Publication Date:
2019
Description:
〈p〉Publication date: July 2019〈/p〉
〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 72〈/p〉
〈p〉Author(s): Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens〈/p〉
〈div xml:lang="en"〉
〈h5〉Abstract〈/h5〉
〈div〉〈p〉This paper presents a behavioral model of public, 〈em〉revealed〈/em〉 preferences (RP) for 〈em〉various types of electric vehicles (EVs)〈/em〉 while accounting for 〈em〉a latent (green) travel pattern construct〈/em〉 and 〈em〉charging infrastructure characteristics〈/em〉. 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.〈/p〉〈/div〉
〈/div〉
Print ISSN:
1361-9209
Electronic ISSN:
1879-2340
Topics:
Architecture, Civil Engineering, Surveying
,
Energy, Environment Protection, Nuclear Power Engineering
,
Geography
