretofindRobotaxis?10+citieswithRobotaxiservicesinChina15

(11)Policyprogress?Supportivepolicieswithmoreoperatingareas16

(12)Insurancesupport?Stillinearlystageofdevelopment18

(13)ReasonstouseRobotaxi?Anewridingexperiencewithentertainment18

(14)Futureformfactors?Withoutsteeringwheels,butwithroboticarms,Alanddrones19

(15)Futuremarketsegmentation?Wideningchoiceofcarmodels20

(16)Potentialup-scalingmethods?Collaborationwithridingplatforms21

(17)Potentialup-scalingmethods?Shared-ownershiptoencourageadoption22

(18)Whattoimprove?Densityandfleetcoverage23

(19)Whattoimprove?Cleaningandmaintenance23

(20)Whattoimprove?Algorithmenhancedbyworldmodel24

(21)Howtoevaluatesafety?Sensors,drivingstylesandemergencymeasures25

(22)Howtoenhancesafety?Combinedeffortinsoftware,hardware,andregulations25DisclosureAppendix27

GoldmanSachsGlobalRobotaxi

ChinaRobotaxiTAMSnapshot

ChinaRobotaximarket:US$47Bopportunityby2035E,comparedtoUS$54min2025

cityRobotaxi■Tier-2cityRobotaxi■Othercities

50,000

45,000

40,000

35,000

30,000

+96%

25,000

20,000

15,000

10,000

5,000

20242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

(US$m)

■Tier-1

ChinaRobotaxiFleet:1.9Mby2035Ewith25%penetrationtototalsharedmobilityvehicles,vs.4,000in2025Ewith0.1%penetration

('000)

2,000

1,800

25%

1,600

1,400

20%

1,200

1,000

800

10%

600

400

5%

200

0

2025E2030E2035E

■Shanghai

■Shenzhen

■Othercities

■Beijing

■Guangzhou

■Tier-2cities

●Robotaxipenetrationrate

30%

0%

15%

Fleetsizeby2030(E):Tier-1cities270K;Nationwide474K

(000

BeijingShanghaiGuangzhouShenzhenFleetsizeby2035(E):Tier-1cities622K;Nationwide1.9M

('000)

117

PonyAl,85

67PonyAl,41

34

20

Shanghai

PonyAI,

93

Guangzhou

PonyAl,41

others55

Others31

Beijing

Shenzhen

Others,

Others

20

20

Ordersperday:29ordersperdayinTier-1citiesby2035E

Tier-1

Tier-2

Others

ASPperorder(US$):$3.0perorderinTier-1citiesby2035E

3.5(US$)

3.0

2.5

2.0

1.5

1.0

0.5

0.0

20242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

Tier-1Tier-2Others

Faresperkm(US$):$0.3inTier-1citiesby2035EOperatingdistanceperday(km):284inTier-1citiesby2035E

0.45(US$)0.40

0.350.300.25

0.200.15

0.10

90

0.05

40

20242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

20242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

Tier-1Tier-2Others

Others

273278

179191

340

290

Tier-1

Tier-2

216

101

(km)

284

138

257

268

240

244

190

140

94

Source:Companydata,GoldmanSachsGloballnvestmentResearch

GoldmanSachsGlobalRobotaxi

ChinaRobotaxiTAMindetails

Exhibit2:ChinaRobotaxiTAM:increasingfromUS$54mntoUS$47bnin2025-35EChinaRobotaxiTAM

1.ChinaRobotaxiTAM(US$m)

2024

2025E

2026E

2027E

2028E

2029E

2030E

2031E

2032E

2033E

2034E

ChinaRobotaxiTAM

10

54

206

606

1,703

4,313

11,711

18,637

26,306

33,924

40,538

46,568

Tier-1cityRobotaxi

6

40

156

484

1,457

3,335

8,064

11,351

14,189

16,492

17,866

19,457

Tier-2cityRobotaxi

3

12

29

66

181

785

2,835

5,374

9,272

14,334

19,161

23,150

Othercities

1

3

21

56

65

193

812

1,912

2,845

3,098

3,512

3,961

Mix

100%

100%

100%

100%

100%

100%

100%

100%

100%

100%

100%

100%

Tier-1cityRobotaxi

60%

73%

76%

80%

86%

77%

69%

61%

54%

49%

44%

42%

Tier-2cityRobotaxi

29%

22%

14%

11%

11%

18%

24%

29%

35%

42%

47%

50%

Othercities

10%

5%

10%

9%

4%

4%

7%

10%

11%

9%

9%

9%

Byoperators

10

54

206

606

1,703

4,313

11,711

18,637

26,306

33,924

40,538

46,568

PonyAl

1

9

31

88

371

1,305

4,964

7,803

10,918

12,807

14,631

16,416

Baidu

9

33

124

378

569

757

1,247

2,119

3,073

3,687

4,204

4,624

Others

0

13

51

140

764

2,251

5,501

8,714

12,315

17,430

21,704

25,529

2.RobotaxiRevenuespervehicle

2024

2025E

2026E

2027E

2028E

2029E

2030E

2031E

2032E

2033E

2034E

2035E

Revenuespervehicle(US$'000)

8

13

18

23

24

24

25

25

25

25

25

25

Tier-1city

9

14

20

26

26

28

30

31

31

31

31

31

Tier-2city

8

12

16

17

17

17

19

20

21

22

22

22

Othercities

5

8

11

12

13

13

15

17

18

19

20

20

YoY%

107%

62%

36%

25%

6%

0%

3%

0%

1%

1%

0%

-1%

Tier-1city

40%

51%

43%

29%

0%

6%

6%

3%

2%

0%

0%

0%

Tier-2city

104%

59%

33%

5%

1%

1%

10%

4%

6%

5%

2%

0%

Othercities

133%

56%

31%

13%

3%

4%

15%

9%

8%

4%

4%

0%

Faresperkm(US$)

Tier-1city

0.40

0.40

0.40

0.40

0.38

0.36

0.33

0.33

0.32

0.31

0.31

0.30

Tier-2city

0.32

0.32

0.32

0.32

0.30

0.27

0.26

0.25

0.24

0.24

0.23

0.23

Othercities

0.26

0.26

0.26

0.26

0.24

0.22

0.21

0.20

0.19

0.19

0.19

0.18

YoY%

Tier-1city

0%

0%

0%

0%

-6%

-6%

-6%

-2%

-2%

-2%

-2%

-2%

Tier-2city

0%

0%

0%

0%

-8%

-8%

-5%

-5%

-2%

-2%

-2%

-2%

Othercities

0%

0%

0%

0%

-8%

-8%

-5%

-5%

-2%

-2%

-2%

-2%

Operatingdistanceperday(km)

Tier-1city

94

101

138

179

191

216

244

257

268

273

278

284

Tier-2city

95

107

137

144

158

173

200

219

236

253

264

270

Othercities

Travelleddistanceperday(km)

84

94

117

132

149

168

204

235

258

274

290

296

Tier-1city

200

220

300

360

360

380

420

440

440

440

440

440

Tier-2city

225

275

350

350

350

375

475

475

525

550

550

550

Othercities

Utlizationrate

240

240

300

330

330

420

510

510

600

630

630

630

Tier-1city

47%

46%

46%

50%

53%

57%

58%

59%

61%

62%

63%

65%

Tier-2city

42%

39%

39%

41%

45%

46%

42%

46%

45%

46%

48%

49%

Othercities

Revenuespervehicleday(US$)

35%

22

39%

36

39%

49

40%

62

45%

66

40%

66

40%

68

46%

68

43%

68

44%

69

46%

69

47%

69

Tier-1city

38

41

56

72

72

77

82

84

86

86

86

86

Tier-2city

30

34

44

46

47

47

52

54

57

60

61

61

Othercities

22

24

30

34

35

37

42

46

50

52

54

54

Operatingdays

Tier-1city

250

350

365

365

365

365

365

365

365

365

365

365

Tier-2city

250

350

365

365

365

365

365

365

365

365

365

365

Othercities

250

350

365

365

365

365

365

365

365

365

365

365

Numberofordersperday

Tier-1city

14

15

21

27

27

27

28

29

29

29

29

29

Tier-2city

14

15

19

20

20

20

20

20

21

22

22

22

21

Othercities

14

15

16

17

17

17

18

18

19

20

21

ASPperorder(US$)Tier-1city

2.6

2.6

2.6

2.7

2.7

2.9

3.0

3.0

3.0

3.0

3.0

3.0

Tier-2city

2.2

2.3

2.3

2.3

2.3

2.4

2.6

2.7

2.7

2.7

2.8

2.8

2.6

OthercitiesFleetsize

1.5

1.6

1.9

2.0

2.1

2.2

2.3

2.6

2.6

2.6

2.6

1.Robotaxivolume

2024

2025E

2026E

2027E

2028E

2029E

2030E

2031E

2032E

2033E

2034E

2035E

Robotaxivolume(units'000)

1.3

4.1

11.4

26.9

71.0

179.3

473.5

756.3

1,054.1

1,347.7

1,609.4

1,861.3

Tier-1cities

0.7

2.8

7.7

18.5

55.3

119.1

270.4

368.9

451.2

526.5

571.0

621.7

Beijing

0.2

0.9

2.8

6.3

20.7

44.2

105.9

134.8

172.2

205.3

221.8

243.2

Shanghai

0.1

0.5

0.7

2.6

8.9

20.5

53.2

86.5

114.5

137.3

152.4

171.3

Guangzhou

0.2

1.0

3.0

6.6

17.6

34.8

63.5

84.4

93.4

104.9

111.1

115.5

Shenzhen

0.1

0.5

1.2

3.0

8.1

19.6

47.8

63.2

71.0

78.9

85.6

91.7

Tier-2cities

0.4

1.0

1.8

3.9

10.7

45.8

150.4

274.0

446.2

657.3

859.2

1,037.6

Othercities

0.2

0.3

1.9

4.6

5.1

14.4

52.7

113.5

156.7

163.9

179.3

202.0

YoY%

95%

224%

178%

136%

164%

152%

164%

60%

39%

28%

19%

16%

2.SharedMobilityandPenetration(Taxi+Ridehailing+Rob

Sharedmobilityfleetvolumebycity(m)

4.6

otaxi)

4.8

4.9

5.0

5.0

5.1

5.5

5.9

6.3

6.7

7.0

7.4

Tier-1cities

1.0

1.1

1.2

1.2

1.3

1.3

1.4

1.5

1.5

1.6

1.7

1.8

Tier-2cities

2.5

2.6

2.6

2.7

2.7

2.8

2.9

3.1

3.2

3.4

3.5

3.7

Othercities

1.1

1.2

1.1

1.1

1.0

1.0

1.2

1.4

1.5

1.7

1.8

1.9

YoY%

10%

6%

2%

2%

1%

2%

7%

7%

7%

6%

6%

5%

Sharedmobilityfleetvolumebyoperation(m

4.6

4.8

4.9

5.0

5.0

5.1

5.5

5.9

6.3

6.7

7.0

7.4

4.3

Ridehailingfleet

3.2

3.5

3.5

3.6

3.6

3.6

3.7

3.8

3.9

4.0

4.1

Taxifleet

1.4

1.4

1.4

1.4

1.4

1.4

1.4

1.3

1.3

1.3

1.3

1.3

Robotaxifleet

0.0

0.0

0.0

0.0

0.1

0.2

0.5

0.8

1.1

1.3

1.6

1.9

YoY%

10%

6%

2%

2%

1%

2%

7%

7%

7%

6%

6%

5%

25%

35%

Tier-1cities

0%

0.3%

1%

2%

4%

3%

9%

19%

25%

17%

29%

33%

23%

34%

Beijing

0%

0.2%

1%

1%

4%

9%

20%

24%

29%

33%

34%

35%

Shanghai

0%

0.1%

0%

1%

3%

6%

14%

22%

27%

31%

33%

35%

Guangzhou

0%

0.5%

1%

3%

7%

14%

24%

31%

32%

35%

35%

35%

Shenzhen

0%

0.3%

1%

2%

4%

10%

23%

29%

31%

33%

34%

35%

Tier-2cities

0%

0.0%

0%

0%

0%

2%

5%

9%

14%

19%

24%

28%

Othercities

0%

2024

0.0%

2025E

0%

2026E

0%

2027E

0%

2028E

1%

2029E

4%

2030E

8%

2031E

10%

2032E

10%

2033E

10%

2034E

11%

2035E

Robotaxivolumebycompany(units'000)

1.3

4.1

11.4

26.9

71.0

179.3

473.5

756.3

1,054.1

1,347.7

1,609.4

1,861.3

PonyAl

0.1

0.6

1.6

3.9

15.2

51.2

180.8

294.4

404.8

465.5

521.3

573.5

Baidu

1.0

2.1

5.4

12.1

18.2

25.5

45.0

76.5

110.9

133.1

151.7

166.9

Others

0.1

1.4

4.4

10.9

37.6

102.5

247.7

385.5

538.4

749.1

936.4

1,120.9

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

GoldmanSachsGlobalRobotaxi

GlobalRobotaxiTAMscenarios

OurAutonomousVehicles(AVs)forecastimpliesthataglobalfleetofafewmillioncommercialAVsusedforridesharecouldbeontheroadin2030.Althoughthis

wouldcompriselessthan1%oftheglobalcarparcofover1bnvehicles,itcouldresultina>$25bnmarketforpersonalmobilityfromrobotaxis(dependingon

factorssuchasASPs,tripsperday,andaveragemilestraveledpertrip).Weassumetheinternationalmixofthebusinessaffectsrevenuepertripinthis2030scenario.More

optimisticscenariosonutilizationandASPswouldimplya$100bn+marketin2030.

Exhibit3:Weestimatethemarketin2030forrobotaxiscouldbe>$25bn

2030marketscenariosforrobotaxis($mn)

Tripsper

robotaxiperday

3,3004,000

GlobalAV1,350

Revenue

pertrip

150750

sinoperation(000s)2,0002,650

$14,600$29,200

$43,800$58,400

$73,000

$87,600

$102,200

$20,440

$40,880

$61,320

$81,760

$102,200

$122,640

$143,080

$26,280

$52,560

$78,840

$105,120

$131,400

$157,680

$183,960

$12,045

$24,090$36,135

$48,180$60,225

$72,270$84,315

$16,863

$33,726

$50,589$67,452$84,315$101,178

$118,041

$21,681$43,362$65,043$86,724$108,405$130,086

$151,767

$4,928$9,855$14,783$19,710$24,638$29,565

$34,493

$6,899$13,797$20,696$27,594$34,493$41,391

$48,290

$8,870$17,739$26,609$35,478$44,348$53,217$62,087

$9,673$19,345$29,018$38,690$48,363$58,035

$67,708

$13,542$27,083

$40,625$54,166

$67,708

$81,249$94,791

$17,411$34,821$52,232$69,642$87,053$104,463

$121,874

$2,738$5,475$8,213$10,950$13,688$16,425

$19,163

$3,833$7,665$11,498$15,330$19,163$22,995

$26,828

$4,928$9,855$14,783$19,710$24,638$29,565

$34,493

$548

$1,095

$1,643$2,190

$2,738

$3,285$3,833

$767$1,533$2,300

$3,066$3,833

$4,599

$5,366

$986$1,971$2,957$3,942$4,928$5,913$6,899

2

4

6

8

10

12

14

2

4

6

8

10

12

14

2

4

6

8

10

12

14

$5

$7,300$14,600$21,900$29,200$36,500$43,800

$51,100

$10,220$20,440

$7

$30,660$40,880

$51,100

$61,320$71,540

$13,140$26,280

$9

$39,420

$52,560$65,700

$78,840$91,980

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

(1)Marketsize?700xChinaRobotaxiTAMgrowthinthenext10years

WeexpectChina'sRobotaximarkettogrowfromUSS$54millionin2025to

US$12billionin2030andUS$47billionin2035(Exhibit4).TheTAMwillarow757xinthe10yearsof2025-35,indicatingastrongmarketopportunity.Revenuegenerationismainlyfromridingfarecharges,whichwewilldiscussfurtherintherevenue

generationsessionofthereport.Overall,weexpecteachRobotaxicangenerateUS$69perdayby2035(vs.US$36in2025),whichwillbehigherthantraditionalride-hailing

vehicleswhichonaveragegenerateUS$28-56(Rmb200-450)perday,duetolongeroperatingtimes.

GoldmanSachsGlobalRobotaxi

Exhibit4:RobotaxiTAMinChina:increasingtoUS$47bnin3035

(US$m)

46,568

50,00045.00040,00035,00030,00025,00020,00015,00010,000 5,0000

■Tier-1cityRobotaxi

■Tier-2cityRobotaxi

40,538

■Othercities

33,924

26,306

18,637

11,711

4,313

606

1,703

54206

10

2024

2025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

Exhibit5:RobotaxifleetinChina:increasingto1.9mby2035,basedonforecastofmultiplerobotaxicompanies

(kunits)

2,000

1,800

1,600

1,400

1,200

1,000

800

600

PonyAl■Baidu■Others

474

1,609

1,348

1,054

756

1,861

400

179

71

27

200

1

4

11

0

20242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

WemodelChina'stotalRobotaxifleetsizetogrowfrom4.1thousandby2025to0.5millionby2030and1.9millionby2035(Exhibit5).Weexpecttheexisting

players,includingPonyAI,WeRide,BaiduApollotocontinuetobeamongthemajor

players,consideringthehightechnologicalentrybarrierandleaders'edgeinalgorithm,data,highdefinitionmap,operations,andpartnershipwiththecarOEMsandlocal

governments.RobotaxiswillbeaneffectivesupplementtoChina'spublictransportecosystem,inourview,consideringpotentialdrivershortagesduetotheaging

population.

Exhibit6:China'stotalnumberofridehailingvehicle,taxisandbuses

000)

Ridehailingvehicles

Taxi

Bus

(000)

Ridehailingvehicles

Taxi

Bus

20191,0401,392693

2020

1,120

1,394

704

2021

1,558

1,391

709

2022

2,118

1,362

703

20232,7921,367683

YoY%

Ridehailingvehicles

Taxi

Bus

20208%0%2%

2021

39%

0%

1%

202236%-2%

-1%

2023

32%

0%

-3%

Source:MinistryofTransportofPRC

(2)Penetration?25%by2035tofillthelabourgapoftaxidrivers

4milliondriversretiringby2035,perourestimate.AsurveybyTsinghuaUniversityshowsthattaxidriversagedabove46accountedfor31%oftheridehailingdriversinChinain2021.With13millionactiveride-hailingandtaxidriversinChina,thosewithinthe46-65agegroupin2021willmostlyretireby2035(agedover60),suggestingthat4milliondriverswillretireduring2021-2035.Weexpectthelaborgaptobepartially

fulfilledbyourestimated1.9munitsofrobotaxis(Exhibit7).

GoldmanSachsGlobalRobotaxi

Exhibit7:Weestimatetherewillbe4moftaxi/ridehailingdriverstoretireby2035

Agegroup

Agestructureofsharedmobilitydriversasof2021

%

#of

drivers(m)Remarks

56-65

6%

0.8Retiringby2025

46-55

25%

3.2Retiringby2035

26-45

65%

8.5

25andbelow

4%

0.5

Total

#ofdriversretiringby2035#ofrobotaxiperGSeby2035

#ofnewdriversneeded

100%

13.0

4.0

1.9

2.2

Source:ResearchreportontravelplaformsinChina'sfrst-tiercitiesbyTsinghuaUniversity,GoldmanSachsGloballnvestmentResearch,CompanydataThedrivershortagehasbecomeincreasinglyprevalentinChinaduetodemographic

changeandadeclininginterestamongyoungpeopleinpursuingthisprofession

(accordingtomediareports).In2024,multiplecitiesincludingShenzhen,Hangzhou,NingboandChengduannouncedtoextendthemaximumageoftaxidriversto65yearsold,inordertocopewiththepotentialdrivershortages.

Exhibit8:SharedmobilityfleetinChina(2025E,munits)

Exhibit9:SharedmobilityfleetinChina(2035E,munits)

(munits)

(munits)

3.5,72%

·Ridehailingfleet■Taxifleet·Robotaxifleet

·RidehailingfleetTaxifleet■Robotaxifleet

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

Source:Companydata,GoldmanSachsGlobalInvestmentResearch

Exhibit10:PenetrationcycleofRobotaxisinChina:Tier-1/Tier-2/Otherscities

Exhibit11:PenetrationcycleofRobotaxisinChina:vs.NEVandL4/L5technology

40%

35%

30%

25%

20%

15%

40%

RobotaxipenetrationinChina

一一RobotaxipenetrationinChina(Tier-1)

一RobotaxipenetrationinChina(Tier-2)

35%

30%

25%

RobotaxipenetrationinChina(others)

20%

15%

2011201220132014201520162017201820192020202120222023

一一L4/L5penetrationinChinaRobotaxipenetrationinChina

一

EQ\*jc3\*hps45\o\al(\s\up4(N),2)

EQ\*jc3\*hps45\o\al(\s\up4(V),11)

2e

EQ\*jc3\*hps45\o\al(\s\up4(e),2)

EQ\*jc3\*hps45\o\al(\s\up4(t),3)

rinChina(RHS,

40%

35%

30%

25%

20%

15%

10%10%

10%

5%

0%

5%5%

0%0%

202320242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

202320242025E2026E2027E2028E2029E2030E2031E2032E2033E2034E2035E

Robotaxipenetration=Robotaxifleet/(Robotaxi+traditionaltaxi+sharedridingvehiclefleet)

Robotaxipenetration=Robotaxifleet/(Robotaxi+traditionaltaxi+sharedridingvehiclefleet)

Source:Companydata,GoldmanSachsGlobalInvestmentResearchSource:Companydata,GoldmanSachsGlobalInvestmentResearch

ThepenetrationofrobotaxitotheoverallsharedmobilityfleetinChinawillincreasefrom<1%in2025,graduallyto9%by2030andaccelerateto25%by2035E,inourview.Theinitialrampupofrobotaxiadoptionwillbegradual,aswe

GoldmanSachsGlobalRobotaxi

expectrobotaxiplayerstostayprudent,expandingcarefullytotestthealgorithmandensuringsafety.Theywillalsoneedtimetobuildupacustomerfeedbacksystemandimproveservicequality.

(3)Elementsofsuccess?Technologyandexperience

Technologyandexperienceremainthecompetitivemoat.Webelievethatmileage,

disengagement,andaccidentrateareimportantelementstomeasurethereadinessofarobotaxiplayertoconductlargescaledeployment:(1)Testingmileage:mileageis

important,asitindicatesexperienceandsuccessfultrackrecord.(2)Milesper

disengagement:Theneedforhumaninterventionsreflectthedifferenceinthelevelofintelligence.(3)Activetrafficaccidentrate:Accidentratewillbeakeymetricto

monitorwhenrobotaxisbeginlargescalebusinessoperations.Traditionaltaxiscan

cause0.036fatalaccidentperbnkmtraveled(Link),androbotaxisneedtohaveabetterperformancethanthat.

Exhibit12:Commonlyusedtechtermstomeasurerobotaxi'ssafetylevel

KeymetricsHowtobenchmarkandmeasurethesafetylevel

AccumulatedtestingmileagesAveragetestingspeed

MPD

MPC

Remoteassistant

Basicsafetyfunction

Emergency

Cybersecurity

Thehigherthebetter,withmoreexperiences

Thehigherthebetter,showingcompany'scapabilitestoensuresafetyamidhighspeedMilesperDisengagement,thelowerthebetter

MilesperCollision,thelowerthebetter

Numberofvehiclesperremoteassistantstaffcouldhand