A Framework for Projecting the (VMT) Level Strategies in ...

AFrameworkforProjectingthePotentialStatewideVehicleMilesTraveled(VMT)ReductionfromState-LevelStrategiesinCalifornia

March2017 AWhitePaperfromtheNationalCenterforSustainableTransportation

MarlonBoarnet,UniversityofSouthernCalifornia

SusanHandy,UniversityofCalifornia,Davis

AbouttheNationalCenterforSustainableTransportationTheNationalCenterforSustainableTransportationisaconsortiumofleadinguniversitiescommittedtoadvancinganenvironmentallysustainabletransportationsystemthroughcutting-edgeresearch,directpolicyengagement,andeducationofourfutureleaders.Consortiummembersinclude:UniversityofCalifornia,Davis;UniversityofCalifornia,Riverside;UniversityofSouthernCalifornia;CaliforniaStateUniversity,LongBeach;GeorgiaInstituteofTechnology;andUniversityofVermont.Moreinformationcanbefoundat:ncst.ucdavis.edu.

U.S.DepartmentofTransportation(USDOT)DisclaimerThecontentsofthisreportreflecttheviewsoftheauthors,whoareresponsibleforthefactsandtheaccuracyoftheinformationpresentedherein.ThisdocumentisdisseminatedunderthesponsorshipoftheUnitedStatesDepartmentofTransportation’sUniversityTransportationCentersprogram,intheinterestofinformationexchange.TheU.S.Governmentassumesnoliabilityforthecontentsorusethereof.

AcknowledgmentsThispaperwaspreparedforandfundedbytheStrategicGrowthCouncil(SGC).TheauthorswouldliketothanktheSGCfortheirsupportofuniversity-basedresearchintransportation,andespeciallyforthefundingprovidedinsupportofthisproject.

AFrameworkforProjectingthePotentialStatewideVehicleMilesTraveled(VMT)ReductionfromState-LevelStrategiesin

CaliforniaANationalCenterforSustainableTransportationWhitePaper

March2017

MarlonBoarnet,SolPriceSchoolofPublicPolicy,UniversityofSouthernCalifornia

SusanHandy,InstituteofTransportationStudies,UniversityofCalifornia,Davis

[pageleftintentionallyblank]

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TABLEOFCONTENTSIntroduction...........................................................................................................................1

1.Pricing.................................................................................................................................4

2.InfillDevelopment............................................................................................................14

3.TransportationInvestments..............................................................................................23

3.1BicycleandPedestrianInfrastructure.........................................................................23

3.2TransitInvestments....................................................................................................27

3.3HighwayCapacity.......................................................................................................31

4.TransportationDemandManagementPrograms..............................................................35

4.1Employer-BasedTripReductionPrograms..................................................................35

4.2TelecommutingPrograms...........................................................................................37

Conclusions..........................................................................................................................40

References............................................................................................................................42

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AFrameworkforProjectingthePotentialStatewideVehicleMilesTraveled(VMT)ReductionfromState-LevelStrategiesinCaliforniaEXECUTIVESUMMARY

TheCaliforniaGlobalWarmingSolutionsActof2006(AssemblyBill32)createdacomprehensive,multi-yearprogramtoreducegreenhousegas(GHG)emissionsinthestateto80%below1990levelsby2050.WiththerecentpassageofSenateBill32,theStateofCaliforniahasadoptedanadditionaltargetofreducinggreenhousegasemissionsto40%below1990levelsby2030.Tomeetthesegoals,analysisshowsthatCaliforniawillneedtoachieveanadditional7.5percentreductioninlight-dutyvehiclemilesoftravel(VMT)by2035,andanadditional15percentreductioninlight-dutyVMTby2050.TheCaliforniaAirResourcesBoard(ARB)isthusconsideringawiderangeofstrategiesforthe2016ScopingPlanUpdatethatfocusonreducingdemandfordriving.Thesestrategiesfallintofourgeneralcategories:Pricing,InfillDevelopment,TransportationInvestments,andTravelDemandManagementPrograms.TheStatehastheabilitytodirectlyimplementsomeofthesestrategiesthroughstatepolicy;forotherstrategies,theStatecanadoptpoliciesthatencourageorrequiretheimplementationofthestrategyonthepartofregionalagencies,localgovernments,and/ortheprivatesector.Inthispaper,weconsidertheevidenceavailableandassumptionsneededforprojectingstatewideVMTreductionsforeachcategoryofstrategies.Ourgoalistoprovideaframeworkforprojectingthemagnitudeofreductionsthatthestatemightexpectforthedifferentstrategies.ThisframeworkhelpstoilluminatethesequenceofeventsthatwouldproduceVMTreductionsandhighlightsimportantgapsinknowledgethatincreasetheuncertaintyoftheprojections.Despiteuncertainties,theevidencejustifiesstateactiononthesestrategies:theavailableevidenceshowsthatthestrategiesconsideredinthispaperarelikelytoreduceVMTifpromotedbystatepolicy.Wedonotinthispaperexaminethepotentialco-benefitsofVMT-reductionstrategies,includinghealth,equity,andotherbenefits,buttheevidenceofthesebenefitsisalsostrongandfurtherjustifiesstateaction.

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StrategyCategory

StatePolicytoVMTLink

EffectonIndividualVMT

PotentialforStatewideImplementationandAdoption–StrategyExtent

Pricing

Mostdirect StrongeffectSolidevidence

Canbeappliedstate-wide(fueltaxes,VMTfees)andintargetedareas(linkpricing,cordonpricing,parkingpricing).Mosteffectivewhereindividualshavegoodalternativestodriving.Strategieshaveequityimplications.Generatesrevenuesthatcanbeinvestedintransportationsystem.

InfillDevelopment

Directandindirect

ModerateeffectSolidevidence

Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingininfillareas.Maydependonchangesinlocallandusepolicy.Mayrequirefinancialincentives.LandusechangesandVMTeffectsaccrueoverthelongterm.

TransportationInvestments

Bike/Ped Directandindirect

SmalleffectModerateevidence

Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingwhereinvestmentsaremade.Maydependonchangesinlocalinvestments.Mayrequirefinancialincentives.Mayrequirepackageofstrategies.Manyco-benefits.

Transit Directandindirect


Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingwhereinvestmentsaremade.Maydependonchangesintransitagencyaction.Mayrequirefinancialincentives.Mayrequirepackageofstrategies.Manyco-benefits.

Highways Direct

StronginducedVMTeffectSolidevidence

NewcapacitythatreducestraveltimesleadstoVMTgrowth.Effectisgreatestincongestedareas.OperationalimprovementsthatreducetraveltimescanalsoinduceVMT.

TransportationDemandManagement

Moreindirect ModerateeffectSolidevidence

Mostapplicableinmetroareas.Generallyimplementedbylargeemployersinresponsetostateorlocalrequirementsorfinancialincentives.Someapplicationsappropriateforruralareas.

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IntroductionTheCaliforniaGlobalWarmingSolutionsActof2006(AssemblyBill32)createdacomprehensive,multi-yearprogramtoreducegreenhousegas(GHG)emissionsinthestateto80%below1990levelsby2050.WiththerecentpassageofSenateBill32,theStateofCaliforniahasadoptedanadditionaltargetofreducinggreenhousegasemissionsto40%below1990levelsby2030.TheAB32ScopingPlan,firstadoptedin2008,outlineshowthestatewillmeetthesetargets.In2015,GovernorBrowndirectedtheCaliforniaAirResourcesBoard(ARB)toupdatetheScopingPlan.ThetransportationsectionsofpreviousScopingPlanswereprimarilyfocusedoncleanerfuelsandcleanervehicles;VMTreductionstrategieswerelimitedtocontinuingimplementationofSB375.Withthe2016ScopingPlanUpdate,theCaliforniaAirResourcesBoard(ARB)isconsideringawiderrangeofstrategiesthatfocusonreducingdemandfordriving.ARBprojectsthatvehiclemilesoftravel(VMT)willgrow11percentfromtodayto2030.ArecentvisioningscenarioanalysisdonebyARBfortheMobileSourceStrategy,whichwillbeincorporatedintotheupdatedScopingPlan,concludedthatinadditiontoexistinginitiativessuchascontinuedimplementationofSB375andimprovementsinvehicleandfueltechnology,Californiawillneedtoachieveanadditional7.5percentreductioninlight-dutyVMTby2035,andanadditional15percentreductioninlight-dutyVMTby2050,inordertomeettheState’soverallGHGgoals.1State-levelpolicies,priorities,andinvestmentswillhaveaprofoundeffectontrendsinVMTandarecriticaltoshiftingthestatefromtheprojectedincreasesinVMTtotheneededreductionsinVMT.ThereisextensiveevidenceonstrategiesthatcanreduceVMT,asdocumentedinaseriesofresearchbriefsweproducedforARB.2InresponsetoSB375,theStatehasalreadytakenactiontoimplementsomeofthestrategiesthatresearchshowsarelikelytoreduceVMT.State-fundedgrantprograms,forexample,providefundingandfinancingforinfilldevelopment,transit,bicyclefacilities,andotherchangestothebuiltenvironmentthatwillenableCalifornianstoreducetheirdriving.Atthesametime,itisimportanttorecognizethatmanylong-standingstatepoliciesarelikelytocontributetoincreasedVMTtrendseventhoughthiswasnottheirprimaryobjective.Mostnotably,decadesofexpansionsofthestatehighwaysystem,declinesintheinflation-adjustedstategastax,andfinancialandpolicybarrierstoinfilldevelopmentandhousingproductionhavecontributedtoanupwardVMTtrend.3Statepoliciesoftenworkagainsteachotherininfluencinghowmuchthestate’sresidentsdrive.1MobileSourceStrategy,May2016.Availableat:http://www.arb.ca.gov/DraftPlanning/sip/2016sip/2016mobsrc.pdf2SenateBill375-ResearchonImpactsofTransportationandLandUse-RelatedPolicies.Availableat:https://arb.ca.gov/cc/sb375/policies/policies.htm3ForasummaryoftheevidenceonhowhighwaycapacityincreasesleadtomoveVMT,seetheARBpolicybriefonhighwaycapacityandinducedtravel,athttps://www.arb.ca.gov/cc/sb375/policies/hwycapacity/highway_capacity_brief.pdf.https://www.arb.ca.gov/cc/sb375/policies/hwycapacity/highway_capacity_brief.pdf.

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ThestrategiesforreducingdrivingthattheStateisconsideringfortheScopingPlanUpdatefallintofourgeneralcategories:Pricing,InfillDevelopment,TransportationInvestments,andTravelDemandManagementPrograms.TheStatehastheabilitytodirectlyimplementsomeofthesestrategies,particularlypricingandsomeinfrastructurestrategies,throughstatepolicyanddirectinvestment.Forotherstrategies,theStatecanadoptpoliciesthatencourageorrequiretheimplementationofthestrategyonthepartofregionalagencies,localgovernments,and/ortheprivatesector.Infilldevelopment,forexample,dependslargelyonlocallandusepolicies.Forsomestrategies,suchasbicycleinfrastructure,statepolicycanbothdirectlyandindirectlyinfluenceitsimplementation.Projectingthestate-wideimpactofstatepolicyonVMTthusdependsontwocomponents:the“strategyeffect,”theeffectofthestrategy,whenimplemented,onthebehaviorofCaliforniansandtheamountthattheydrive;andthe“strategyextent,”theextentoftheimplementationofthestrategyacrossthestateinresponsetostatepolicyandotherforces.Theevidencebaseonstrategyeffectisstrongformostofthestrategiesunderconsideration:wecanbeconfidentthat,ifimplemented,thesestrategieswillproduceareductioninVMT,evenifthemagnitudeofthatreductionisuncertain.Incontrast,theevidenceonhowtoincreasethestrategyextentisoftenmorelimited.Forexample,theinfluenceofstatesubsidiesoraffordablehousingpolicyontheactionsthatlocalgovernmentstakewithregardtoprovidingmoreinfilldevelopmentissometimesdebated,suggestinganeedformoreresearchonactionsthestatecouldtaketofostermoreinfilldevelopment.Theexistingevidencebase,however,clearlyshowsthatincreasedinfilldevelopmentleadstoreducedVMT.Forinfilldevelopment,thequestionisnotwhetherinfilldevelopmentwouldleadtoreduceddriving–itwill–butratherwhichstatepolicieswouldleadtomoreinfilland,ifthosepoliciesareimplemented,howmuchwouldVMTbereduced.Thisisonlyoneexample;wediscussthedifferencebetweenstrategyeffectandstrategyextentforallfourcategoriesofpoliciesthatarecoveredinthisdocument.Inthispaper,weconsiderthe

StrategyEffectandStrategyExtentStrategyEffect:Thestrategyeffectishowastrategy(orpolicy)wouldchangeVMT.Forexample,ifthefueltaxinthestatewereincreasedbytenpercent,howwouldonedriver’sVMTchange?StrategyExtent:Strategyextentishowmanydrivers(orpersons)canorwouldbeaffectedbyastrategy.Forexample,iftheStateoffersincentivesforinfilldevelopment,howmanymoreinfillunitswillbebuilt,andhencehowmanypersonsareaffectedbythestrategy?Wecansimplifybyimaginingthattheoverallpolicyimpactisthestrategyeffectmultipliedbythestrategyextent.

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evidenceavailableandassumptionsneededforprojectingstatewideVMT4reductionsforeachcategoryofstrategies.Ourgoalistoprovideaframeworkforatleastroughlyprojectingthemagnitudeofreductionsthatthestatemightexpectforthedifferentstrategies.Theprojectionmethodsdifferforeachstrategydependingonits“causalchain”–thesequenceofeventstriggeredbystatepolicythatultimatelyproducereductionsinVMT,includingbothstrategyextent(thecausalchainfromstatepolicytostrategyimplementation)andstrategyeffect(thecausalchainfromstrategyimplementationtoVMTreduction).Theforminwhicheachstrategyeffectisreportedintheliteraturealsodeterminestheprojectionmethod;indiscussingstrategyeffectwerelyonourreviewsoftheevidencebaseasreportedintheARBResearchBriefs,mentionedabove.Wealsooutlinethecriticalgapsinknowledge,data,ormethodsthatmustbefilledbeforemorerobustprojectionsarepossible.Californiahasstakedacutting-edgepositionwithitsGHGreductionframework,andthatgivesthestateanopportunitytopushourknowledgebaseforward.ByhighlightingknowledgegapswearenotingareaswhereCaliforniacancontinueandextenditstraditionofleadershipinenvironmentalpolicyandenvironmentalscience.Wedonotinthispaperexaminethepotentialco-benefitsofVMT-reductionstrategies,thoughtheyarepotentiallysubstantial.ReducingVMTnotonlyreducesGHGemissions,italsoreducesemissionsofpollutantsthatharmhumanhealthaswellasagriculturalproductivityandnaturalhabitats.Infilldevelopmentcoupledwithinvestmentsintransitservicesandbicycleandpedestrianinfrastructureexpandstransportationoptions,reducingtheneedforowningaprivatevehicleandthefinancialburdenthatcomeswithitforlower-incomehouseholds.EvidenceofthebenefitsofVMT-reductionstrategiesforhumanhealth,socialequity,theenvironment,andtheeconomyisstrong,anditfurtherjustifiesstateactiontopromotethesestrategies.

4Formostofthestrategiesweexaminehere,theavailableresearchexaminestheeffectofthestrategyonVMTorotheraspectsoftravelbehaviorratherthanGHGemissions.WhileVMTreductionstranslaterelativelydirectlyintoGHGemissionsreductions,otherfactorsmaycomeintoplay.If,inadditiontoVMTreductions,thestrategyalsoleadstochangesindrivingspeeds(notjustaveragesbutdistributionsofspeedsoverthecourseoftrips)orchangesinthetypesofvehiclesCalifornian’sdrive,thentheconversiontoGHGemissionsislessstraightforward.Infilldevelopment,forexample,mightreducedrivingdistancesbutalsoencouragesmallervehiclesandproducemorecongestionandthuslowerspeeds.Forthemostpart,theliteratureprovideslittlebasisfordevelopingmorenuancedconversionsofVMTtoGHGemissionsforthesestrategies.

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1.PricingPricingisaparticularlypromisingpolicytooltoreduceVMTandassociatedGHGemissions,fortworeasons.First,theeffectsizefrompricinginterventionstoVMTislargerthantheeffectsizeforotherpolicyorplanningtools.Second,pricingcanbeappliedtoabroadbase,andstateactioncanbeparticularlyeffectivehere.Inotherwords,pricingcanachieveabroadstrategyextentquickly.Recallthattheeffectofapolicyistheeffectsize(e.g.theamountthatadriver’sVMTwouldbereducedifthepolicywereappliedtothatdriver)multipliedbythenumberofdriversexposedtothepolicy.Pricingrevenuescanbeusedtoexpandnon-automobiletraveloptions,makingthepricingpoliciesthemselvesmoreeffectiveatVMTreduction.Similarly,pricingpoliciescanbeusedtoaddressequityconcerns,forexamplebyexpandingbusservice,providingpedestrianorbicycleimprovements,ormitigatingenvironmentalimpactsinlow-incomeneighborhoods.Pricingalsohastheadvantageofraisingrevenuetofundneededtransportationprojects.Statewide,ourcitiesandcountieshavetransportationneedsthatoutstripavailablerevenue.Forexample,theStateTransportationPlanidentifiesa$294billionfundinggap–fundingonly45percentoftheState’stransportationsystemneedsthrough2020.5Pricingandvehiclefeescanfundinfrastructureimprovements,managecongestion,andmaintainroadwayswhilealsoimprovingairqualityandbettermanageourtransportationinfrastructure.Thereareseveraldifferentwaystousepricing.Wedefinethosebrieflyhere:LinkTolls:Chargeatolltodriveonaportionofahighway.Thetolltypicallyvarieswithcongestionlevels.Examplesincludethehigh-occupancytolllanesonSanDiego’sSR-125andLosAngelesI-110,andcongestionpricedtolllanesonSR-91inOrangeCounty.IntheSanDiegoandLosAngelesexamples,thetolladjustsbasedontrafficlevels(moretrafficimpliesahigher

5Seehttp://www.dot.ca.gov/hq/tpp/californiatransportationplan2040/Final%20CTP/CTP2040-Appendices-WebReady.pdf.

Statepolicy Local

policy

Pricing VMT

Strategyextent Strategyeffect

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toll)whilethetollontheSR-91inOrangeCountyisbasedontimeofday(peakperiodshavehighertolls.)6CordonTolls:Chargeatolltocrossintoadowntowncentralbusinessdistrictorothercongestedarea.TherearecurrentlynoexamplesofcordontollpricingintheU.S.WellknowninternationalexamplesofcordontollsincludeLondon’stollring,aroundthecenterofthecity,andthecordontollinSingapore.VMTfees:Driversarechargedafeebasedonmilesdriven(VMT).OregonlaunchedaVMTfeepilotexperimentwhichenrolleddriversinpilotprogramstotestreplacingthestate’sfueltaxwithaVMTfee.Californialaunchedasimilarpilotin2016.7In2008-2010,theUniversityofIowaledanationalpilotprogramthatexaminedVMTfeesinlieuoffueltaxesintwelvelocations.NoVMTfeehasmovedbeyondthepilot/studyphaseintheU.S.Fueltaxes:FueltaxesareappliedbyeverystateintheU.S.andthefederalgovernment.At-the-pumpfueltaxesareassessedonacentspergallonbasis,andsoarenotadjustedforinflation.Arelativelyminorexceptioniscaseswheresalestaxesarealsoappliedtoper-gallonfueltaxes.Increasedfuelefficiencyimpliesthatpersonscandrivemorepergallon,hencefueltaxesraiselessrevenuepermiledrivenasvehiclefuelefficiencyincreases.Parkingprices:Therearemanyparkingpricingschemes,fromfixed-pricedstreetmeterstoworkplaceparkingcash-outschemesthatofferemployeescashinlieuofsubsidizedfreeparkingtopoliciesthatchargeemployeesornon-worktravelersforparkingtoreal-timemeteredparkingpricesthatadjusttoequilibratesupplyanddemand.AllhavebeenappliedinCalifornia.Todate,parkingpricingpolicyinthestatehasbeenexclusivelythedomainoflocalgovernments,thoughAB744reducedparkingspacerequirementsstatewideforaffordableseniorhousing.8Pay-as-you-goinsurance:Thispolicyproposestochangevehicleinsurancefromamonthlyorsix-monthfee,whichistypicallyassessedindependentofdriving,toaper-milefee.Freightlowemissionzones:Thisproposalwouldestablishlowemissionzones,usuallynearresidentialareas,wheretruckswouldeitherhavetouselowemissiontechnologyorpayafee.Theprospectofcombiningpricingwithcarefullanduseconsiderationsisapromisingwayto

6SomehighwaysinCaliforniausetollsthatdonotvarywithtimeofdayorcongestion.ThetollroadsinsouthOrangeCounty(portionsofSR73,133,241,and261)haveflatratepricing.Thetollsonthoselaneswerenotdesignedtomanagecongestion,butaresolelyafinancingtool.Thereislittleevidenceonwhetherandhowflat-ratetollsreducedriving,althoughonecaninferthatthepriceeffectmaybesimilar.Wefocusourattentiononcongestiontolls,whichbringtheaddedbenefitofcongestionmanagementandforwhichtheevidencebaseislarger.7Seehttps://www.californiaroadchargepilot.comand,forarelateddiscussion,MarlonG.Boarnet,“PolicyApproachesforCalifornia’sTransportationFuture,”CaliforniaCentral,2016,availableathttp://californiacentral.usc.edu/wp-content/uploads/2016/06/CA-Central-transportation-6-13-16.pdf.8Seehttps://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201520160AB744.

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addressenvironmentaljusticeimplicationsoftruckemissionsthatdisproportionatelyaffectlow-incomecommunities.Yetthispolicy,becauseitisahybridofpricing,emissiontechnologyrequirements,andlandusepatternsthatwouldinteractwiththetransportationnetwork,islessapurepricingstrategy.Also,theresponseoftrucktraffictopricingdependsonthenatureofdrivercontractualrelationshipswithtruckingcompaniesandhenceisbestinformedbyevidencethatisspecifictopricingandtrucking.Forthosereasons,webelievetheexistingpricingevidence,largelyfrompassengertravelandmostlyfrompurepricingexperimentsorpolicies,cannotbeaseasilyappliedtolowemissionzones.Wenote,though,thatthesamebasictheoryappliestotrucksastopassengers–higherpriceswoulddiscouragedrivingactivityinthelocationsandatthetimesforwhichthepriceishigher–anditisonlythemagnitudeanddetailedeffectofalowemissionzonethatwedonotdiscussfurtherhere.StrategyEffect:ImpactsofPricingonIndividualorHouseholdVMTTheavailableevidenceoneffectsizescanbegroupedintofourcategories:(1)linkandcordontolls,(2)VMTfees,(3)Fuelprices(andhencefueltaxes),and(4)parkingpricing.Weknowofnoavailableevidenceontheeffectsizeofpay-as-you-goinsurance,andforthereasonsmentionedabovewebelievethatfreightlowemissionszones,whilepromising,shouldbeaseparatetopicofstudy.Importantly,boththeoryandevidencesuggestthattheeffectsizesaresimilaracrossthedifferentpricingtoolsforwhichdataareavailable.Apriceisaprice,and,asanapproximation,driversshouldnotcareiftheypayadollartobuygas,driveonthehighway,orpark;theeffectofthepriceondrivingmightbequitesimilarforthosedifferentpolicies.Asitturnsout,theempiricalrangeofpricingeffectsizesacrossdifferentpoliciesaresimilar,andthatallowssomeconfidencetointerpretfromtheexistingevidencebasetopolicies,suchaspay-as-you-goinsurance,forwhichthereisnotcurrentlyaneffectsizeevidencebase.Itisreasonabletoassume,forexample,thatpay-as-you-goinsurancewouldlooktodriverslikeaVMTfee,andhencethattheVMTfeeevidencewouldapply.Asmentionedabove,freightlowemissionzones,becausetheyareahybridofpricing,emissiontechnologyrequirements,andlanduse,wouldrequireadditionalevidencenotdiscussedhere.TherangeofeffectsizesinTable1islargeinsomecases(e.g.thelong-runelasticityofVMTwithrespecttofuelprice.)Wenotethataconservativeestimateofanelasticitywouldbe-0.1,whichistowardthelowendoftherangeforlinkandcordontollsandforfuelprices.Similarly,resultsfromtheOregonVMTfeepilotprogramsuggestthatreplacingafueltaxwithaVMTfeeinarevenue-neutralwaycouldreduceVMTby11to14percent.Overall,wesuggestthatanelasticityofVMTwithrespecttopricingof-0.1isaconservativeestimatethatmightbeusedtoapplyacrossdifferentpricingprograms.Mostoftheevidenceonparkingpricingrelatespricetothedemandforparkingspaces,andinferringaVMTelasticityforparkingpricingcanbemoredifficult.However,arecentprograminSanFrancisco,SFpark,adjustson-streetparkingpricesbasedonoccupancy–raisingthe

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meteredpriceforanon-streetparkingspacewhenmorethan80percentofthespacesonablockareoccupied(Millard-Ball,etal.,2014).RecentstudiesofSFparksuggestthattheprogramandit’sdemand-basedpricingmayreducecruisingforparkingby50percent(Millard-Ball,etal.,2014).Table1:EffectSizesforPricingPoliciesPricingPolicy Elasticity(unlessotherwise

noted)Source

LinkandCordonTolls -0.1to-0.45 ARBpolicybriefonroaduserpricing

VMTfees -11%to-14.6%reductionfromshiftinggastaxtoVMTfee

ARBbriefonroaduserpricing,fromOregonVMTfeeexperiment

Fuelprices -0.026to-0.1(short-run)-0.131to-0.762(long-run)

ARBbriefongasprice

Parkingpricing -0.3fordemandforparkingspaces

ARBparkingpricingandparkingmanagementbrief

Source:ARBpolicybriefs,athttps://arb.ca.gov/cc/sb375/policies/policies.htmStrategyExtent:ImpactofStatePolicyonPricingPricingcanbeimplementedinwaysthatachievebroadstrategyextent.VMTfeesandfuelpricescanaffecteverydriverinthestate.Again,thispaperprovidesaframeworkforatleastroughlyprojectingthemagnitudeofreductionsthatthestatemightexpectforthedifferentstrategies.TherearefewotherStateactionsthatcouldsimilarlyachieveuniversalcoveragewithoutcollaborationorleadershipfromabroadrangeofmunicipalgovernments.Linkandcordontollshavetypicallybeenthepurviewoflocalgovernments,andbecausesuchcongestionpricingisapplicableincongestedlocations,linkandcordontollswouldlikelycontinuetobealocalgovernmentactivity.ButCaltransistheowneroperatorofthestatehighwaysystem,andsotheStatehasmanyopportunitiestoencouragelinkpricing,inparticular,onstatehighwayroutes.TheStatecould,forexample,offersubsidiesorincorporatepricingmoreexplicitlyintotheSB375SustainableCommunitiesStrategy(SCS)process.Similarly,theStatecouldworkcloselywithlocalgovernmentsandcountytransportationagenciestoencourageinnovativeprogramsthatusepricingwhilealsoaddressingtheequityquestionsthatareraisedbyroadorVMTpricing.Otherefforts,suchaspay-as-you-goinsurance,couldbeimplementedthroughStateaction.Overall,Stateactioninpricingcanhaveabroadextentandcantakeeffectquickly,asopposedtolandusepolicieswhichwouldhaveasizeableeffectbutoveralongerperiodoftimeasthebuiltenvironmentismodified.ThestepstouseinquantifyingtheimpactofState-levelpricingstrategiesonVMTareshowninTable2below.Table2hasfourpanels,forfueltaxes,VMTfees,linkorcordontolls,andpay-as-you-goinsurance.Parkingpricingisnotshown,becausethelinkfromthosepoliciestoVMThasbeenlessstudied,althoughthenascentevidencefromSFParkispromisingandsuggeststhat

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pricedparkingcansubstantiallyreducetheamountthatdrivers“cruise”tofindparkingspaces(Millard-Ball,Weinberger,andHampshire,2014).Notethatthedataonthefuelpricesgivesdirectestimatesoftheeffectofchangesinfuelprices(from,e.g.,taxchanges)onVMT;relativelyfewassumptionsareneededcomparedtootherpoliciesthatwediscussedinthispaper.ThedataonVMTfeessimilarlyrequirefewassumptions,althoughthestatewouldrequireadvancesinmodelingthelocationoftrafficacrossthestateandintoandfromneighboringstatesforacompleteanalysis.WhiletheVMTfeedataarefrompilotprograms,thoseprogramsandthecurrentpilotinCaliforniaprovideanopportunitytogetgoodevidenceontheeffectofVMTfeesondriving.Tollsrequireanassumptionabouttheamountofdrivingthatwouldbedivertedtoroutesortimesofdaythatarenottolled,andtheevidenceonthatismorelimited.Leape(2006)estimatesthataquarterofthetrafficreductionwithintheLondoncordontollringwasdivertedtootherroutes.Pay-as-you-goinsurancerequiresanassumptionthattheelasticitiesfromVMTfeeorfueltaxstudiesapply,butsuchasassumptionistheoreticallysound.Overall,quantifyingtheeffectofpricingondrivingrequiresrelativelyfewassumptionscomparedwithotherpolicies.

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Table2:AssumptionsandDataNeededtoEstimateEffectofState-LevelPricingStrategiesonVMTPanelA:FuelPrices

Step AssumptionsorDataNeeded

ValidityofAssumption(Scale:1=poor,5=excellent)

Futureresearchtaskstostrengthenassumptionsanddata

1.Quantifypercentageincreaseinfuelprice

Compareproposedtaxincreasestoexistingfuelprices

Validity=5(excellent)Dataareavailableonfuelprices,bystateandforareaswithinthestate.Fuelpricesvaryovertime,oftensubstantiallyso,andsoanalystswouldhavetoaddressthatvariationovertimeinassessingthe"base"(before-tax-increase)fuelprice.

Dataareavailable.

2.Determinepopulationthatwillbeaffectedbytax

Fueltaxestypicallyaffecteveryoneinthestate

Validity=4(good)to5(excellent)Theliteratureonpassengertravelandfueltaxesgivesgoodevidence;lessliteratureonfreighttravelandfueltaxes

Torefinefutureestimates,thestatecanstudyhowfreighttravelrespondstofueltaxesandwhetherthestrategyeffect,frommostlypassengervehiclestudies,appliestofreighttraffic.

3.Applystrategyeffecttoaffectedpopulation

Useelasticityof-0.1(minus0.1),perdiscussionabove

Validity=4(good)to5(excellent)

Studiesontheeffectsizearehighquality.FutureresearchshouldexaminehowvariationinfuelpricesovertimeaffectVMT,giventhehighmonth-to-monthandyear-to-yearvolatilityinfuelprices.Overthelong-term,taxesmightbedesignedtoadjustintheoppositedirectionofmarketfuelpricevariation,holdingat-the-pumpfuelpricesmoreconstant.

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PanelB:VMTFee




1.AssessextentofVMTfee

Feescouldbestatewideorforsub-setsofstate


TrafficwillcrossbordersifVMTfeedoesnotapplytoentirestate,andevenifstatewide,sometrafficwillenterandleavethestate.Someimprovementinstatewidetravelmodelingcouldbeneededtoaccountforbordereffects.

2.QuantifywhetherVMTfeewillberevenueneutral

AssumptionaboutrevenueneutralitywilltranslatetoamountoftheVMTfee


Continuepilotprogramstounderstandhowrevenuerespondstofeelevels

3.Iffeeisrevenueneutral,applyevidenceoneffect

OregonpilotprogramsuggestsrevenueneutralVMTfeewillreducedrivingby11to14percent

Validity=3(fair)to4(good)

EvidencefromCaliforniapilotprogram(nowunderway)shouldbeusedtosupplementtheOregonevidence

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PanelC:LinkorCordonTolls




1.Estimatetollamountandresultingchangeincostoftravel

Dataonpre-existingtravelneeded--useestimatesofnumberofpersonspassinglinkfromCaltranslinktraveldata(e.g.AADT),andestimatepre-tolldollarcostoftravelbasedonaveragetriplengths

Validity=3(fair)Dataonlinktravelcanbeobtained,buttheliteraturedoesnotclarifyifthetime-costoftravelshouldbeincludedinthebaseamounttoanalyzechangeintravelcost.

Californiahasexistingtolllanes,anddatafromthoselanesshouldbeusedtogetbetterinformationabouttheappropriatemeasureofthepopulationaffectedandhowtomeasuretollcostsforpurposesofapplyingtheelasticityofthestrategyeffect.

2.Estimatereductionintrafficintolledarea

Applyelasticities,whichforlinkandcordontollswillusuallypredictreductionintrafficinthetolledarea,notreductionsinVMT

Validity=3(fair)to4(good)

Continueresearch,particularlyoncordontollswhichhavenotbeenimplementedinU.S.andsorequireresearchfrominternationalsettings

3.Estimatedivertedtraffic

Estimatetheamountofdrivingthatmovedfromthetolledareatoadifferentroute

Validity=2(poor) Theevidenceonhowtollsdiverttrafficislimited.Leape(2006)estimates1/4ofreducedtrafficinLondoncordontollwasdivertedtootherroutes.TolllanepricechangesinCaliforniacanprovideanopportunityforbefore-afterstudiesoftrafficdiversion.

4.EstimateVMTreduction

Usedataorassumptionsaboutaveragetriplengths(beforetolling),reductionintrips,andthefractionoftripsdivertedtogetestimateofreducedVMT.

Validity=2(poor)to3(fair)

Divertedtrafficistheweakestlinkhere,andfutureresearchshouldfocusonhowtollpricechangesdiverttraffic.

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PanelD:Pay-As-You-Go-Insurance




1.AssessPopulationAffectedbyPay-As-You-GoInsurance

Ifprogramisvoluntary,usedatafrompilotprogramsorothermarketstoassesshowmanydriverswouldoptforpay-as-you-goinsurance

Validitity=3(fair) Thereisverylimitedexperiencewithpay-as-you-goinsurance.Pilotprogramsareadvisabletounderstandthe"takeup"rateforthisinsuranceproduct,particularlyifpay-as-you-gocompeteswithtraditionalflat-rateinsurance.

2.Quantifypercentageincreaseincostofdriving

Compareproposedpay-as-yougofees(permilebasis)toexistingper-miledrivingcosts


Dataareavailableonper-miledrivingcosts.

3.Determineeffectsizefordrivers

Assumepay-as-you-gostrategyeffectissimilartoVMTfeesorfueltaxes,henceelasticity=-0.1

Validity=4(good) ThepriceeffectislikelyverysimilartoVMTfeesorfueltaxeswhichchangethemarginal(e.g.per-mile)costofdriving.Pilotprogramsshouldbedevelopedtoconfirmthistheoreticalprediction.

4.Applyeffectsizetoaffectedpopulation

Directcalculationfromstepsabove


Again,ifpay-as-you-gocompeteswithflat-rateinsurance,understandingconsumerdemandforpay-as-you-gowillbeimportant

PolicyConsiderationsforPricingPricingpoliciesgeneratearevenuestream.Thatisanimportantpotentialbenefit.PricingalsobringssubstantialpolicyadvantagesbeyondVMTreduction.Pricingrevenuescanbeusedtoexpandnon-automobiletraveloptions,makingthepricingpoliciesthemselvesmoreeffectiveatVMTreduction.Similarly,pricingpoliciescanbeusedtoaddressequityconcerns,forexamplebyexpandingbusservice,providingpedestrianorbicycleimprovements,ormitigatingenvironmentalimpactsinlow-incomeneighborhoods.SalestaxfinancehasbecometheprimarymeansoftransportationfinanceinmostlargeCaliforniametropolitanareas.Thesalestaxisregressive,meaningthatsalestaxesarealarger

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fractionofincomeforlowerincomepersonsthanforhighincomepersons.Salestaxesarepaidbypersonsirrespectiveoftheiruseofroads,raisingbothefficiencyandequityissues.Fromanefficiencyperspective,salestaxesprovidenonexusbetweenrevenuesraisedanduseofthetransportationsystem.Fromanequityperspective,salestaxesarepaidbypersonswhodonotusethesystem,withlowerincomepersonspayingalargershareoftheirincomeinsalestaxes.SchweitzerandTaylor(2008)comparedthetoll-roadfinanceoftheSR-91inOrangeCountywithanequivalent(revenue-neutral)salestaxfinanceandfoundthatunderreasonableassumptionstollroadfinancewouldbemoreequitable,andthatsalestaxfinancecouldinmanycasesplacealargerburdenonlowerincomehouseholds.Pricingpolicieshavetheprospectofprovidingmuchneededrevenuesfortransportation,inwaysthatbuildalinkbetweenuseofthesystemandfinancingwhilebeingmoreequitablethancurrenttransportationfinancepolicies.PricingpolicieswillbemoreeffectiveinreducingVMTwhenandwherethereareeasilyavailablenon-automobileoptions.Hencepolicymakersshouldbeawarethatimplementingpricinginlocationswithmanytraveloptions,orwithaplantoexpandtraveloptions,wouldbeapreferredapproach.Fortunately,congestionandparkingpricingwouldlikelybeimplementedfirstincongestedurbanareasorinlocationswherelandvaluesarehigh,whicharetypicallythesamelocationswithnon-automobiletransportationoptions.WhileevidencesuggeststhatstateinterventiontoincreasethepriceofdrivingishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table2presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.

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2.InfillDevelopmentLanduseinCaliforniahaslongbeenalocaldomain,butmanyStateactionsandlaws,suchasRegionalHousingNeedsAssessment(RHNA)allocationsandtheCaliforniaEnvironmentalQualityAct(CEQA)influenceoutcomes.TheStatealsoprovidessubsidies,suchastheAffordableHousingandSustainableCommunities(AHSC)program,whichcanassistlocalitiesthatarepursuinginfilldevelopment.Statepolicy,andthelinkfromstatepolicytolocalpolicy,isimportant.Yettheevidenceismostclearonthestrategyeffect,theeffectfromlandusesassociatedwithinfilldevelopmenttoVMT.ManylandusepolicieshavethepotentialtoreduceVMT.TheARBpolicybriefsdiscusstheeffectofresidentialdensity,employmentdensity,landusemix,streetconnectivity,distancetotransit,regionalaccessibilitytojobs,andjobs-housingbalance.Theliteratureprovidesstrongevidencethatpersonswholiveinmorecentrallylocated,dense,mixedusedevelopmentswithwalkableinfrastructureandneartransitoptionswilldriveless.Theeffectoflanduseonreducingdrivingis,atleastinpartandpossiblyinlargestpart,causal,meaningthatwhenpersonsmovetoamixed-usetransit-orientedorwalkableneighborhood,thelandusecausesthemtodriveless(Cao,Mokhtarian,andHandy,2009;NationalResearchCouncil,2009;DurantonandTurner,2016.)WewillfirstdiscussthatbodyofevidenceontheeffectoflanduseandinfilldevelopmentonVMT(i.e.thestrategyeffect),thenturntotheupstreamquestionoftheeffectofstateandlocalpolicyoninfilldevelopment(i.e.thestrategyextent).Notethatpoliciestopromoteinfilldevelopmentarepoliciesthatwillplacemoreresidentsinlocationsthataremoreaccessibletojobsandtransit,withhigherdensities,moremixedlanduses,andbetterstreetconnectivity.Henceweuse“infilldevelopment”asasummarymeasureoflanduse,bothbecauseitisameaningfulmeasureandbecauseitclarifiespolicyapproachestometropolitanareaplanning.Statepoliciescanaffecttheprospectsforinfilldevelopment,andrecentstateactions(e.g.SB743)areattemptstomeasureimpactsinwaysthatchangetheattributedtraffic/transportationimpactofinfillversusoutlyingdevelopmenttomoreappropriatelygiveenvironmentalcredittoinfillprojectsthatwillreduceVMTinlargemetropolitanareas.StrategyEffect:ImpactofInfillDevelopmentonIndividualorHouseholdVMT

Statepolicy

Localpolicy

InfillDevt

VMT


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Thefirstquestionishowtomeasuretheeffectofinfilldevelopmentonindividualorhouseholdtravelbehavior.9Wesuggestthatthebestproxymeasureforinfilldevelopmentisregionalaccesstojobs.Bothlayaudiencesandpolicy-makersoftenthinkaboutresidentialdensitywhenmeasuringlanduse,becausedensityisintuitive(personsordwellingunitsperlandarea)andeasytomeasure.YetresidentialdensityisamongthelandusevariableswiththeweakestlinkstoVMT.ThestrategyeffectsizeofresidentialdensityonVMThasanelasticityfrom-0.05to-0.12,meaningthatifdensitydoubled,householdVMTwouldbereducedbyfrom5to12percent.Thestrategyeffectsizeofregionaljobaccessistwiceaslarge–anelasticityoffrom-0.13to-0.25.10ThisimpliesthatdensityaloneisalessmeaningfulmetricforVMTreductionthanproximitytojobcenters.However,inpractice,increaseddensityislikelyalsoneededtoincreasethenumberofhouseholdsnearjobcenters.Notonlyisthestrategyeffectofdensitysmallerthanthestrategyeffectofregionaljobaccess,regionaljobaccessisapolicywithapotentiallybroaderstrategyextent.Doublingresidentialdensitywouldbe,inmostlocations,outsideoftherealmoffeasiblepolicychanges.Asweshowintheappendix,infillpoliciescandoubleahousehold’sregionaljobaccessinCalifornia’surbanareassimplybyprovidinghousingoptionsthatareclosertojobconcentrations,andarelikelyfeasibleinwaysthatdoublingdensityisusuallynot.Overall,regionaljobaccessisamuchbettermeasureofthestrategyeffectandthepolicypossibility(strategyextent)ofinfilldevelopment.Improvingregionalaccesstojobsimpliesaplanningfocusonwhere,inthemetropolitanarea,newgrowthoccurs.Wouldnewgrowthbenearthecenter,wheremorejobsarelocatedandhencewhereaccesstojobsisgood,oronfringe,whereaccesstojobsisweaker?Atypicalmeasureofjobsaccessiscalleda“gravityvariable.”Mostgravityvariablesareasumofthejobsthataresidentcanreachfromtheirhousehold,multiplyingjobsbytheinverseofthedistancefromahousehold’shometothejob.Jobsthatareclosertowhereahouseholdlivescountformore,andjobsfartherawaycountforless.Therearedifferentmathematicalformulationsintheliterature.Someauthorssumonlyjobswithinfivemilesofahousehold(foranapplication,seeSalon,2014,orBoarnetandWang,2016.)Otherstudies(e.g.Zegras,2010)usedistancefromthedowntownbyitself,notingthatahousehold’sdistancefromdowntownisstronglycorrelatedwithgravityvariablemeasuresofjobaccess.Fornow,notethatdistancefromdowntown(e.g.,whetherahouseholdlive10milesfromdowntown,or20milesfromdowntown)iseasiertomeasurethanagravityvariablethatsumsalljobsinthemetropolitan9Oftentimestheacademicliteraturelooksathouseholdtravel,becausefamilymemberswithinahouseholdcantradetrips,suchthatonepersonmightgotothestorewhiletheotherdoesthebanking,orviceversa.Usinghouseholddataallowsresearcherstotreatthehouseholdasthebehavioralunit.Whentheoverallliteratureissummarized,aswedohere,thedisaggregatedataaretypicallyfromstudiesofindividualtravelersordrivers,orfromhouseholds.10SeetheARBResearchBriefsonresidentialdensityandregionalaccesstojobs,athttps://www.arb.ca.gov/cc/sb375/policies/density/residential_density_brief.pdfandhttps://arb.ca.gov/cc/sb375/policies/regaccess/regional_accessibility_brief120313.pdf,respectively.

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areaweightedbytheinverseofthedistancefromthehouseholdtothosejobs.Havingsaidthat,muchoftheliteraturehasusedgravityvariables,andsowediscussgravityvariablesfirst.Figure1showsgravityvariablemeasuresofjobaccessforthegreaterLosAngelesregion,infivecategories,orquintiles.Figure1showsthatlocationsneardowntownhavethebestjobaccess,andjobaccessdeclinesasonemovesfurtherfromdowntown.TheARBpolicybriefforregionaljobaccessibilitysuggestsanelasticityofVMTwithrespecttojobaccessrangingfrom-0.13to-0.25,meaningthatifjobaccessweredoubled(a100percentincrease),householdVMTwoulddeclinebyfrom13to25percent.Notethathighendoftherangeofthisstrategyeffectisalmostexactlythesameaswhatyouwouldgetifyouusedasimplermeasureofdistancefromdowntown,forwhichtheARBpolicybriefssuggestaneffectsizeof022to0.23,meaningthatifahouseholdmovesfrom10to20milesawayfromdowntown(a100percentincreaseintheirdistancetodowntown),theirVMTwouldincreaseby22to23percent.11

Figure1.GravityVariableofRegionalAccesstoJobs,metropolitanLosAngeles,2000(reprintedfromBoarnet,Houston,Ferguson,andSpears,2011,Figure7.3)

11SeetheARBResearchBriefsonregionalaccesstojobs,https://arb.ca.gov/cc/sb375/policies/regaccess/regional_accessibility_brief120313.pdf.

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Thestrategyeffectwouldmeasuremovingpersons(orchangingthelocationofnewdevelopment)fromplaceswithpoortobetterjobaccess.Asanexample,theSouthernCaliforniaAssociationofGovernmentshasproposedtofocusalmosthalfoftheregion’sfuturegrowthandnewdevelopmentinhighqualitytransitareas,definedasplaceswithinahalf-mileoffixed-routetransitorbustransitwithpeak-periodtransitserviceof15minutesorless.12Manyothermetropolitanareashaveengagedinscenarioplanningexercisestosimulatechangesingrowthpatternsthatwouldfavorinfilldevelopment.ReferringbacktothemapinFigure1,thedarkestshadedareashavethebestjobaccess(theyareinthefifth,orhighest,quintilesofaccess.)Thenextdarkestareasareinthefourthquintile,andthenexthighestareasareinthethirdquintile,andsoforth.ExamplecommunitiesinthoseareasareshowninTable3below.Table3:ExamplesofMunicipalitiesin3rd,4th,and5thQuintileofRegionalAccesstoEmploymentJobaccessquintilea Exampleneighborhood/municipality5thquintile(highestjobaccess) DowntownLosAngeles

HollywoodWestLosAngelesCrenshawEchoPark

4thquintile SantaAnaOrangeFullertonLakewoodLaMiradaSouthernSanFernandoValley

3rdquintile NorthOrangeCountyCovina

AnidealmeasureoftheeffectofinfilldevelopmentwouldmeasuretheeffectofchangingthelocationofdevelopmentonVMT–forexample,whatwouldhappenif,insteadofbuildingnewresidencesnearCovina(thethirdquintileofjobaccessinFigure1),theLosAngelesregionaddednewresidencesincommunitiessuchasSantaAna(thefourthquintileofjobaccess)orEchoPark(thefifthorhighestquintileofjobaccess.)Onemethodwouldbetoassess,numerically,howmuchameasureofahousehold’sjobaccesswouldincreasewhentheylocatein,forexample,SantaAnaorEchoParkasopposedtoCovina.Suchamethodisoutlinedintheappendix.Thisapproachwouldrequireseveralcomputationalsteps,andforsimplicitywedo

12SCAG’s2016RegionalTransportationPlanprojectsthat46percentofnewresidentialgrowthand55percentofnewemploymentgrowthwillbeonthethreepercentoftheregion’slandthatisinhighqualitytransitareas.SeeSouthernCaliforniaAssociationofGovernments,2016RTP/SCS,ExecutiveSummary,p.8,http://scagrtpscs.net/Documents/2016/final/f2016RTPSCS_ExecSummary.pdf.

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notgooverthathere,althoughwenotethattheestimatedstrategyeffectcomputedintheappendixissimilartowhatwepresenthereusingsimplermethods.Ratherthanuseagravityvariableforregionalaccesstojobs,onecouldusedistancefromthedowntowntoapproximatethechangeinthejobaccessmeasure.Followingtheexample,Covinaisapproximately24miles(drivingdistance)fromdowntownLosAngeles,whileEchoParkisapproximately4milesfromdowntownLosAngeles,areductionindistancefromdowntownof83percentifinfilldevelopmentcouldallowahouseholdtolocateinEchoParkratherthanCovina.Multiplyingthatchangeindistancebythe0.22effectsizeofdistancefromdowntown,thisimpliesthatmovinghouseholdsfromCovinatoEchoParkcouldreducetheirdrivingby18percent.Usingmoresophisticatedregressiontechniques,BoarnetandWang(2016,Table12,p.36)predictthatahouseholdmoveacrosssimilardistancesintheLosAngelesregioncouldbeassociatedwithevenlargerVMTreductions–aslargeas33percent.13Wecanusetheliterature,witheffectsizesdrawnfromchangesingravityvariablesorsimplerchangestodistancefromdowntown,topredicttheeffectofincreasedinfilldevelopment.Table4givesanillustrationofthestepsandthedataandassumptionsneeded.

13SeeMarlonG.BoarnetandXizeWang,UrbanSpatialStructureandthePotentialforReducingVehicleMilesTraveled,NationalCenterforSustainableTransportationresearchreport,April,2016,availableathttp://ncst.ucdavis.edu/wp-content/uploads/2014/08/04-18-2016-NCST-Urban-Spatial-Structure-Boarnet-4_10_16.pdf,accessedSept.24,2016.

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Table4:AssumptionsandDataNeededtoEstimateEffectofInfillDevelopmentonHouseholdVMTStep AssumptionsorData

NeededValidityofAssumption(Scale:1=poor,5=excellent)


1.Measurelandusepatternsassociatedwithinfilldevelopment

Chooseameasurethatwillproxylocationintheregion,andhenceinfillpolicies:Regionaljobaccessmeasuresasagravityvariableordistancefromdowntown

Validity=3(fair)to4(good)Ifaccesstotransitandaccesstonon-autotransportationareincludedelsewhereintheanalysis,evidenceindicatesthatremaininglandusepatternsarecorrelatedwithregionaljobaccess;theevidencesuggeststhatthesizeofthestrategyeffectisverysimilarwhethermeasuredbygravityvariablesordistancefromdowntown,eveninhighlysub-centeredmetroareas

DevelopstatewideGISmeasuresoflandusecharacterizedbyeither(1)distancefrommetropolitanareadowntown,(2)gravitymeasureofregionalaccesstojobs,or(3)thelandusecategoriesdevelopedinresearchbySalon(2014)whichcanlikelybeanalogstoregionaljobaccess

2.Usedataacrossdifferentlocationstoproxyinfilldevelopment–translateinfilltochangesinajobaccessgravityvariableorchangesindistancefromdowntown.

Needassumptionsorinformationfromscenariomodelsaboutdifferentgrowthscenariosformetropolitanareastounderstandhowregionaljobaccesswouldchange,andforhowmanyhouseholds

Validity=2to3(poortofair)Thereareseveralscenariotools,butallsuchtoolsarepossiblepolicyfutures.Therewillbeuncertaintyregardingtheamountofinfilldevelopment,andwesuggestmodelingseveralpossiblefutureinfillgrowthscenarios,fromaggressiveuseofinfilltosomewhatlessaggressive,toboundpossibilities.

RecommendusingorupdatingthescenariotooldevelopedaspartofSalon(2014)forstatewidesimulationsofmovesacrossdevelopmenttypes.

3.UseanelasticityofhouseholdVMTwithrespecttoregionaljobaccesstocalculatepercentagechangesinhouseholdVMT

UseregionaljobaccesselasticityfromARBregionalaccessibilitybrief.

Validity=4(good)Jobaccesselasticitiesvarywithinmetropolitanareas,asdemonstratedbyBoarnetetal.(2010)andSalon(2014),butregionalaveragesgiveagoodmid-pointoraverageeffect.

Userangesofelasticitiesfrom,e.g.,Boarnetetal.(2010)orSalon(2014),oradaptandusethescenariotoolfromSalon(2014)

4.ApplypredictedpercentagechangeinhouseholdVMTtoabase-yearmeasureofhouseholdVMTtoobtainpredictedchangeinhouseholdVMT.

ApplypredictedpercentagechangeinhouseholdVMTtoaveragehouseholdVMTforametropolitanareaorthestate.

Validity=2to3(poortogood)TheCHTShasdataonhouseholdVMTindifferentlocations.Thesedataareavailableandreliable.Thedifficultyisunderstandingwherehouseholdsmighthavelocatedabsentinfillpolicies,apointcurrentlynotsufficientlyaddressedintheliterature.Scenariomodelscanbeusedtoassesswherehouseholdswouldhavelivedabsentinfillpolicies.

Moreresearchonhowchangesinhousingsupplyinspecificlocations(e.g.infill)affectresidentiallocationchoicesofhouseholds.

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Table4illustratesfoursteps,(1)measuringlandusepatterns,(2)simulatingchangesindevelopmentpatterns(e.g.frominfilldevelopment)andtranslatingthosechangesindevelopmentpatternsintochangesinameasureofregionaljobaccessordistancefromdowntown,(3)usingelasticitiesintheliteraturetomeasuretheimpactofachangeinregionalaccesstojobs(ordistancetodowntown)onVMT,and(4)applythepredictedchangeinVMTtoabaseyearlevelofhouseholdVMT.Table4startswithafirststepofmeasuringlanduse,eitherwithgravityvariablesorwithsimplermeasuresofdistancefromdowntown.NotethattheAirResourcesBoardrecentlyfundedresearchbySalon(2014)whichdevelopedstatewidecategoriesofneighborhoodtypes,andthoseneighborhoodtypesmightbecloseapproximationstoregionaljobaccess,andsoweaddthoseneighborhoodtypesdevelopedbySalon(2014)tothelistofpossibleregionaljobaccessmeasures.AcomplementaryapproachcouldbebasedontheCaliforniaStatewideTravelDemandModel,whichhasemploymentdataforzonesstatewide.14Thesecondstepwouldassesshowchangesintheamountofinfilldevelopmentwouldleadtochangesinjobaccessandhowmanypersons(households)wouldbeaffectedbythosechanges.Wesuggestboundingpossibleamountsofnewdevelopmentinthissecondstep,fromamodestamountofinfilltoaggressiveuseofinfill,relyingonlocalpolicyexpertisetoinformhowmodestandaggressivewouldbequantifiedintermsofnumberofnewhousingunitsandhencethenumberofhouseholdsaffected.Step3inTable4applieselasticitiesfromtheARBjobaccesspolicybrief.Wenotethatthereisanascentliterature(Boarnet,2011;Salon,2014)thatgivesevidencethatthestrategyeffectofregionaljobaccessonVMTvariesdependingonwhere,inthemetropolitanarea,ahouseholdlives,butwealsonotethatmid-pointoraverageestimatesofthepolicyeffectwillbothworkwelland,ifanything,understatetheVMTeffectofinfilldevelopment.15Thelaststepwouldbetoapplythestrategyeffect(percentreductioninVMT)tothenumberofhouseholdsaffectedbythestrategy.Theevidenceisconsistentandverystrongthathouseholdsthatliveinmorecentrallocationsinurbanareasdriveless.Thatrelationshipisverycommoninthedata,andsophisticatedstudiesthatattempttocontrolforhouseholdlocationchoicessuggestthatmorecentrallocationswithbettermulti-modaltransportationaccesscausehouseholdstodriveless(e.g.DurantonandTurner,2016;Spears,Houston,andBoarnet,2016.)Whilewesuggest,inStep4ofTable4,thatthestatecontinuetoresearchhowdifferenthouseholdschoosetheirresidentiallocation,andhencewhichhouseholdswouldmoveintoinfilldevelopments,wenotethatsuchinformationwillbemoreimportanttounderstandquestionsofequity(e.g.gentrificationanddisplacement)

14SeetheSB743ImpactAssessmentWebpage,athttp://www.dot.ca.gov/hq/tpp/offices/omsp/SB743.html.ThedataavailabletherecanprovideabasisformeasuresofemploymentinzonesthroughoutCalifornia,andhenceformeasuresofemploymentaccess.15Thestrategyeffectofregionalaccesstojobsmightbelargerincentrallylocatedareas,implyingthatusingthemetropolitan-wideaverageeffectsfromtheARBpolicybriefsmightunderstatetheVMT-reducingeffectofinfilldevelopment.Foradiscussionandevidence,seeBoarnetetal.(2010)andSalon(2014).

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ratherthantounderstandwhetherhouseholdsincentrallocationsdriveless.Theliteratureprovidesstrongevidencethathouseholdsinmorecentralpartsofurbanareasdriveless.StrategyExtent:ImpactsofStatePoliciesonInfillDevelopmentWhilethereisstrong,evidence-basedcorrelationbetweeninfilldevelopmentandVMTreduction,estimatingstate-wideVMTeffectsofStatepoliciestoencourageinfilldevelopmentrequiresadditionalassumptionsabouttheeffectivenessofstatepoliciesinmakinginfilldevelopmenthappen.Thereisstillalackofempiricalliteratureonhowstatepoliciesleadtomore(orless)infilldevelopment,butthestate’sexistingpolicyframework,includingbutnotlimitedtoSB375,provideanopportunitytostudyhowstategoalsandrequirementsinfluencedevelopmentactivity.Fornow,wenotethatthestatehasmanypolicytoolsthatcaninfluencedevelopment.StatePolicyConsiderationsforInfillDevelopmentThestatehasinterestsinincreasinginfilldevelopment,andtheliteraturedemonstratesthatdoingsowilladvanceStateVMTreductiongoals(aswellasmultipleotherStatepolicypriorities).SB743changedthetrafficimpactmetricinCEQA,andGovernorBrownrecentlyproposedaby-righthousingproposalwhichwasnotacteduponbythelegislature.Thestatehasalsorecentlytakenactiononauxiliarydwellingunits.Morecouldbedonebycontinuedchangesinthemeasurementofimpactsrequiredbystatelegislation(e.g.CEQA),orwithlegislationthatallows(orevenrequires)streamlineddevelopmentapprovalwhencertainconditions(possiblyinfilllocationand/orprovidingaffordablehousing)aremet.Thestatecouldalsosubsidizeinfilldevelopment,orprovidetaxreductions,whichcouldincentivizeincreasedinfilldevelopment,althoughwenotethatsuchtools,inisolation,wouldnotgetaroundrestrictivelocallanduseregulations.Additionally,theStatecouldaddtothe“toolbox”ofexistingfinancingtoolsforinfilldevelopmentandalsothefinancingthatisavailableforcritical,infill-supportiveinfrastructure,whichwouldalsolikelyincentivizeanincreasedshareofinfilldevelopment.Financingtoolsarelikelytobeparticularlycriticalinshapingfuturedevelopmentpatternsinareasofthestatewhereinfillisataneconomicdisadvantagecomparedtogreenfieldormoreremotedevelopmentduetomarketconditionsand/ordistressedconditionsininfillareas.Finally,theStatecoulddirectlyincentivizeconsumerchoice,forexamplethroughlow-VMThousingrebatesor“livewhereyouwork”incentiveprograms.Thelocationofinfrastructure,includinghighways,transit,schools,andmajorpublicbuildings,canalsoinfluencegrowthpatterns.16Aligningstateinfrastructurespendingwithinfillgoals,e.g.throughperformancemetricsorothercriteria,wouldbeonewaytoensurebetterleveragetheseinvestmentstofurtherVMTandGHGreductiongoals.

16Forevidenceoftheeffectofhighwaysongrowthpatterns,seeFunderburg,etal.(2010)andBaum-Snow(2007).

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WhileevidencesuggeststhatstateinterventiontoincreaseinfilldevelopmentishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table4presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.

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3.TransportationInvestmentsInthissection,weseparatelyconsidertheVMTimpactsofthreecategoriesoftransportationinvestments:bicycleandpedestrianinfrastructure,transitservice,andhighwaycapacity.Althoughtheimpactsofbicycleinfrastructurearedistinctfromtheimpactsofpedestrianinfrastructure,themethodsforprojectingtheirimpactsaresimilar,soweconsiderthemtogether.Thesubsectionontransitfocusesontheimpactofexpansionsintransitserviceratherthaninfrastructureperse,giventhenatureoftheresearchavailable.Weconsideronlyintra-regionaltransitservice,ratherthaninter-regionalservicesuchashigh-speedrail,thepotentialGHGimpactsofwhichhavebeenquantifiedusinganARB-approvedmethodology.17ThesubsectiononhighwaycapacitydiffersfromthefirsttwointhattheavailableresearchprovidesevidenceonincreasesinVMTresultingfromincreasesincapacity.3.1BicycleandPedestrianInfrastructure StrategyEffect:ImpactofBicycleandPedestrianInfrastructureonIndividualorHouseholdVMTInvestmentsinbicycleandpedestrianinfrastructurehavethepotentialtoreduceVMTbyencouragingashiftfromdrivingtotheseactivetravelmodes.Agrowingbodyofresearchshowsastrongconnectionbetweentheextentofbicycleandpedestrianinfrastructureandtheamountofbicyclingandwalkinginacommunity.Manyoftheavailablestudiesfocusoncommutetripsratherthanactivetravelforallpurposes;somestudiesdonotseparateactivetravelfromrecreationalwalkingandbicycling.Moststudiesmeasureinfrastructureinvestmentsintermsofmilesoffacilitiesorpercentageincreasesinmilesoffacilitieswithoutaccountingforthequalityofthenewfacilitiesortheirimpactontheconnectivityofthebicycleorpedestriannetwork,thoughcurrentstudiesarebeginningtoprovideinsightsintotheeffectsoffacilitycharacteristicsandnetworkconnectivity,notjustextent(e.g.Monsere,etal.2014).AssummarizedintheARBResearchBriefs,differencesbetweenthestudiesdonotenableaconsensusestimateofthestrategyeffect,thoughresultsfromindividualstudiescouldbeused.Arelativelyrecentstudyof24Californiacitiesfoundthata1%increaseinthepercentofstreetlengthwithbikelanesinacitywasassociatedwithanincreaseofabout0.35%intheshareof17https://www.arb.ca.gov/cc/capandtrade/auctionproceeds/hsrinterimqm.pdf

Statepolicy

Localpolicy

Infra-structure

Modeuse

VMT


24

workerscommutingbybicycle(MarshallandGarrick,2010).Theseresultssuggestthatinacitywhere1%ofcommutersbicycle,a100%increase(i.e.adoubling)inthepercentofstreetswithbikelaneswouldincreasethebicyclecommutershareto1.35%.Forwalking,aNorthCarolinastudyfoundthata1%increaseintheportionoftheroutewithsidewalkswasassociatedwitha1.23%increaseintheshareofwalkcommuting(RodriguezandJoo,2004),thoughotherstudiessuggestamuchmoremodesteffect.WhiletheliteraturestronglysuggeststhatbikeandpedestrianinfrastructureincreasebikingandwalkingandthereforedecreaseVMT,quantifyingtheprecisereductionsinVMTistricky.First,studiessuggestthattheeffectsofinvestmentsdependonthecontext,includingtheadoptionofotherstrategiestopromotewalkingandbicycling,suchaseducationalprogramsorpromotionalevents(Pucher,etal.,2010).Comprehensiveeffortsthatcombinestrategicandhigh-qualityinfrastructureinvestmentswithpromotionandeducationoveraperiodoftimehavebeenshowntoproducesubstantialincreasesinbicycling.Inaddition,investmentsinfacilitiesthatconnectimportantdestinationsandcontributetotheoverallconnectivityofthenetworkwillhavemoreimpactthanstand-alonefacilitiesthatdonotserveimportantdestinationsorhelptobuildalargernetwork.Second,newwalkingandbikingtripsdonotnecessarilyreplacedrivingtrips;theymayreplacetransittrips,forexample,ortheymaybeentirelynewtrips.Thedegreetowhichwalkingandbikingtripssubstitutefordrivingtripsisdifficulttopinpoint,asdiscussedbyPiatokowski,etal.(2015).Third,whenthesetripsdosubstitutefordriving,theymaybeshorterthanthetripstheyreplace,particularlyfornon-commutetrips.Forexample,anindividualmaychoosetobiketoanearbystoreratherthandrivingtoastoreacrosstown,inwhichcaseameasureoftheincreaseinbicyclingdistancewouldunderestimatethereductionindrivingdistance.Fourth,reductionsinVMTfromnon-commutetripsarealsolikelytooccur.Thus,projectedreductionsinVMTbasedonthecommuteeffectsarealmostcertainlylowerthantheprobablereductions.ProjectingstatewidereductionsinVMTresultingfrominvestmentsinbicycleandpedestrianinfrastructurerequiresassumptionsabouteachofthesepossibilities,asoutlinedinTable5.StrategyExtent:ImpactofStatePolicyonBicycleandPedestrianInfrastructureInvestmentsinbicycleandpedestrianinfrastructurearemostlymadeatthelocallevelbycitiesandsometimescounties.Statepolicycaninfluencesuchinvestmentsthroughgrantprograms,forexample,Caltrans’ActiveTransportationProgram.Thestatecan(andindeeddoes)encouragesuchinvestmentsbyallowingMetropolitanPlanningOrganizationstodeveloptheirowngrantprogramsusingthestateandfederalfundsallocatedtotheMPO.However,researchshowsthatsimplyallowingMPOstospendfederalfundsonbicycleandpedestrianinfrastructuredoesnotguaranteethattheywill(HandyandMcCann,2011).EstimatingstatewidereductionsinVMTresultingfromStatepoliciesandprogramsthatsupporttheexpansionofbicycleandpedestrianinfrastructurerequiresanestimateoftheincreaseinbicycleandpedestrianinfrastructureoveraspecifiedperiodoftime(seeTable5,Step2).Thisincreasedependsonwhatpoliciesthestateadopts,howMPOsandlocalgovernmentsrespond

25

tothesepolicies,andhowStateactionsinfluencetheinvestmentsthatlocalgovernmentschoosetomakewiththeirownfunds–allverydifficulttopredictwithprecision.Oneapproachtoestimatingthepercentincreaseinbike/pedinfrastructureistoestimatethefundingavailablefortheseinvestmentsforthespecifiedperiodoftime,thenconvertthisamounttomilesofbikefacilitiesandsidewalksusingdataonthepermilecostsofsuchfacilities.Anotherapproachistoanalyzeincreasesininfrastructureforselectedcitieswheregooddataontheextentofinfrastructureattwoormorepointsintimeisavailable.SanFrancisco,forexample,isplanningtodoubleitsmilesofprotectedbikelanes(from15to30miles)inthenext15months.18Becausebicyclefacilitiesarelessubiquitousthanpedestrianfacilities,agivenlengthofnewfacilitywillrepresentalargerpercentageincreaseforbicycleinfrastructure.StatePolicyConsiderationsforBike/PedInfrastructureTheavailableevidenceshowsastrongconnectionbetweentheextentofbicycleandpedestrianinfrastructureandtheamountofwalkingandbicycling.AlthoughprojectingtheVMTimpactsofnewinvestmentsinsuchinfrastructureinvolvesanumberofcriticalassumptions,givenlimitationsintheavailableevidence,thisstrategyshowsstrongpotentialforreducingVMT,inadditiontoproducingotherbenefitsforthecommunity(seeSallis,etal.2015foradiscussionofco-benefits).ResearchsuggeststhatstateactionstoincreasebicycleandpedestrianinfrastructurewouldbemosteffectiveinreducingVMTifimplementedinconjunctionwithpromotionalandeducationalprograms(Pucher,etal.2010).Inaddition,emergingevidencesuggeststhathigherqualityinfrastructure,suchasprotectedbicyclelanes,aremoreeffectiveinpromotingincreasesinactivetravel(e.g.Monsere,etal.2014),sostateactionscouldprioritizesuchhigh-qualityinfrastructuretoensuremaximumVMTreductionpermileofinfrastructure.Networkconnectivityisalsonowrecognizedasacriticalconsiderationinprioritizinginvestmentsinbicycleandpedestrianinfrastructure(Mekuria,etal.2012),sostateactionsthatprioritizeconnectivityimprovementscouldagainhelptoensurethehighestVMTreductionspermileofinfrastructure.StatepolicycurrentlyencouragessuchinvestmentsinbicycleandpedestrianinfrastructurethroughgrantprogramsandbygivingMPOsflexibilityinhowtheyspendtheirstateandfederalfunds.StrongerstatemeasurescouldrequireMPOstospendacertainshareofstatefundingonthesemodesorsetperformancestandardsforwalkingandbicyclingthatMPOsmustmeetinordertoreceivefunding.Additionally,theStatecouldallocateagreaterportionofstatetransportationfundstodirectinvestmentsinpedestrianandbicycleinfrastructure.AnyofthesemeasurescanhelpensuremaximumVMTreductionpermilecreatedbyincorporatingtheconsiderationsintheparagraphaboveintoguidelinesfortheallocationoffunds.

18https://www.sfmta.com/about-sfmta/blog/new-generation-bikeways-coming-san-francisco

26

WhileevidencesuggeststhatstateinterventiontoincreasebicycleandpedestrianinfrastructureishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table5presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.Table5.SuggestedStepsforCalculatingVMTImpactsofBicycleandPedestrianInfrastructureInvestmentsStep AssumptionsorData



1.Measureexistingbicycle/pedestrianinfrastructure

Mostcommonmeasureispercentofstreetlengthwithbike/pedfacilities

Validity=3(fair)Mostcommonmeasuredoesnotaccountforqualityoffacilitiesortheconnectivityofthenetwork.

DevelopstatewideGISdatabaseofbike/pedfacilities,includingcharacteristicsoffacilities.Developmeasuresofnetworkconnectivity.

2.Measurechangesinbicycle/pedestrianinfrastructureaspercentageofcurrentinfrastructure

Estimateadditionalbikeorpedinfrastructurethatcouldbeconstructedgivenfundingavailable,forstateorbyregion.

Validity=3(fair)Costsofinfrastructurevarybyfacilitytypeandcontext.

3.Useanelasticityof%bike/pedcommutingwithrespecttobike/pedinfrastructuretocalculatepercentageincreasein%bike/pedcommutetrips

UsebikeorpedelasticityfromARBbicycleorpedestrianinfrastructurebrief.

Validity=3(fair)Bike/pedelasticitiesmayvarybycontext.Availableelasticitiesaccountonlyforbike/pedcommuting,notbike/pedtravelforotherpurposes.

Conductstudiesoftheimpactsofbike/pedinfrastructureinvestmentsthatmeasurechangesinallbicyclingorwalkingtrips,bytrippurpose.

4.Applypredictedpercentagechangein%bike/pedcommutetripstoabase-yearmeasureofannualstatewideorregionalbike/pedcommutetripstoestimateincreaseintotalannualbike/pedcommutetrips

Useestimateofannualstatewidebike/pedcommutetripsorestimatesbyregion.

Validity=4(good)TheCHTShasdataonbike/pedcommutetripsstatewideandbyregion.Bike/pedtripsmaybeunderreported.(NotethatAmericanCommunitySurveydatareportsonlyusualcommutemode.)

Improvesurveydesigntobettercapturebike/pedtripsbypurpose.

27

Table5.SuggestedStepsforCalculatingVMTImpactsofBicycleandPedestrianInfrastructureInvestments(Continued)Step AssumptionsorData



5.Adjustnumberoftripstoreflectswitchingfrommodesotherthandrivingtoestimatereductionintotalannualdrivingcommutetrips

Applydrivingcommutemodeshareforstateorbyregion.

Validity=2(weak)Propensitytoshifttobike/pedcommutingmayvarybycurrentmodeandbycontext.

Conductstudiesoftheimpactsofbike/pedinfrastructureinvestmentsthatmeasureshiftsbetweenmodes.Conductsuchstudiesindifferentcontexts.

6.ConvertreductionintotalannualdrivingcommutetripstoreductionintotalannualcommuteVMT

Useestimateofaveragecommutedistanceforbike/pedcommutersstatewideorbyregion.

Validity=3(fair)TheCHTShasdataonaveragecommutedistanceforbike/pedcommutersstatewideandbyregion.Drivingcommutetripseliminatedbynewbike/pedtripsmaybelonger(orshorter)thancurrentbike/pedcommutedistances.

Conductstudiesoftheimpactsofbike/pedinfrastructureinvestmentsthatmeasurecommutedistancefornewbike/pedcommuters.

3.2TransitInvestmentsStrategyEffect:ImpactofTransitInvestmentsonIndividualorHouseholdVMTInvestmentsintransitservicehavethepotentialtoreduceVMTbyencouragingashiftfromdrivingtotransit.Manydifferenttypesofinvestmentsarepossible,includingimprovedaccesstobusstopsandrailstations,coordinatedschedulesandtransfersbetweensystems,real-timeinformationaboutarrivalsanddepartures,andelectronicfarecards.AssummarizedintheARBTransitServiceresearchbrief,however,mostresearchfocusesontheeffectsofchangesinfares,changesinservicefrequency(orchangesinheadways),orchangesinmilesofservice.Moststudiesexaminetheeffectsofthesechangesforbussystems,thoughsomereporteffects

Statepolicy

Agencypolicy

Servicelevel

Transituse

VMT


28

forrailsystems.Outcomesaremeasuredintermsofchangesintransitridership,i.e.thenumberoftransittripsmadeforthespecifiedperiodoftime.AccordingtotheARBresearchbrief,theavailableresearchshowsthata1percentincreaseinservicefrequencywillleadtoaridershipincreaseofapproximately0.5percentandthata1percentincreaseinservicehoursormilescouldleadtoahigherincreaseofaround0.7percent.Effectsizesarelikelytobehigherincaseswheretheinvestmentstarget“choice”riderswhoarenotdependentontransit,higher-incomeriders,off-peakandnon-commutetrips,andsmallcitiesandsuburbanareas.Thesefindingsareapplicabletometropolitanareasbutnotnecessarilytoruralareaswheretransitserviceissparse.Aswithbicycleandpedestrianinvestments,althoughtransitinvestmentsarelikelytoreduceVMT,quantifyingtheeffectsoftransitinvestmentsonVMTisnotstraightforward.First,studiessuggestthattheeffectsofinvestmentsdependonthecontext,asnotedabove.Second,notallnewtransittripsreplacedrivingtrips;theymayinsteadreplacebicyclingorridinginacarpool,ortheymaybeentirelynewtripsthatwouldnototherwisehavebeenmade.Third,newtransittripsmaybeshorter(orlonger)inlengththananydrivingtripstheyreplace.Forexample,anindividualmaychoosetotakethebustotheneareststoreratherthandrivingtoastoreacrosstown,inwhichcaseameasureoftheincreaseintransitdistancewouldunderestimatethereductionindrivingdistance.ProjectingstatewidereductionsinVMTresultingfrominvestmentsintransitservicerequiresassumptionsabouteachofthesepossibilities,asoutlinedinTable6.ArecentstudyoftheopeningoftheExpoLineinLosAngelesprovidessomeofthemostdirectevidenceavailableoftheimpactoftransitinvestmentsonVMT(Spears,etal.2016).Thisstudy,whichmeasuredVMTforhouseholdslivingnearthenewlight-raillinebeforeandaftertheopeningoftheline,foundthathouseholdslivingwithin1mileofanewExpostationdrovealmost11mileslessperdaybecauseofthenewline18monthsafteritsopening.Theauthorsconcludethatlargeinvestmentsinlightrail,coupledwithsupportivelandusepolicies,have“thepotentialtohelpachieveclimatepolicygoals.”StrategyExtent:ImpactofStatePolicyonTransitInvestmentsBecausemuchofthefundingforintra-regionaltransitflowsdirectlyfromtheUSDOTtotransitagencies,thestateroleinpromotingtransitinvestmentsismorelimitedthanitisforothermodes.Inaddition,transitimprovementsareincreasinglyfundedthroughcountyandregionalsalestaxmeasures,suchastheupcomingballotmeasuresinSacramento,theBayAreaandLosAngeles.ThestateprovidestransitfundingthroughStateTransitAssistance19,bondmeasuressuchasProp1B20,andmorerecently,throughtheCaliforniaClimateInvestmentsFund(capandtradeproceeds).

19http://www.sco.ca.gov/Files-ARD-Payments/Transit/statetransitassistanceestimate_1617_january16.pdf20http://www.dot.ca.gov/hq/transprog/ibond.htm

29

EstimatingstatewidereductionsinVMTresultingfromimprovementsintransitservicerequiresanestimateoftheincreaseintransitserviceoveraspecifiedperiodoftime(seeTable6,Step2).Thisincreasedependsonwhatpoliciesthestateadopts,howtransitagenciesrespondtothesepolicies,andtheinvestmentsthattransitagencieschoosetomakewiththeirownfunds–allverydifficulttopredictwithprecision.Oneapproachtoestimatingthepercentincreaseintransitserviceistoestimatethefundingavailableforserviceimprovementforthespecifiedperiodoftime,thenconvertthisamounttohoursormilesofserviceusingdataonthepermilecostsofsuchservice.AnotherapproachwouldbetocompileproposedtransitinvestmentsintheRegionalTransportationPlansfortheMetropolitanPlanningOrganizationsinthestateandassumethisleveloraproportionatelyhigherlevel(toreflectnewstatepolicy)ofinvestmentintransitservice.StatePolicyConsiderationsforTransitInvestmentsTheavailableevidenceshowsastrongconnectionbetweentheextentoftransitserviceandtransitridership.AlthoughprojectingtheVMTimpactsofnewinvestmentsintransitserviceinvolvesanumberofcriticalassumptions,givenlimitationsintheavailableevidence,thisstrategyshowsstrongpotentialforreducingVMT.Serviceexpansionsarelikelytohavemoreimpactwhencombinedwithotherstrategiessuchasimprovedaccesstobusstopsandrailstations,coordinatedschedulesandtransfersbetweensystems,real-timeinformationaboutarrivalsanddepartures,andelectronicfarecards.TheimpactsoftransitinvestmentsonVMTarelikelytobehigherincaseswheretheinvestmentstarget“choice”riders,higher-incomeriders,off-peakandnon-commutetrips,andsmallcitiesandsuburbanareas.TheStatecanincreasetheVMT-reductionimpactofstateactionstoincreasetransitridershipbyconsideringtheseconditionswhen,forexample,developingguidelinesforfundingallocations,alongwithotherconsiderationsthatachieveotherpolicygoals,e.g.prioritizinginvestmentsindisadvantagedandlow-incomecommunities.Althoughthebulkoftransitfundingcomesfromfederalandlocalsources,theStatedoesprovidetransitfundingtoregionalandlocaltransitagenciesthroughanumberofdifferentprograms.ThestatecouldensurelargerreductionsinVMTbytargetingthisfundingtoareasandinvestmentsthatarelikelytohavelargerimpacts.TheStatecouldalsoconsiderprogramsthatdirectlyencouragetransituse,includingtaxbreaksforemployer-providedtransitpassesmodeledonfederalpolicy.21Statepoliciesthatpromoteinfilldevelopmentaroundtransitstationscanalsohelptoincreasetransituse(seesectiononInfillDevelopment).Effortstocoordinateservicesamongregionalandlocalagenciescouldprovevaluableaswell.WhileevidencesuggeststhatstateinterventiontoimprovetransitserviceishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–for

21http://www.nctr.usf.edu/programs/clearinghouse/commutebenefits/

30

thepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table6presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.forCalculatingVMTImpactsofTransitInvestmentsTable6.SuggestedStepsforCalculatingVMTImpactsofTransitInvestmentsTable6.SuggestedStepsforCalculatingVMTImpactsofTransitInvestmentsStep Assumptionsor

DataNeededValidityofAssumption(Scale:1=poor,5=excellent)


1.Measurecurrenttransitserviceinmetroareas

Mostcommonmeasuresisservicehoursormiles.

Validity=3(fair)Measuredoesnotaccountforqualityofserviceorconnectivityofthetransitnetwork.

ExtractstatewidedataontransitservicefromNationalTransitMapandadddataasneeded.Developmeasuresofnetworkconnectivity.

2.Measureincreasesintransitserviceaspercentageofcurrentservicebymetroarea

CompileplannedincreasesintransitservicefromRTPsandassumeproportionateincreasebasedonproportionateincreaseinfunding

Validity=4(good)Costsofexpansionvarybyservicetypeandcontext.

DevelopaGISdatabaseoffundedtransitserviceincreases

3.Useanelasticityofridershipwithrespecttotransitservicetocalculatepercentageincreasesintransitridershipbymetroarea

UsetransitridershipelasticityfromARBtransitbrief

Validity=3(fair)Transitridershipelasticitiesmayvarybytypeofimprovementandcontext.

Conductstudiesoftheimpactsoftransitimprovementsofdifferenttypesandindifferentcontexts.

4.Applypredictedpercentagechangeintransitridershiptoabase-yearmeasureofannualtransittripsbymetroareatoestimateincreaseintotalannualtransittripsbymetroarea

Useestimateoftransittripsbyregion

Validity=5(excellent)Transitagenciesreportannualridership.

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Table6.SuggestedStepsforCalculatingVMTImpactsofTransitInvestments(Continued)Step Assumptionsor



5.Adjustincreaseintotalannualtransittripstoreflectswitchingfrommodesotherthandrivingtoestimatereductioninannualdrivingtripsbymetroarea

Applydrivingmodesharebymetroarea.

Validity=2(weak)Propensitytoshifttotransitmayvarybycurrentmodeandbycontext.

Conductstudiesoftheimpactsoftransitimprovementsthatmeasureshiftsbetweenmodes.

6.ConvertchangeintotalannualdrivingtripstochangeintotalannualVMTbymetroarea

Useestimateofaveragetripdistancefortransitridersbymetroarea.

Validity=3(fair)TheCHTShasdataonaveragedistancefortransittripsbymetroarea.Drivingtripseliminatedbynewtransittripsmaybelongerorshorterthancurrenttransittripdistances.

Conductstudiesoftheimpactsoftransitimprovementsthatmeasuretripdistancefornewtransittrips.

3.3HighwayCapacityStrategyEffect:ImpactofHighwayCapacityonAggregateVMTIncreasedhighwaycapacityissometimesproposedasastrategyforreducingGHGemissions,followingthelogicthatincreasedcapacitywillreducecongestion,smoothtrafficflow,andtherebyreduceGHGemissionsthroughimprovedefficiencyofvehicleoperation.Astrongbodyofevidence,however,supportstheconclusionthatincreasesinhighwaycapacitydonot

Statepolicy

HighwayCapacity

Traveltime

VMT


32

measurablyreducecongestioninthelong-run.Thisphenomenonisreferredtoas“inducedtravel”or“inducedtraffic”:theincreaseincapacityineffectreducesthe(time)priceofdriving,andwhenthepricegoesdown,consumptiongoesup.Themostrecentandarguablymostrigorousstudyshowsanelasticityofaround1after10years(DurantonandTurner,2011).Inotherwords,a1%increaseinhighwaylanemilesleadstoa1%increaseinVMT.Conversely,studiesshowthatreductionsinhighwaycapacity,inthefewplacestheyhaveoccurred,havenotresultedinanincreaseincongestion,suggestingthatVMTeitherdisperseswidelyordecreasesoverall,thoughtheseeffectshavenotbeenquantified.EstimatingincreasesinVMTresultingfromincreasesinhighwaycapacitywouldberelativelystraightforward(Table7).Itisimportanttonotethattransportationsystemsmanagement(TSM)strategies,suchaseco-drivingprograms,incidence-clearanceprograms,roundabouts,andvariousothersystemsoperationsapproaches22alsohavethepotentialtoincreasetheeffectivecapacityofthehighwaysystem.Tothedegreethattheyreducetraveltimes,theymayinduceadditionalvehicletravelthatcouldoffsetwhateverimprovementsinfuelefficiencyorreductionsinGHGemissionstheyproduce.TheVMT-inducingpotentialofthesestrategieshasnotbeenrigorouslyassessed.StrategyExtent:ImpactofStatePolicyonHighwayCapacityOvernearlyacentury,theStatehasbuiltahighwaysystemthatnowtotalsnearly25,000lane-milesofInterstates,freeways,andexpressways.23In2014alone,theCaliforniaTransportationCommissionprogrammed$2.2billioninprojectsfortheState’shighwaysystemforatwo-yearperiod.24TheRegionalTransportationPlansadoptedbytheMPOstogetherwiththeStateTransportationPlanoutlinecontinuedexpansionstothehighwaysystem,drawingonfederal,state,andlocalfundingsources,despiteagrowingshareoftheavailablefundinggoingtowardsmaintenanceoftheexistingsystem.Theprojectslistedintheseplanscouldbecompiledtoprojectthepercentageincreaseinhighwaycapacityoveraspecifiedperiod.Animportantcaveatisthatproposedprojectsareoftendelayed,sometimesbydecades,asprioritieschangeorbecauseoflegalchallengestosuchprojects,usuallyasapartoftheenvironmentalreviewprocess.StatePolicyConsiderationsforHighwayCapacityAstheowner-operatorofthehighwaysystem,theStatehasdirectcontroloverprojectsthatexpandorreduceitscapacity.AlthoughcountysalestaxmeasuresnowaccountforasignificantshareofhighwayspendingintheState,CaltransandtheCaliforniaTransportation22SeetheARBResearchBriefsonEcoDriving,TrafficIncidenceClearance,Roundabouts,andTrafficOperations,availableat:https://arb.ca.gov/cc/sb375/policies/policies.htm23HighwayStatistics2014.Tablehm60.Available:https://www.fhwa.dot.gov/policyinformation/statistics/2014/24http://www.catc.ca.gov/programs/STIP/2016_STIP/Rev_Fund_Estimate_Jan_16.pdf

33

Commissionmustapprovetheseprojects.Undercurrentpractices,theVMT-inducingpotentialoftheseprojectsisnotgenerallyaccountedforinthedecision-makingprocess.SuchanalysescouldverywellshowthatstateinvestmentsinhighwaycapacityareatoddswithstategoalsforreducingGHGemissions.TheStatecouldusetheCaliforniaTransportationPlan,oranotherplatform,toestablishnewpoliciesthatlimitcapacityexpansion,e.g.throughperformancecriteriaforstatefundingthattakeVMTincreasesintoaccount.Thecurrentplancontinuestofocusoncapacityexpansionasimportantforaddressingcongestion,thoughitacknowledgesthatsuchinvestmentsalonewillnotsolvethecongestionproblem.25Astate-level“fix-it-first”policywouldensurethatmaintenanceneedsaremetbeforefundingisapprovedforprojectsthatexpandcapacity.NewguidelinesonanalyzingtheenvironmentalimpactsofproposedhighwayprojectscouldensurethatpotentialVMTincreasesareadequatelyassessed.26WhileevidencesuggeststhatstateinterventiontoincreasehighwaycapacityishighlylikelytoyieldincreasesinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table7presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation25http://www.dot.ca.gov/hq/tpp/californiatransportationplan2040/index.shtml26http://www.dot.ca.gov/ser/cumulative_guidance/ceqa_guidelines.htm

34

Table7.SuggestedStepsforCalculatingVMTImpactsofHighwayCapacityExpansionStep Assumptionsor



1.Measurecurrenthighwaylanemilesstatewide

Caltransdata Validity=5(excellent)

2.Measureincreaseshighwaycapacityaspercentageofcurrentcapacitystatewide

CompileplannedhighwaycapacityexpansionfromstateandMPOplans

Validity=4(good)TimingoffuturehighwayprojectsbeyondthosecurrentlyprogrammedinaTransportationImprovementProgramisuncertain.Proposedprojectscanbeaddedordroppedwhenplansareupdated.

DevelopGISdatabaseofexistinghighways,fundedhighwayexpansionprojects,andproposedbutunfundedhighwayexpansionprojects

3.UseanelasticityofVMTwithrespecttohighwaycapacitytocalculatepercentageincreaseinVMT

UsecapacityelasticityfromARBcapacitybrief

Validity=4(good)Evidenceisconsistent

4.ApplypredictedpercentageincreaseinVMTtoabase-yearmeasureofannualstatewideVMTtoestimateincreaseintotalannualVMT

UseVMTmeasurefromCaltrans

Validity=5(excellent)

35

4.TransportationDemandManagementProgramsTransportationdemandmanagementprogramsencompassavarietyofstrategies,includingemployer-basedtripreduction(EBTR)programs,telecommutingprograms,andvoluntarytravelbehaviorchangeprograms.Car-sharingservicesmightalsoplayaroleinmanagingdemand.Whiletheliteratureprovidesstrongevidenceontheeffectsofparticipationintheseprogramsontravelbehavior,itprovideslimitedinsightsintofactorsaffectingtheextenttowhichindividualschoosetoparticipateintheseprograms.4.1Employer-BasedTripReductionProgramsStrategyEffect:ImpactofEBTRProgramsonIndividualorHouseholdVMTEmployer-basedtripreductionprograms,alsoknownascommute-tripreductionprograms,usevariousapproachestoreducesingle-occupantcartraveltowork.Employersmayprovideservicesthatpromotecarpooling,suchascarpoolmatchingservices,preferentialparkingforcarpoolers,subsidizedvanpools,orguaranteedrideshomeforcarpoolers.Someprogramsincludefinancialincentivesforparticipants.Employerssometimesprovideworksitefacilitiesforemployeeswhocommutebyactivetravelmodes.Telecommutingprogramsandalternativeworkschedulesareoftenofferedaswell.Availablestudies,assummarizedintheARBresearchbrief,suggestthatcommuteVMTdeclinesby4%to6%onaverageforemployeesatworksitesparticipatinginEBTRprograms,includingemployeeswhoswitchfromdrive-alonetoothermodesandthosewhodon’t.Reductionsarelikelytobehigherwhenprogramsofferabroadarrayofassistanceandincentivesandatsiteswithhighlevelsoftransitaccess.StrategyExtent:ImpactofStatePoliciesonEBTRProgramsEBTRprogramsareimplementedvoluntarilyorasarequirementoflocal,regional,orstatepolicy.Forexample,SouthernCalifornia’sRegulationXV,implementedin1988,requiredemployerswithworksitesofmorethan100employeestodevelopemployeetripreductionplans.In1995,Statelegislationprohibitedairdistrictsorotherpublicagenciesfrommandatingemployertripreductionprogramsunlesssuchmandatesarerequiredbyfederallaw.ButtheStateallowedtheSanJoaquinValleyAirDistricttoadoptacommute-tripreduction

Statepolicy

Pro-grams

Partici-pation

VMT


Localpolicy

36

programin2009,andtheBayAreaAirQualityManagementDistrictadoptedaprogramin2013.SeveralSiliconValleycitieshavecappedsingle-occupancyautotripsaspartofentitlementsfornewtechcompanycampusexpansions.TheextenttowhichEBTRprogramsareimplementedinthefuturedependsonrequirementsforsuchprogramsasestablishedbystateorlocalpolicy.Projectingthestate-wideVMTreductionpotentialofsuchprogramsrequiresanassumptionabouttheserequirements,forexample,thattheywouldapplytoallworksiteswith100ormoreemployees.ThestrategyeffectwouldapplyonlytocommuteVMTforemployeesattheworksiteswithEBTRprogramsratherthantoallcommuteVMT.StatewidereductionsinVMTcouldbeprojectedasoutlinedinTable8.PolicyConsiderationsforEBTRProgramsTheavailableevidenceshowsastrongconnectionbetweenemployer-basedtripreductionprogramsandreductionsincommuteVMT.ThestatewideimpactonVMTofstatepoliciesthatrequireorencouragetheadoptionofEBTRprogramsdependsonthetotalnumberofemployeesatworksitesthatadoptsuchprograms.ThisstrategyshowsstrongpotentialforreducingVMTdependingontheaggressivenessofthestatepolicy.CaliforniacouldadoptanEBTRprogramrequirementmodeledonWashingtonState’s,whichrequiresemployerswith100ormoreemployeesin9of39countiestoadopttrip-reductionprograms.Suchprogramsaretraditionallyimplementedinmetroareaswithhighlevelsofcongestion,butprogramslikevanpoolingandtelecommutingcouldworkinruralareaswithlongcommutedistances.Whileevidencesuggeststhatstateinterventiontoincreaseemployer-basedtripreductionprogramsishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table8presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.

37

Table8.SuggestedStepsforProjectingVMTImpactsofEmployer-BasedTripReductionProgramsStep Assumptions

orDataNeeded



1.UseeffectsizeforworksitestoestimatepercentagedecreaseincommuteVMTforparticipatingworksites

UseeffectsizefromARBEBTRbrief

Validity=3(fair)Elasticitieswillvarybyprogramandcontext

ConductstudiesoftheimpactsofEBTRprogramsofdifferenttypesandcontexts.

2.EstimatethenumberofemployeesatworksitesofthesizespecifiedintheEBTRpolicybymetroarea

DataiscollectedbyCAFranchiseTaxBoard

Validity=5(excellent)

3.UsetheaveragecommutedistancebymetroareatoestimatetheannualcommuteVMTforemployeesatworksitesrequiredtoadoptEBTRprogramsbymetroarea

UsecommuteVMTestimatesfromMPOsand/orCaltrans

Validity=4(good)AmericanCommunitySurveyandCHTSprovidedataoncommuteVMT

4.ApplypredictedpercentagedecreaseincommuteVMTtoestimatedannualcommuteVMTforEBTRworksitestoestimatedecreaseintotalannualcommuteVMTbymetroarea

Calculation

4.2TelecommutingProgramsStrategyEffect:ImpactofTelecommutingProgramsonIndividualVMTTelecommutingisthepracticeofworkingfromhomebyemployeeswhohavearegularworkplace.Telecommutingmaybeencouragedasapartofanemployer-basedtripreductionprogram(seeSection4.1)orasastand-aloneprogram.TheavailableresearchshowsstrongevidencethattelecommutingreducesVMT.AssummarizedintheARBTelecommutingresearchbrief,reductionsincommuteVMTmaybeashighas90%ontelecommutingdays,andpersonalVMTmaydeclinebyroughly55to75%ontelecommutingdays.AnnualVMTreductionsfortelecommutersdependonhowfrequentlytheseworkerstelecommute.Availablestudiesshowthattelecommutersaverage1.2to2.5daysperweek.

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ItisimportanttonotethatmostoftheresearchontheVMTimpactsoftelecommutingwasconductedinthe1990s.WiththeadventoftheInternet,wirelessservices,andsmartphones,today’spatternsoftelecommutingmaybequitedifferentthaninthepast,andtheimpactsondrivingmaybemoreorlessthanpreviously.Anecdotally,itappearsthatworkisincreasinglydoneinplacesotherthantheofficeorhome,theVMTimplicationsofwhichareuncertain.StrategyExtent:ImpactofStatePolicyonTelecommutingProgramsStateandlocalrequirementsforemployer-basedtripreductionprogramsmayencouragetheadoptionoftelecommutingprograms.TheStatemightalsoencourageemployerstoadopttelecommutingprogramsthroughtaxincentivesandotherpolicies.Projectionsfromthe1990sastotheshareofworkerswhowouldbetelecommutingbynowhavenotpannedout,thoughtelecommutinglevelsarenotinsignificant.Measuringtheextentoftelecommutingischallenging,givenincreasingflexibilityinworksitesandworkhours.StatewidereductionsinVMTcouldbeprojectedasoutlinedinTable9.PolicyConsiderationsforTelecommutingProgramsTheavailableevidenceshowsastrongconnectionbetweentelecommutingprogramsandreductionsinVMT.ThestatewideimpactonVMTofstatepoliciesthatrequireorencouragetheadoptionoftelecommutingprogramsdependsonthetotalnumberofemployeeswhochoosetotelecommuteandhowfrequentlytheytelecommute.ThisstrategyshowsstrongpotentialforreducingVMTdependingonemployeedemandfortelecommuting.Californiacouldencouragetelecommutingbyadoptingarequirementforemployer-basedtripreductionprogramsthatincludeatelecommutingprogram(seeSection4.1).Suchprogramsaretraditionallyimplementedinmetroareaswithhighlevelsofcongestion,buttelecommutingprogramscouldworkinruralareaswithlongcommutedistances.WhileevidencesuggeststhatstateinterventiontoincreasetelecommutingprogramsishighlylikelytoyieldreductionsinVMT,estimatingamoreprecisedegreeofimpactfromstateactions–forthepurposesofmodelingbyARBandotherstoquantifyanticipatedVMTreductionsfromspecificstrategies–wouldrequirefurtheranalysis.Table9presentsanoutlineofsuggestedstepsforgainingmoreprecisionandclarityinthisestimation.

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Table9.SuggestedStepsforProjectingVMTImpactsofEmployer-BasedTripReductionProgramsStep AssumptionsorData



1.UseeffectsizetoestimatepercentagedecreaseinpersonalVMTontelecommutingdays

UseeffectsizefromARBTelecommutingbrief

Validity=3(fair)Availableresearchisdated,andeffectsizemaynowbedifferent

Conductnewstudiesoftelecommutingpatternsandimpacts

2.Estimatetheaveragenumberoftelecommutingdaysperweek

UseaveragetelecommutingdaysfromARBTelecommutingbrief

Validity=3(fair)Availableresearchisdated,andtelecommutingfrequencymaynowbedifferent


3.UsetheaveragedailyVMTforworkersbymetroareatoestimatetheannualcommuteVMTforemployeeswhotelecommutebymetroarea

UseVMTestimatesfromMPOsand/orCaltrans

Validity=4(fair)AmericanCommunitySurveyandCHTSprovidedataoncommuteVMT.Telecommutersmayhavelongercommutersthantheregionalaverage


4.ApplypredictedpercentagedecreaseindailyVMTandaveragenumberoftelecommutingdaystoestimatedecreaseintotalannualVMTforaveragetelecommuterbymetroarea

Calculation

5.MultiplyestimateddecreaseintotalannualVMTfortelecommutersbyestimatednumberoftelecommutersbymetroareatogetdecreaseintotalannualVMTbymetroarea

UsetelecommuterestimatesfromMPOsand/orCaltrans

Validity=4(fair)AmericanCommunitySurveyandCHTSprovidedataonshareofworkerstelecommutingusuallyoronanygivenday,respectively

Developimprovedsurveyquestionstomeasureextentoftelecommutingintravelsurveys

40

ConclusionsTheavailableevidenceshowsthatthestrategiesconsideredinthispaperarelikelytoreduceVMTifpromotedbystatepolicy.TheconnectionbetweenstatepolicyandVMTreductionismoredirectforsomestrategiesthanothers(seeTable10),buttheavailableevidenceinallcasespointstoVMTreductions,evenifprojectionsofthemagnitudeofthestatewideeffectsdependonanumberofassumptions.TheframeworkwehaveoutlinedforgeneratingstatewideprojectionsofVMTreductionsforthesestrategieshelpstoilluminatethesequenceofcausaleventsthatwouldproduceVMTreductionsandhighlightsimportantgapsinknowledgethatincreasetheuncertaintyoftheprojections.Despiteuncertainties,theevidencejustifiesstateactiononthesestrategies.Mostofthestrategiesdiscussedherearecomplementary:VMTreductionsarelikelytobegreaterifstrategiesareadoptedincombination.Forexample,infilldevelopmentcoupledwithinvestmentsintransitserviceandbicycleandpedestrianinfrastructurewillhavemoreofanimpactthaninfilldevelopmentortransportationinvestmentsontheirown.PricingstrategieswillhavemoreimpactonVMT(withlessimpactonhouseholdbudgets)ifgoodalternativestodrivingareavailable.Theoneexceptiontothiscomplementarityruleishighwaycapacity:newhighwaycapacity(whetherfromconstructionofadditionallanesorimplementationoftransportationsystemsmanagementstrategies)islikelytoincreaseVMTthroughthe“inducedtravel”effectandwillatleastpartlyoffsetreductionsinVMTachievedthroughotherstrategies.Thetimeframeofthestrategiesisanotherimportantconsideration.Somepricingstrategiescanbeimplementedquickly,iftheStatehasthepoliticalwilltodoso,withdirectimpactsonthetravelchoicesofCalifornians.Transportationinvestmentsmaybealongertermproposition,requiringaseriesofinvestmentsovermanyyearsbeforetransitorbicyclenetworksareextensiveenoughtoattractsubstantialnumbersofdrivers.Infilldevelopmentisalsoalongertermproposition,asnewdevelopmentrepresentsasmallincrementofalldevelopmentinanyoneyear.ButtheselongertermstrategiesareessentialforprovidingandimprovingalternativestodrivingthatenablemorepainlessVMTreductions;theyalsoproducemanyotherbenefitsforcommunitiesasdiscussedintheARBresearchbriefs(seealsoSallis,etal.2015).WehavealsooutlinedtheneedforimproveddataandadditionalstudiestoreducetheuncertaintyinprojectionsofthestatewidereductionsinVMTthatstatepolicymightproduce.Investmentsindataandresearcharewelljustifiedbythesignificanceofthepoliciesunderconsiderationandtheseriousnessoftheproblemtheywouldaddress.However,theStatedoesnotneedtowaitfornewdataorresearchtoact.Infact,theStateisalreadyactingthroughnumerouspoliciesthatdirectlyandindirectlyinfluenceVMTwhetherthatwastheirpurposeornot.TheexistingevidenceisstrongenoughtopointtheStateintherightdirectiontoachievetheneededreductionsinVMTstartingnowandoverthedecadestocome.

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Table10.SummaryofStatePolicyOptionsStrategyCategory

StatePolicytoVMTLink

EffectonIndividualVMT

PotentialforStatewideImplementationandAdoption–StrategyExtent

Pricing

Mostdirect StrongeffectSolidevidence

Canbeappliedstate-wide(fueltaxes,VMTfees)andintargetedareas(linkpricing,cordonpricing,parkingpricing).Mosteffectivewhereindividualshavegoodalternativestodriving.Strategieshaveequityimplications.Generatesrevenuesthatcanbeinvestedintransportationsystem.

InfillDevelopment

Directandindirect

ModerateeffectSolidevidence

Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingininfillareas.Maydependonchangesinlocallandusepolicy.Mayrequirefinancialincentives.LandusechangesandVMTeffectsaccrueoverthelongterm.

TransportationInvestments

Bike/Ped Directandindirect


Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingwhereinvestmentsaremade.Maydependonchangesinlocalinvestments.Mayrequirefinancialincentives.Mayrequirepackageofstrategies.Manyco-benefits.

Transit Directandindirect


Mostapplicableinmetroareas.Willaffectpopulationslivingandworkingwhereinvestmentsaremade.Maydependonchangesintransitagencyaction.Mayrequirefinancialincentives.Mayrequirepackageofstrategies.Manyco-benefits.

Highways Direct

StronginducedVMTeffectSolidevidence

NewcapacitythatreducestraveltimesleadstoVMTgrowth.Effectisgreatestincongestedareas.OperationalimprovementsthatreducetraveltimescanalsoinduceVMT.

TransportationDemandManagement

Moreindirect ModerateeffectSolidevidence

Mostapplicableinmetroareas.Generallyimplementedbylargeemployersinresponsetostateorlocalrequirementsorfinancialincentives.Someapplicationsappropriateforruralareas.

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Appendix:LinkingScenarioPlanningModelsofInfillDevelopmenttoFine-GrainedDataontheEffectofInfillStrategiesTableA1showsanexamplecalculationoftheeffectsizeofmovingfromthethirdtofourthquintileofregionaljobaccessorfromthefourthtofifthquintileofregionaljobaccessintheLosAngelesregion,asshowninFigure1inthetext.ThedatainTable2showmid-pointsofthegravityvariablequintilefromtherangesthatarereportedinBoarnetetal.(2011).FollowingacrosscolumnsinTable2,movesfromthemid-pointofthethirdquintileofjobaccesstothefourthquintileincreasethegravityjobaccessvariableby38.72percent,basedonthevaluesreportedinBoarnetetal.(2010).Usinganelasticityrangeof-0.13to-0.25fromtheARBbriefs,theresultingchangeinhouseholdVMTis38.72percentmultipliedby-0.13or-0.25,orareductionoffrom5.03to9.68percentinhouseholdvehicletravel.Similarly,movingfromthefourthquintileofjobaccess(e.g.inLakewood,perTableXX)tothetopquintile(e.g.neardowntown)isa102.65percentincreaseinthejobaccessmeasure,whichwhenmultipliedbythelowandhighvaluesfortheelasticityimplyareductioninhouseholdVMTrangingfrom13.34to25.66percent.Theseestimatesboundthe18percentVMTreductionthatweobtainedinthebodyofthereportfromdistancemeasuresratherthangravitymeasures,suggestingthatusingdistancetothemetropolitanareadowntowncanbeagoodapproximationformorecomplexmeasuresofjobaccess.TableA1:ExampleCalculationofEffectofMovesAcrossJobAccessQuintilesonDailyHouseholdVMT fromARBregional

accessibilitybrief elasticityfromARB

brief %changeVMT

Accessquintile(fromBoarnetetal.2010)

mid-pointofgravityvariablerange

%changemid-pointaccessacrossadjacentquintiles

Lowestimate

Highestimate

HHVMTmiles/day(fromBoarnetetal.2010)

Lowestimate

Highestimate

5th 524.75 102.65 -0.13 -0.25 47.81 -13.34% -25.66%4th 258.94 38.72 -0.13 -0.25 47.81 -5.03% -9.68%3rd 186.67 -0.13 -0.25 47.81 Sources:CalculatedfromdatainBoarnetetal.(2011)andARBregionalaccessibilitypolicybrief(https://arb.ca.gov/cc/sb375/policies/regaccess/regional_accessibility_brief120313.pdf.)