Scipediacontent: Scipediacontent moved page Draft Content 471473053 to Kaddoura et al 2017a

2021-02-02T06:04:33Z

Scipediacontent moved page Draft Content 471473053 to Kaddoura et al 2017a

Scipediacontent: Created page with " == Abstract == Autonomous vehicles (AV) create new opportunities to traffic planners and policy-makers. In the case of shared autonomous vehicles (SAVs), dynamic pricing,..."

2021-02-02T06:04:27Z

Created page with " == Abstract == Autonomous vehicles (AV) create new opportunities to traffic planners and policy-makers. In the case of shared autonomous vehicles (SAVs), dynamic pricing,..."

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== Abstract ==

Autonomous vehicles (AV) create new opportunities to traffic planners and policy-makers. In the case of shared autonomous vehicles (SAVs), dynamic pricing, vehicle routing and dispatch strategies may aim for the maximization of the overall system welfare instead of the operator’s profit. In this study, an existing congestion pricing methodology is applied to the SAV transport mode. On the SAV operator’s side, the routing- and dispatch-relevant cost are extended by the time and link-specific congestion charge. On the users’ side, the congestion costs are added to the fare. Simulation experiments are carried out for Berlin, Germany in order to investigate the impact of SAVs and different pricing setups on the transport system. For the pricing setup, where SAV users only pay the base fare and there is no congestion charge added to the user costs, the model predicts an SAV share of 17.7% within the inner-city Berlin service area. The level of traffic congestion increases, air pollution levels decrease and noise levels slightly increase in the inner-city area. The SAV congestion charge pushes users from SAVs to the walk, bicycle and conventional (driver-controlled) private car (CC) mode. The latter effect is avoided by applying the same congestion charge also to CC users. Overall, this study highlights the importance to control both, the SAV and CC mode in order to improve a city’s transport system.

== Original document ==

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

* [https://depositonce.tu-berlin.de/bitstream/11303/10254/3/kaddoura_etal_2017.pdf https://depositonce.tu-berlin.de/bitstream/11303/10254/3/kaddoura_etal_2017.pdf]

* [https://api.elsevier.com/content/article/PII:S0965856419310456?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S0965856419310456?httpAccept=text/xml],
: [https://api.elsevier.com/content/article/PII:S0965856419310456?httpAccept=text/plain https://api.elsevier.com/content/article/PII:S0965856419310456?httpAccept=text/plain],
: [http://dx.doi.org/10.1016/j.tra.2020.03.032 http://dx.doi.org/10.1016/j.tra.2020.03.032] under the license https://www.elsevier.com/tdm/userlicense/1.0/

* [https://depositonce.tu-berlin.de/bitstream/11303/10254/3/kaddoura_etal_2017.pdf https://depositonce.tu-berlin.de/bitstream/11303/10254/3/kaddoura_etal_2017.pdf],
: [https://www.sciencedirect.com/science/article/abs/pii/S0965856419310456 https://www.sciencedirect.com/science/article/abs/pii/S0965856419310456],
: [https://depositonce.tu-berlin.de/handle/11303/10254 https://depositonce.tu-berlin.de/handle/11303/10254],
: [https://ideas.repec.org/a/eee/transa/v136y2020icp48-63.html https://ideas.repec.org/a/eee/transa/v136y2020icp48-63.html],
: [https://academic.microsoft.com/#/detail/2983480070 https://academic.microsoft.com/#/detail/2983480070]

* [https://depositonce.tu-berlin.de/handle/11303/10254 https://depositonce.tu-berlin.de/handle/11303/10254],
: [http://dx.doi.org/10.14279/depositonce-9216 http://dx.doi.org/10.14279/depositonce-9216]

DOIS: 10.1016/j.tra.2020.03.032 10.14279/depositonce-9216

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Kaddoura et al 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 471473053 to Kaddoura et al 2017a

Scipediacontent: Created page with " == Abstract == Autonomous vehicles (AV) create new opportunities to traffic planners and policy-makers. In the case of shared autonomous vehicles (SAVs), dynamic pricing,..."