Tran, CQ, Keyvan-Ekbatani, M, Ngoduy, D orcid.org/0000-0002-0446-5636 et al. (1 more author)
(2022)
Dynamic wireless charging lanes location model in urban networks considering route choices.
Transportation Research Part C: Emerging Technologies, 139.
103652.
ISSN 0968-090X
Abstract
Wireless charging technologies have now made it possible to charge while driving, which offers the opportunity to stimulate the market penetration of electric vehicles. This paper aims to support the system planner in optimally deploying the wireless charging lanes on the network, considering traffic dynamics and congestion under multiple vehicle classes. The overall objective is to maximise network performance while providing insights into traffic propagation patterns over the network. A multi-class dynamic system optimal model is adopted to compute an approximate representation of the dynamic traffic flow. As a result, the problem is formulated as a mixed-integer linear program by integrating the dynamic routing behaviour into the charging location problem. Finally, the proposed framework has been tested on different sized test-bed networks to examine the solution quality and illustrate the model’s efficacy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Transportation Research Part C: Emerging Technologies. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Electric vehicles; Wireless charging lanes; Location model; Bi-level optimisation; Dynamic traffic assignment |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Mar 2022 12:52 |
Last Modified: | 08 Apr 2023 00:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trc.2022.103652 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:184972 |
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Filename: TRC-21-01335R1 Revised manuscript - 9-Feb.pdf
Licence: CC-BY-NC-ND 4.0