A data-driven travel demand model to predict electric vehicle energy consumption: focusing on the rural demographic in the UK

McKinney, T.R. orcid.org/0000-0001-7982-2274, Ballantyne, E.E.F. orcid.org/0000-0003-4665-0941 and Stone, D.A. orcid.org/0000-0002-5770-3917 (2023) A data-driven travel demand model to predict electric vehicle energy consumption: focusing on the rural demographic in the UK. Transportation Planning and Technology. ISSN 0308-1060

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Keywords: Travel demand model; rural; activity based models; passenger vehicle usage; simulation; electric vehicles
Dates:
  • Accepted: 8 August 2023
  • Published (online): 28 August 2023
  • Published: 28 August 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield)
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 14 Sep 2023 13:47
Last Modified: 14 Sep 2023 13:47
Status: Published online
Publisher: Informa UK Limited
Refereed: Yes
Identification Number: https://doi.org/10.1080/03081060.2023.2248195
Related URLs:

Export

Statistics