BCG波士顿咨询：2026年全球城市出行标杆研究报告-2026-01-数字化

BCGCITYMOBILITYCOMPASS

TheGlobalChampionsofUrbanMobility

January2026

ByMarkusHagenmaier,SebastianPfaffinger,ArtursSmilkstins,JohannesWahl,JulienBert,NikolausLang,VladislavBoutenko,andAndreyBerdichevskiy

Spendafewminutesatrushhourinmanymajorcities,andyou’llseethestarkrealitiesofmobility:cloggedroads,pollutedair,andpatchy

masstransit.Butwhilemostcitiesaresuffering,someareovercomingthesechallenges.Inthosecities,residentsenjoybettermobilityand

livehealthierlives,withshortercommutesandcleanerskies.

Toidentifywhichcitiesareperformingwellandwhatlessonstheycanoffer,weconductedacomprehensiveanalysisof

morethan150citiesaroundtheworldandrankedthembytheirurbanmobilityperformance.Wecallthisframework

theBCGCityMobilityCompass.Ourapproachinvolved

assessingmorethan20KPIspercity,supplementedwithanin-depthsurveyofmorethan50cityleaders.Fromthat

analysis,wegroupedcitiesintosixarchetypes,basedon

suchfactorsastheirpopulationsizeanddensity,urban

layout,andmobilitypreferences,todeterminewhichcitiesarebuildingfuture-readymobilitysystems.(Seet

he

appendix

foradetaileddiscussionofourmethodology.)

Followingthatresearch,wedevelopedaglobalbenchmarkdesignedtoserveasabasisforgauginghowcitiesperformonthefactorsthatmattermosttocityleadersand

residentsalike:fast,sustainable,seamless,affordable,andaccessibletransport.Usingthistool,citiescanmakeplanstotransformtheirmobilitysystemsandmovepeoplemoreeffectively—todayandinthefuture.(See“

ANew,On-

DemandMobilityDiagnosticsToolfor150Cities

.”)

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY2

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY3

ANew,On-DemandMobilityDiagnosticsToolfor150Cities

Tobringourextensivedatabasetolife,wehavecreated

BCG’sCityMobilityHealthCheckTool

,adigital

benchmarkingtooldesignedtoenablecityleaderstoidentifystrengthsandshortcomingsoftheircitywithjustoneclick.Thetoolwillultimatelycoverall150citiesinourresearch

study,butthethreethatfollowofferaninitialsample.

Londonhasstrongsystemcapacity,thankstoitsextensiveanddensetrack-basedpublictransitnetwork,offering

convenientaccesstoroughly95%ofLondon’sresidents.

Thecityalsobenefitsfromregulationsincludingcongestionpricing,ultra-lowemissionzones,andarangeofrestrictionsonprivatevehicleaccess.Ontheotherhand,thecitycan

improvebymakingpublictransportmoreaffordable.

Programstoincreasenonfarerevenue,decreaseoperatingexpenses,orbettercross-subsidizewithrevenuefrom

privatetransportpushinitiativescouldallhelpreducepublictransportticketprices.

Copenhagenisagloballeaderinactivemobility,with

extensiveinfrastructuredesignedforsafeandconvenient

walkingandbiking,andwithahighshareofaccessible

greenareasinthecity.Inaddition,morethan90%of

residentsalreadylivewithinaconvenientdistanceofa

publictransportstation.Still,thecitycanfurtherimproveitstrack-basedpublictransport,whichisbelowaveragebutis

currentlybeingaddressedwithanongoingmetroexpansion.

SanFranciscostandsoutasagloballeaderinmobility

innovation,activelypilotingmobility-as-a-serviceplatformsandautonomousvehicles—withmorethan800robotaxis

alreadyoperatingonitsstreets.Amongcar-dependent

cities,SanFranciscohasarelativelylowshareofprivatecartripsatjustabove60%,whereasmanyU.S.peersexceed

90%.Nevertheless,thisfigureremainshighbyinternationalstandards.Thecitycanfurtheradvanceitsmobilitysystembystrengtheningpublictransport—expandingbusroutes

andincreasingstopdensity—andbycontinuingto

discourageprivatecarusethroughmeasuressuchashigherparkingfeesandcongestionpricing,followingtheexampleofcitiessuchasNewYork.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY4

TransportationSystemsPushedtotheBrink

Inoursurvey,95%ofcitieshaveset2035targetstomove

peoplemoreeffectively—outofprivatecarsandinto

sustainablemodes,includingpublictransportorformsof

activemobility(micromobility,bicycles,orwalking).Ambitionlevelsvaryglobally.CitiesinEuropeandAsia-Pacifichave

establishedgoalsofhavingresidentsmakemorethan60%ofalltripsviasustainablemodesby2035;citiesinNorth

AmericaandtheMiddleEasthavesetmoremodesttargetsofaround30%to40%.Yetregardlessoftheirambitionlevel,citiesarecurrently10to15percentagepointsbehindwheretheyshouldbeinordertomeettheir2035targets,andtheyareunlikelytoclosethatgap.(See

Exhibit1

.)And

historically,mostcitieshavebeenabletoshiftonlyaboutthreetofivepointsofmodalshareperdecade.

Inthefuture,achievingmobilitytargetswilllikelybecome

morechallenging,asmosturbanareasfacemounting

pressuresfromtheeffectsofurbanization,anincreased

relianceonprivatelyownedcars,andgrowingsystem

complexity.Technologyalonewillnotprovideasilverbullet,becauseeachinnovationsolvessomeproblemswhile

creatingnewones.Forinstance,althoughelectricvehicles(EVs)cansignificantlyreducepollution,theyalsorequireextensivenewinfrastructure,addingfiscalstrainand

introducingnewplanningchallenges.Navigatingthis

evolvinglandscapesuccessfullycallsfordecisiveactionsfromleaders.

EXHIBIT1

Worldwide,CitiesFaceaGapofAlmost15PercentagePointsBetweenToday’sTransportMixandTheirTargetsfor2035

SUSTAINABLETRANSPORTMODALSHARE,STATUSQUOVERSUSAMBITION(%)

Ambition:~54

40–14

Global

Ambition:~70

66–4

Europe

Ambition:~34

14–20

NorthAmerica

Ambition:~61

54–7

Asia-Pacific

Ambition:~39

19–20

MiddleEast

StatusquoGaptoambition

Source:BCGanalysis.

Note:Sustainabletransportmodesincludemicromobility,walking,cycling,andpublictransport;theydonotincludepowertrainsonprivatecars.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY5

SixUrbanMobilityArchetypes

Thereisnouniversalblueprintfortransformingurban

mobility.Inoursurvey,morethan90%ofcityleaders

reportedstrugglingtoidentifythemosteffectivelevers—underscoringthepotentialvalueoftailoredpeer

comparisonsinhelpingthemadvancemobilityoutcomes.

Toidentifycomparablepeers,wegroupedthe150

globalcitiesinouranalysisintosixarchetypes,accountingfordifferencessuchaspopulationdensity,geographic

layout,economicconditions,mobilitymaturity,andinfrastructurebase:

•ProsperousInnovationCenters.Thefirstarchetypeincludescitieswithapopulationoflessthan3

millionandabove-averagepopulationdensity,wheresustainablemodesdominate—withactivetransport,suchaswalkingorcycling,commonlyaccountingformorethan50%oftrips.Thesecitiescombinedenseinfrastructurewithadvanceddigitalintegrationto

createefficient,people-centeredmobilityecosystems.ExamplesincludeUtrechtandCopenhagen.

•TraditionalMiddleweights.Thesecondcategory

comprisescitieswithpopulationsoflessthan3million,

whereprivatecarsremainthedominantmodeof

transport.Becauseoftheirlowerpopulationdensities(inmanycaseslessthan3,000residentspersquarekilometer)andcorrespondinglyreducedsystemcomplexity,these

citiescanstillachievesolidmobilityperformanceoverall.ExamplesincludeNashvilleandTallinn.

•Mass-TransitMegacities.Nextaredenselypopulatedurbanareaswithpopulationsofmorethan3million

(andoftenfarmore).Publictransportisthedominantmode,typicallyaccountingforroughlyhalfofalltrips.Thesecitiesoperatelarge-scalenetworks,oftenrelyingonastrongtrack-basedtransitbackbone.Moreover,

theyincreasinglyapplypolycentricplanningtomanagepeopleflows,demandpeaks,andotherfactors.

ExamplesincludeSingaporeandTokyo.

•MultimodalMetropolises.Citiesinthiscategory

relyonablendofpublictransportandactivemobilityasdominantmodes.Overall,sustainabletransport

typicallyaccountsforthree-fourthsofalltrips.These

cities,typicallywithpopulationsslightlygreaterthan3millionandlessconcentrateddowntownareas,aimfor

seamlessintegrationacrosstransportmodes.BerlinandBarcelonaareleadingexamples.

•PrivateTransportPowerhouses.Thefiftharchetypeincludeshighlycar-dependentcitieswithpopulation

sizesabove3million,where,onaverage,approximately80%to90%oftripsoccurinprivatevehicles.Thisisa

resultofadifferingurbanplanningapproach:Widely

spreadcitieswithextensivesuburbs—particularlyin

theUS—andoftenrathermonocentricurbanlayouts

makecommuteslongandcarsnecessary.Chicagoisanexampleofthisarchetype.

•DevelopingUrbanGiants.Thesearesignificanturbanagglomerationsindevelopingcountries,usuallywith

populationsexceeding10million.Theyarecharacterizedbyhighdensityandrapiddemographicexpansion

thatislikelytocontinue(insomecasesatratesof

40%to60%by2040).Despitethesecomplexities,thescaleandmomentumofcitiesinthiscategoryoffer

significanttransformationpotential.DelhiandDhakaarerepresentativecitiesinthisgroup.

Mobilitysystemperformanceacrossthesegroupsreveals

strikingdisparities.Moreadvancedarchetypessignificantlyoutperformlessmaturepeers,evenwiththedatacontrolledforsize.Forinstance,ProsperousInnovationCenters

experienceroughly50%lesscongestionthanTraditional

Middleweightsofsimilarsize.Private-TransportPowerhousesemitmorethantwiceasmuchCO₂per10-minutecommuteasMass-TransitMegacities.(See

Exhibit2.

)

Overall,ouranalysisshowsastrongcorrelationbetween

cityperformanceandcardependency.Forexample,incitieswithpopulationsabove3million,residentsofthefivecitieswiththelowestcarmodalshareeachspend30to40fewerhoursincongestionperyearandemitabout800gramslessCO₂per10-minutecommutethanthoselivinginthefive

citieswiththehighestcarmodalshare.(See

Exhibit3

.)

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY6

EXHIBIT2

AmongArchetypes,ProsperousInnovationCentersandMass-TransitMegacitiesLeadinMinimizingTrafficCongestionandEmissions

Congestion

TIMELOSTINTRAFFICPERRESIDENTPERYEAR(HOURS)

Emissions

CO2EMITTEDPER10-MINUTECOMMUTE(GRAMS)

150

100

50

1,800

1,500

1,200

900

600

300

0.11101000.1110100

POPULATION(MILLIONS)POPULATION(MILLIONS)

ProsperousInnovationCentersTraditionalMiddleweightsMultimodalMetropolisesMass-TransitMegacities

PrivateTransportPowerhousesDevelopingUrbanGiants>80%ofcitiesineacharchetypeinarea

Sources:ABCofmobilityresearchproject;Numbeo;BCGanalysis.

Note:LogarithmicXaxisappliedtoenhancechartreadability.

EXHIBIT3

TheShareofPrivateCarsinaCityStronglyCorrelateswithTrafficCongestionandCO2Emissions

Congestion

PRIVATECARMODALSHARE(%)

Emissions

PRIVATECARMODALSHARE(%)

100

50

0

100

50

0

02040608010005001,0001,500

TIMELOSTINTRAFFICPERRESIDENTPERYEAR(HOURS)CO2EMITTEDPER10-MINUTECOMMUTE(GRAMS)

Sources:ABCofmobilityresearchproject;Numbeo;BCGanalysis.

Note:Sampleincludesapproximately40citieswithpopulationsexceeding3million,primarilyindevelopedcountries.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY7

GlobalChampions

Clearly,therearedifferencesnotonlybetweenarchetypesbutalsowithineacharchetype,assomecitiesoutperformtheirdirectpeers.Toidentifytheseleaders,weassessedthecitiesinourstudyaccordingtosixquantifiable

dimensions,eachwitharangeofpotentialKPIs:

•OverallSystemOutcomesandEffectiveness(forexample,timelostincongestionperresident,orCO2emissionsfora10-minutetrip)

•PrivateTransportManagement(forexample,parkingfeesasapercentageofincome,oruseofcongestionpricingschemes)

•PublicTransportPerformance(forexample,costofamonthlypublictransportticketasapercentage

ofincome,oraccessibilitytopublictransportasa

percentageofpopulationlivingwithin500metersofabusstoportrack-basedpublictransportstation)

•ActiveMobilityPromotion(forexample,bikelanecoverage,orthecostofsharedbikesorscooters)

•DemandManagement(forexample,polycentricityscore,ortheimplementationofactivedemand

managementinitiatives)1

•FutureReadinessandTechnologyAdoption(for

example,spendingondigitaltoolssuchasdigitaltwins,ortheuseofend-customerplatforms)

Byaggregatingscoresacrosstheseareas,werankedall150citiesinouranalysisonascaleof1to10,leadingtosixglobalmobilitychampions—oneforeacharchetype.(See

Exhibit4

.)

EXHIBIT4

KualaLumpur

Bangalore

Manila

Delhi

Dhaka

Developing

UrbanGiants

Totalscore

System

outcomes

Privatetransportmanagement

Publictransportperformance

Activemobilitypromotion

Demand

management

Tech

adoption

2.92.92.52.42.1

....●

.....

....●

....

....●

....

TheHighest-RankingCitiesinEachArchetype

Utrecht

Helsinki

Vienna

Amsterdam

Copenhagen

Prosperous

InnovationCenters

Stockholm

Mannheim

Wellington

Tallinn

Rotterdam

Traditional

Middleweights

7.26.96.26.25.9

....w

....w

....

....

..w.w

.w.

Singapore

Tokyo

HongKong

Seoul

London

Mass-TransitMegacities

Berlin

Barcelona

Madrid

Nanjing

Beijing

Multimodal

Metropolises

Private

Transport

Powerhouses

SanFrancisco1

NewYork1

AbuDhabi

Dubai

Sydney

8.28.07.97.87.7

....

.ww..

●..

....●

w...●

..●.

8.38.17.77.67.6

....●

....

●..

..w

●....

....

8.17.66.96.56.3

..●.

ww...

..●..

....

●ww..

.....

5.85.65.55.44.9

...

.ww

....

..●w

..w.

..●●

Scoringintervals:>9.59.5to8.5to.7.5to6.5to.5.5to4.5to●3.5to●2.5to≤1.5

>8.5>7.5>6.5>5.5>4.5>3.5>2.5>1.5

Source:BCGanalysis.

Note:Thescaleforallscoresis1to10.“Totalscore”refertototaloverallscoreonthe2025BCGCityMobilityCompass.

1Metropolitanareadata;higherpublictransportshareinthecityIsdowntownarea(e.g.,inNewYork,publictransportshareforManhattanexceeds50%).

1.Polycentricityreferstocitylayoutsthathavemorethanonedowntowncommercialarea.Thesecitiestendtohavelesstrafficcongestion,becausetheydon’trequireresidentstocommutetothesameareaforwork.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY8

AttheforefrontoftheglobalpackisSingapore,thetop

performeramongMass-TransitMegacities.Singapore7s

leadingpositionreflectsacarefullycalibrated

multidimensionalmobilitystrategythataimstoreduce

relianceonprivatecarsthrougharobustpublictransport

network,promotionofalternativetransportmodes,and

schemestocapthepermissiblenumberofregistered

vehicles.Thecity’sElectronicRoadPricingsystemmanagescongestionbyusingelectronicgantriestoautomatically

chargevehiclesforroadusageduringpeakperiods,withfeesvaryingbylocation,time,andtrafficconditions.Morethan80%ofintersectionsinthecityarecontrolledbyAI.

Ontopofthatstrongfoundation,Singaporeisinvestinginareassuchasactivemobility.Initiativesunderwayincludedevelopmentofa1,300-kilometercyclingpathnetwork

(scheduledtobecompleteby2030),constructionofend-of-tripfacilitieswithshowersandchangingspacesforcyclists,andinvestmentofmorethan$700milliontoenhance

pedestrianinfrastructureandsafety.

Othertop-performingcitiesbuildonadifferentfoundationandpurseotherinitiatives.Forexample,Berlinalreadyhasastrongcyclingculture,withover2,000kilometersofbikelanesinstalledacrossthecity.Nowitisworkingto

integratethatinfrastructurephysicallyanddigitallywith

othermodes—forexample,bytransformingpublic

transportstationsintomultimodalhubs,alongwith

introducingmobilesappsthatletcustomersbook,use,andpayfordifferenttypesoftransitinasingleinterface.This

approachmakesBerlinaleaderintheMultimodalMetropolisarchetype.

HowtheCityArchetypesStackUp

Thesixarchetypesserveasaframeworkforcomparing

groupsofcities,pinpointinggroupandindividual

shortcomings,andidentifyingwaystofurtheradvance

theirmobilitysystems.Consider,forexample,thefour

archetypeswithpopulationsexceeding3million—Mass-

TransitMegacities,MultimodalMetropolises,Private

TransportPowerhouses,andDevelopingUrbanGiants.

(See

Exhibit5

.)Acomparisonofrelevantdataforeach

archetyperevealsanumberofcleardifferences.For

instance,PrivateTransportPowerhouseshave70%to75%fewerbusesthanMass-TransitMegacities.AndDevelopingUrbanGiantshave75%to80%lesstrackforrail,metro,

andlight-railtransitthanMass-TransitMegacities.

ParticularlyconcerningaretheshortcomingsofDevelopingUrbanGiants,astheseweaknessesarelikelytoworsen

sharplywithacceleratingurbanization.Oursimulation

projectsthat,intheabsenceofsignificantinvestment,theshareofthepopulationwithconvenientaccesstopublic

transport(within500to1,000metersofabusstopor

track-basedpublictransportstation)willdropbyaround15percentagepointsby2040,causingoverallaccessibilitytofallsignificantlybelow50%.Atthesametime,existing

track-basedpublictransportcapacitywillbecomeanacutebottleneck:aspopulationdensityrises,weexpectrelativesystemcapacitypercapitatodecreasebyanadditional

25%to30%,furtheramplifyingcongestion,emissions,andaccessibilityissuesinmobility.

EXHIBIT5

80

3.2

78

3.1

Mass-TransitMegacities

4%

9%

3%

Developing

53

3.6

31

0.7

PrivateTransportPowerhousesandDevelopingUrbanGiantsFallShortinMakingMassTransportWidelyAvailable

Accessibility

Affordability

Busavailability

Railavailability

POPULATIONWITH

CONVENIENTACCESSTOPUBLICTRANSPORT(%)1

MONTHLYNETINCOME

SPENTONMONTHLYPUBLICTRANSPORTTICKET(%)

NUMBEROFBUSESPER100,000RESIDENTS

RAIL,METRO,ANDLIGHTRAIL

TRACKFORPUBLICTRANSPORT(KMPER100,000RESIDENTS)

Multimodal

Metropolises

78

2.4

32

3.0

PrivateTransportPowerhouses

57

–3

2.0

+0.

4pp–7

21

1.8

–7

UrbanGiants

Sources:UnitedNations;Numbeo;citydata;BCGanalysis.

Note:pp=percentagepoints.

1Within500metersofabusstationand/orwithin1,000metersofatrack-basedpublictransportstation.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY9

Citieswithfewerthan3millioninhabitantsfacedifferent

challenges.Intheseplaces,activemobility—cycling,

walking,andsharedmicromobility—consistently

outperformsbothprivateandpublictransport–dominatedsystemsacrossnearlyallperformancedimensions.For

example,citieswhereactivemobilityisthedominant

modeexperience25%to30%lowerlevelsofcongestion

andupto25%lowerlevelsofCO2emissionthanpeersthatrelyprimarilyonpublictransport—letalonecitieswhere

mostpeoplerelyonprivatelyownedcars.

ComparingKPIshighlightssomepotentialprioritiesfor

TraditionalMiddleweights.Inthesecities,bikeownershipratesamongadultsaremorethan40%lowerthanin

ProsperousInnovationCenters,roughlybike-lane

infrastructureislessthanone-thirdaslarge,andshared-mobilityavailabilityis55%less.(See

Exhibit6

.)Althoughthetwogroupsshowsimilarlevelsofgreen-space

availability,thedifferencesbetweenthesearchetypes

translateintomeaningfuldifferencesintrafficcongestionandemissionslevels.

EXHIBIT6

InComparisontoProsperousInnovationCenters,Traditional

MiddleweightsLackaBikeCultureandSharedMobilitySystems

Bikeculture

ADULTSWHOOWN

APRIVATEBIKEAND

REGULARLYUSEIT(%)

Infrastructure

AVAILABLEBIKELANES

(KMPER1,000RESIDENTS)

Sharedmobility

SHAREDMICROMOBILITYVEHICLESPER1,000

RESIDENTS

Walkingpromotion

ACCESSIBLEGREENAREAINCITY(%)

Prosperous

InnovationCenters

59

43%

0.43

36%

1.59

55%

0%

23

Traditional

Middleweights

–––

330.280.7123

Sources:UnitedNations;Numbeo;citydata;BCGanalysis.

1Within500metersofthenearestbusstationand/orwithin1,000metersofthenearesttrack-basedpublictransportstation.

FiveStructuralMeasurestoImproveUrbanMobility

Besidessuggestingmode-specificinterventions,thecity

leadersinoursurveyidentifiedbroaderstructural

measuresthatcanleadtogreaterprogress.These

initiatives,whichbuildontrendsinoursurveydataandoninsightssharedbycityleaders,spurchangebyincreasingpublicbuy-in,improvingefficiency,andmakingcitiesmorefuture-ready.

Enlistresidentsinthetransformation.Morethanhalfofcityleaderscitepublicresistanceasamajorbarrierto

mobilitytransformation,yetfewerthan50%involve

residentsintheprocessbeyondparticipatinginbasiconlinesurveys.Inlightofgenerationalshiftsinmobility

preferences,alongwithchangingtechnologies,citiescan

enlistresidentstoactivelyco-createmobilitytransformationthroughouttheplanningandexecutionphases.Madrid’s

“MadridCentral”low-emissionzoneisastrongexample.Whiletheprojectwasindevelopment,citizenscouldoffer

inputthroughanopen-government,onlineparticipation

tool.Thatengagementhelpedthecityovercomeinitial

resistance—andtheoverallprojectreducedcongestioninthezonebymorethan15%,improvedairquality,and

fueledstrongerlocalbusinessactivity.

Establishecosystemsofserviceproviders.Inmany

cities,thenumberofmobilityplayersapproaches100,

includingAVfleets,micromobilityservices,andsensor

providers.Thatoftenleadstoincreasedcomplexity,limitedinteroperability,andsiloeddata.Toimprove,citiescanserveasactiveorchestrators,settingdata-sharingstandards,

enforcinginteroperability,andenablingdigitalcoordination.Hamburgisagoodexample.Thecitycreatedoneof

Europe’smostadvancedmobilitydatalakesbyconnectingpublicandprivatedatastreamstopowerreal-timetrafficmanagementpilotsandpavethewayforbroader

coordinationacrossHamburg’sentiremobilitysystem.

BOSTONCONSULTINGGROUPBCGCITYMOBILITYCOMPASS:THEGLOBALCHAMPIONSOFURBANMOBILITY10

Makesmarterinfrastructureinvestments.Fiscal

constraintsandgrowingdemandformobilitycallfor

smarterinfrastructureinvestments,especiallyforPrivate

TransportPowerhousesandDevelopingUrbanGiants.Forinstance,oursimulationsforDelhiindicatethat,asaresultofpopulationgrowth,thecitywillneedanestimated$7

billionto$10billionby2040justtomaintaincurrentpublictransitservicelevels.Yetthecityalreadyfacessignificantbudgetconstraints—arealitysharedbymorethan75%ofsurveyedcities.Innovativefinancingmechanismsinclude

public-privatepartnerships,adoptionofmodulardesignstocutcapexbyupto20%,anduseofdigitaltoolstomake

planningprocessesmoreefficient.Inonecase,CityFlowbyBCGX,anAI-poweredsimulationandanalytics

platform,helpedaEuropeancapitalcutitsplannedmetrocostsby$1.4billionwithoutsacrificingperformance.

ScaleAIacrossthesystem.AIalreadydelivers

measurableimpactacrossleadingurbanmobilitysystems,

helpingtoreduceemissions,speedtrafficflows,andimprovethepassengerexperienceonpublictransit—allwithout

requiringcostlyinfrastructureoverhauls.LeadingcitiesareembracingAInotjustforoperations,butalsoasastrategiclever.Singapore,forinstance,hasembeddedAIacrossits

entiretransportecosystem,fromdynamicfleetdispatchandpredictivemaintenancetoreal-timedemandforecasting.

Rethinkurbanplanning.Inadditiontotransport

measures,urbanplanning—andspecificallyhuman-

centricdesign—canreducemobilitydemandandmake

citiesmoreresilient.Inthisregard,conceptssuchasthe

15-minutecityshowstrongpromise.Anurbanplanning

approachpilotedinBarcelona,Paris,andTokyo,the

15-minutecitygivesresidentsaccesstoessentialservicessuchaswork,shopping,schools,andhealthcarewithina15-minutewalkorbikeridefromhome.Whenrealized,

thisapproach