Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

8-2018

Abstract

Cars of the future have been predicted as shared and electric. There has been a rapid growth in electric vehicle (EV) sharing services worldwide in recent years. For EV-sharing platforms to excel, it is essential for them to offer private charging infrastructure for exclusive use that meets the charging demand of their clients. Particularly, they need to plan not only the places to build charging stations, but also the amounts of chargers per station, to maximally satisfy the requirements on global charging coverage and local charging demand. Existing research efforts are either inapplicable for their different problem formulations or are at a coarse granularity. In this paper, we formulate the Electric Vehicle Charger Planning (EVCP) problem especially for EV-sharing. We prove that the EVCP problem is NP-hard, and design an approximation algorithm to solve the problem with a theoretical bound of 1 − 1 e . We also devise some optimization techniques to speed up the solution. Extensive experiments on real-world datasets validate the effectiveness and the efficiency of our proposed solutions.

Keywords

Electric Vehicles, Location Selection, Submodularity

Discipline

Electrical and Computer Engineering | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, London, August 19-23

First Page

1330

Last Page

1338

ISBN

9781450355520

Identifier

10.1145/3219819.3220032

Publisher

ACM

City or Country

London

Additional URL

https://doi.org/10.1145/3219819.3220032

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