Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12600
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dc.contributor.authorErcan, Tolgaen_US
dc.contributor.authorOnat, Nuri C.en_US
dc.contributor.authorKeya, Nowreenen_US
dc.contributor.authorTatari, Ömeren_US
dc.contributor.authorEluru, Naveenen_US
dc.contributor.authorKüçükvar, Muraten_US
dc.date.accessioned2022-11-17T08:37:53Z-
dc.date.available2022-11-17T08:37:53Z-
dc.date.issued2022-11-
dc.identifier.urihttps://doi.org/10.1016/j.trd.2022.103472-
dc.identifier.urihttps://hdl.handle.net/11147/12600-
dc.descriptionThe 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.abstractHeavy 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.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofTransportation Research Part D: Transport and Environmenten_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectAutonomous electric vehiclesen_US
dc.subjectShared transporten_US
dc.subjectTransportation mode choiceen_US
dc.titleAutonomous electric vehicles can reduce carbon emissions and air pollution in citiesen_US
dc.typeArticleen_US
dc.authorid0000-0001-7074-4628en_US
dc.institutionauthorErcan, Tolgaen_US
dc.departmentİzmir Institute of Technology. Civil Engineeringen_US
dc.identifier.wosWOS:000876896400003en_US
dc.identifier.scopus2-s2.0-85140765827en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.trd.2022.103472-
dc.description.volume112en_US
dc.identifier.wosqualityN/A-
dc.identifier.scopusqualityN/A-
item.fulltextWith Fulltext-
item.grantfulltextembargo_20250101-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
crisitem.author.dept03.03. Department of Civil Engineering-
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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