Price and Capacity Competition for EV parking with Government Mandates

Brendan Badia, Randall Berry, Ermin Wei

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Increasing focus is being put on expanding the amount of charging infrastructure for electric vehicles (EVs). One tool governments have to induce construction of this infrastructure is through mandates on the number of spots private owners of parking have to convert to include chargers. However, such mandates can impact how parking is priced, the revenue of these firms, parking availability for non-EV cars, and the congestion drivers face while finding parking due to how these private owners may react to it. This paper studies the trade-offs involved in setting a mandate for charging by developing a multi-stage game for the provisioning of parking spots and the subsequent price competition for drivers. Furthermore, we look at different pricing models firms may choose for EV and non-EV drivers and study how this affects the impact of a government mandate.

Original languageEnglish (US)
Title of host publication2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages583-589
Number of pages7
ISBN (Electronic)9781538665961
DOIs
StatePublished - Jul 2 2018
Event56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018 - Monticello, United States
Duration: Oct 2 2018Oct 5 2018

Publication series

Name2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018

Conference

Conference56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018
Country/TerritoryUnited States
CityMonticello
Period10/2/1810/5/18

Funding

This work was supported by Leslie and Mac McQuown and by NSF grant AST-1547328.

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Energy Engineering and Power Technology
  • Control and Optimization

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