skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure

Abstract

This paper presents a behavioral model of public, revealed preferences (RP) for various types of electric vehicles (EVs) while accounting for a latent (green) travel pattern construct and charging infrastructure characteristics. Specifically, a two-level nested logit (NL) model is estimated to explain households' fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households' socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle's principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings revealsmore » that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.« less

Authors:
 [1];  [1];  [2]
  1. Univ. of Illinois, Chicago, IL (United States). Dept. of Civil and Materials Engineering
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V); USDOE
OSTI Identifier:
1559870
Alternate Identifier(s):
OSTI ID: 1637039
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Transportation Research. Part D, Transport and Environment
Additional Journal Information:
Journal Volume: 72; Journal Issue: C; Journal ID: ISSN 1361-9209
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; battery electric vehicle; charging infrastructure; latent travel pattern; plug-in hybrid electric vehicle; revealed preferences

Citation Formats

Nazari, Fatemeh, Mohammadian, Abolfazl, and Stephens, Thomas. Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure. United States: N. p., 2019. Web. doi:10.1016/j.trd.2019.04.010.
Nazari, Fatemeh, Mohammadian, Abolfazl, & Stephens, Thomas. Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure. United States. https://doi.org/10.1016/j.trd.2019.04.010
Nazari, Fatemeh, Mohammadian, Abolfazl, and Stephens, Thomas. Mon . "Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure". United States. https://doi.org/10.1016/j.trd.2019.04.010. https://www.osti.gov/servlets/purl/1559870.
@article{osti_1559870,
title = {Modeling electric vehicle adoption considering a latent travel pattern construct and charging infrastructure},
author = {Nazari, Fatemeh and Mohammadian, Abolfazl and Stephens, Thomas},
abstractNote = {This paper presents a behavioral model of public, revealed preferences (RP) for various types of electric vehicles (EVs) while accounting for a latent (green) travel pattern construct and charging infrastructure characteristics. Specifically, a two-level nested logit (NL) model is estimated to explain households' fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households' socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle's principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings reveals that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.},
doi = {10.1016/j.trd.2019.04.010},
url = {https://www.osti.gov/biblio/1559870}, journal = {Transportation Research. Part D, Transport and Environment},
issn = {1361-9209},
number = C,
volume = 72,
place = {United States},
year = {2019},
month = {7}
}

Journal Article:

Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

Save / Share: