Estimating potential demand for long-distance electric vehicle travel in Washington State

The authors' objective in this study is to use mobile phone apps data to identify high demand locations for charging electric vehicles (EVs) during long-distance trips. It is important to understand travel behavior of current and future EV owners and their destinations, to provide them with reliable and equitable access to charging network. High costs and low utilization of the charging infrastructure emphasizes the need for thorough study of travel patterns. Origin and destination (OD) of trips can be extracted from apps data and ultimately, the authors can use it to estimate OD matrix of EV trips and predicting their travel patterns. However, using this type of data has its own challenges. In this paper, the authors discuss the issues they faced using raw mobile phone apps data and how they addressed them. Using current travel patterns and EV registration data, the authors estimated potential statewide EV trips if they were not constrained by range and charging availability. The authors then assigned the trips to the network using the shortest path given by Google Maps. To make their results more accessible the authors developed a visualization tool to illustrate potential EV traffic on major road segments and ODs of the traffic flow. The framework can be readily extended to incorporate different levels of EV adoption throughout the state, and to account for EV owners’ choices of whether to use an EV or a conventional vehicle for a long trip.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC80 Standing Committee on Alternative Transportation Fuels and Technologies.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Jabbari, Parastoo
    • Khaloei, Moein
    • MacKenzie, Don
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01698159
  • Record Type: Publication
  • Report/Paper Numbers: 19-05264
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM