Autonomous Electric Vehicles Can Reduce Carbon Emissions and Air Pollution in Cities

dc.contributor.author Ercan, Tolga
dc.contributor.author Onat, Nuri C.
dc.contributor.author Keya, Nowreen
dc.contributor.author Tatari, Ömer
dc.contributor.author Eluru, Naveen
dc.contributor.author Küçükvar, Murat
dc.date.accessioned 2022-11-17T08:37:53Z
dc.date.available 2022-11-17T08:37:53Z
dc.date.issued 2022
dc.description The authors declare that they have no conflict of interest. This work was supported in part by an award to the University of Central Florida, as part of Grant No. DTRT13-G-UTC51 from the U.S. Department of Transportation’s University Transportation Centers Program. en_US
dc.description.abstract Heavy dependence on personal vehicle usage made the transportation sector a major contributor to global climate change and air pollution in cities. In this study, we analyzed autonomous electric vehicles and compared their potential environmental impacts with public transportation options, carpooling, walking, cycling, and various transportation policy applications such as limiting lane-mile increases, and carbon tax. Fractional split multinomial logit and system dynamics modeling approaches are integrated to create a novel hybrid simulation model to process data from 929 metro/micropolitan areas in the U.S. for transportation mode choice behavior. The results show that the adoption of autonomous electric vehicles can reduce greenhouse gas emissions by up to 34% of the total emissions from transportation by 2050. This study has revealed that transportation-related impacts can only be reduced with a paradigm shift in the current practices of today's transportation industry, with disruptive reforms of automation, electrification, and shared transport. en_US
dc.identifier.doi 10.1016/j.trd.2022.103472
dc.identifier.issn 1361-9209
dc.identifier.scopus 2-s2.0-85140765827
dc.identifier.uri https://doi.org/10.1016/j.trd.2022.103472
dc.identifier.uri https://hdl.handle.net/11147/12600
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartof Transportation Research Part D: Transport and Environment en_US
dc.rights info:eu-repo/semantics/embargoedAccess en_US
dc.subject Autonomous electric vehicles en_US
dc.subject Shared transport en_US
dc.subject Transportation mode choice en_US
dc.title Autonomous Electric Vehicles Can Reduce Carbon Emissions and Air Pollution in Cities en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id 0000-0001-7074-4628
gdc.author.id 0000-0001-7074-4628 en_US
gdc.author.institutional Ercan, Tolga
gdc.bip.impulseclass C3
gdc.bip.influenceclass C4
gdc.bip.popularityclass C3
gdc.coar.access embargoed access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Civil Engineering en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.volume 112 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W4303684342
gdc.identifier.wos WOS:000876896400003
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 96.0
gdc.oaire.influence 6.654743E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Shared transport
gdc.oaire.keywords Autonomous electric vehicles
gdc.oaire.keywords Multimodal Transportation
gdc.oaire.keywords System Dynamics
gdc.oaire.keywords Fractional Split Multinomial Logit
gdc.oaire.keywords Transportation Mode Choice
gdc.oaire.popularity 6.975185E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration International
gdc.openalex.fwci 14.19365783
gdc.openalex.normalizedpercentile 0.99
gdc.openalex.toppercent TOP 1%
gdc.opencitations.count 79
gdc.plumx.crossrefcites 119
gdc.plumx.facebookshareslikecount 1
gdc.plumx.mendeley 243
gdc.plumx.newscount 8
gdc.plumx.scopuscites 137
gdc.scopus.citedcount 137
gdc.wos.citedcount 112
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