MATSim Model Vienna: Analyzing the Socioeconomic Impacts for Different Fleet Sizes and Pricing Schemes of Shared Autonomous Electric Vehicles

17037 8 93213 2 270118 document 93213 TRBAM-21-03707MATSimModelViennaAnalyzingtheSocioeconomicImpactsforDifferentFleetSizesandPricingSchemesofSharedAutonomousElectricVehicles.pdf application/pdf 3357b9ea72b342278e0d5463d21524fb MD5 3210215 2021-02-16 11:23:02 https://pure.iiasa.ac.at/id/eprint/17037/1/TRBAM-21-03707MATSimModelViennaAnalyzingtheSocioeconomicImpactsforDifferentFleetSizesandPricingSchemesofSharedAutonomousElectricVehicles.pdf 17037 1 1 application/pdf text en public cc_by_nc_4

TRBAM-21-03707MATSimModelViennaAnalyzingtheSocioeconomicImpactsforDifferentFleetSizesandPricingSchemesofSharedAutonomousElectricVehicles.pdf

accepted 93214 2 270125 document 93214 lightbox.jpg image/png 8bbef3a88a4246a96e08a6bdd81caad5 MD5 19314 2021-02-16 11:33:24 https://pure.iiasa.ac.at/id/eprint/17037/2/lightbox.jpg 17037 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/93213 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/93213 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/93213 archive 353 disk0/00/01/70/37 2021-02-16 11:24:36 2021-08-27 17:34:20 2021-02-16 11:24:36 conference_item show 1 Müller J. Straub M. Naqvi A. 8691 0000-0002-0986-6009 Richter G. Peer S. Rudloff C. MATSim Model Vienna: Analyzing the Socioeconomic Impacts for Different Fleet Sizes and Pricing Schemes of Shared Autonomous Electric Vehicles pub ASA EM Shared Autonomous Electric Vehicles (SAEVs) are expected to enter the transportation market in the upcoming decades. In this paper, we describe the preparation of a MATSim model for Vienna in which we add this new service as a new transportation mode. We simulate different pricing schemes for various SAEV fleet sizes and analyze their impacts. Our focus is on the impacts in regards of socioeconomic heterogeneity. One main finding of our paper is that the number of SAEV trips does not necessarily decrease for higher fares. It is instead the average travel time of SAEV rides which decreases if the service gets more expensive. Our simulation results for higher pricing schemes show that many people switch from bike or walk mode to SAEV. Public transport is also highly cannibalized by this new service regardless of the price, whereas SAEVs would always replace no more than 10% of car trips. SAEVs help reduce travel times significantly. People who do not have a car available in their household experience the greatest savings in travel time. A similar high share of SAEV trips is done by people older than 35 years. In regards of gender, our results reveal that women tend to use SAEVs for shorter trips. 2021-01 published 2914 public paper Transportation Research Board 100th Annual Meeting 2021 Washington, D.C. conference FALSE FALSE no info:eu-repo/semantics/conferenceObject