Dynamic Household Vehicle Decision Modeling Considering Plug-in Electric Vehicles
- Kouros
Plug-in electric vehicles (PEVs) offer alternatives to traditional vehicles that rely on petroleum-based fuels. While PEV customers can enjoy significant reductions in fuel costs, they incur a larger capital cost than users of traditional vehicles because PEV technology is still maturing. Therefore, consumers adopting PEVs face a trade-off between fuel cost savings with environmental benefits and extra capital cost. It is thus crucial for policy makers and PEV manufacturers to understand people's vehicle decision-making process while considering their socio-economic and travel pattern characteristics as well as the built-environment factors. This paper presents a connected, two-stage, dynamic model of PEV adoption and vehicle-transaction decision-making. Two connected nested logit (NL) models are estimated. The upper level is a two-level NL model to predict choice of vehicle type between four fuel types: gasoline, diesel, hybrid gasoline-electric, and PEV. The lower level is an NL model of vehicle-transaction choice which accommodates four transaction decisions of buy, trade, dispose, and do nothing, while accounting for the log-sum from the vehicle-type choice model, and is estimated using two waves of a panel data set. We find that households with higher levels of income and education are more likely to adopt a PEV. We also found that primarily decision makers take into account the accessibility to charging stations as a critical factor in choosing PEVs.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technologies (VTO)
- DOE Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1542638
- Journal Information:
- Transportation Research Record, Vol. 2672, Issue 49
- Country of Publication:
- United States
- Language:
- English
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