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Abstract

Intermediate modes of transport, such as shared vehicles or ride sharing, are starting to increase their market share at the expense of traditional modes of car, public transport, and taxi. In the advent of autonomous vehicles, single occupancy shared vehicles are expected to substitute at least in part private conventional vehicle trips. The objective of this paper is to estimate the impact of shared autonomous vehicles on average trip duration and vehicle-km traveled in a large metropolitan area. A stated preference online survey was designed to gather data on the willingness to use shared autonomous vehicles. Then, commute trips and home-based other trips were generated microscopically for a synthetic population in the greater Munich metropolitan area. Individuals who traveled by auto were selected to switch from a conventional vehicle to a shared autonomous vehicle subject to their willingness to use them. The effect of shared autonomous vehicles on urban mobility was assessed through traffic simulations in MATSim with a varying autonomous taxi fleet size. The results indicated that the total traveled distance increased by up to 8% after autonomous fleets were introduced. Current travel demand can still be satisfied with an acceptable waiting time when 10 conventional vehicles are replaced with 4 shared autonomous vehicles.

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Original document

The different versions of the original document can be found in:

http://downloads.hindawi.com/journals/jat/2018/8969353.xml,
http://dx.doi.org/10.1155/2018/8969353 under the license http://creativecommons.org/licenses/by/4.0
https://doaj.org/toc/0197-6729,
https://doaj.org/toc/2042-3195 under the license http://creativecommons.org/licenses/by/4.0/
http://mediatum.ub.tum.de/doc/1485739/document.pdf,
http://dx.doi.org/10.1155/2018/8969353
http://downloads.hindawi.com/journals/jat/2018/8969353.pdf,
https://trid.trb.org/view/1514070,
https://academic.microsoft.com/#/detail/2804442660
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Published on 01/01/2019

Volume 2019, 2019
DOI: 10.1155/2018/8969353
Licence: Other

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