Modeling the Choice of Plug-in Electric Vehicles in California: A Nested Logit Approach

The plug-in electric vehicles (PEVs) help reduce air pollution and greenhouse gas emissions, as well as save energy compared with conventional vehicles. California leads the nation in the PEV adoptions with its sales accounting for almost half of all new PEVs sold in the U.S. Specific supportive policies may help to explain the high level of PEV adoptions in California. However, empirical evidence of influences of public policies on PEV adoptions is still limited. Additionally, most explanatory analyses infer the associations between PEV adoption and relevant factors by using the choice made by individuals under experimental conditions rather than their actual choices. To fill this gap, based on the data collected from California statewide travel survey, which was additionally enriched by a PEV-based sample, a nested logit model was employed to explore factors associated with choices of vehicle technologies including conventional fuel vehicles, plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Model results show that socio-demographics, such as the number of cars per driver, race, income and education level, and the number of children under 12 years old in a household, heavily affect the choice for PEVs. Higher purchase price is associated with PEVs. One policy pertaining to PEVs, allowing PEVs to drive on high occupancy vehicle (HOV) lanes, emerges to be positively associated with PEV adoptions. This study provides a stronger empirical basis for policy decisions of promoting PEVs by contributing to an improved understanding of potential determinants of PEV ownership.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC80 Standing Committee on Alternative Transportation Fuels and Technologies. Alternate title: Modeling Choice of Plug-in Electric Vehicle Buyers in California: Nested Logit Approach.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Tal, Gil
    • Xing, Yan
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 14p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01626526
  • Record Type: Publication
  • Report/Paper Numbers: 17-02193
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 8 2016 10:48AM