Where do you live and what do you drive: Built-environmental and spatial effects on vehicle type choice and vehicle use

Na Chen · Gulsah Akar · Steven I. Gordon

26 citations0/0 files storedInternational Journal of Sustainable Transportation

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Transportation Planning and Optimization Urban Transport and Accessibility Transportation and Mobility Innovations

Abstract

The carbon footprint of daily travel for an individual household is based on the types of vehicles that the household owns, their fuel efficiency, and the number of miles traveled (Federal Highway Administration, 2009 Federal Highway Administration. (2009). The “carbon footprint” of daily travel. NHTS Brief, U.S. Department of Transportation. https://nhts.ornl.gov/briefs/Carbon%20Footprint%20of%20Travel.pdf. [Google Scholar]). Therefore, the types and usage of vehicles a household owns are informational to overall sustainable planning. This study develops a multinomial logit model for vehicle type choice and a spatial autoregressive (SAR) model for vehicle use for Ohio households using the most recent Household Travel Survey (HTS) collected in the Cincinnati metropolitan area. The developed vehicle choice model identifies the effects of the built environment characteristics on vehicle type based on vehicle size, controlling for socio-economic attributes. People residing in neighborhoods characterized with higher densities in population, employment, and intersection and with fewer single detached housing are more likely to own smaller vehicles as compared to the ones living in suburban areas. A good transit accessibility would decrease the probability of owning pickup trucks. The SAR model reveals how the vehicle a household owns is used is still slightly positively associated with his/her neighbour’s vehicle use after controlling for the effects of the built environment and socio-economics. The models will enable decision makers to estimate potential changes in vehicle fleet composition under changing built environment scenarios and neighborhood culture in using private vehicles. Although the model results and estimated coefficients may be different for different urban areas, the methodology is transferable to other communities, locally and nationally.

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References

2001Discrete Choice Methods with Simulation 2010Travel and the Built Environment 2000Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles 2000Transportation–land-use interaction: empirical findings in North America, and their implications for modeling 2011Summary of Travel Trends: 2009 National Household Travel Survey 2004What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice 2006A Self Instructing Course in Mode Choice Modeling: Multinomial and Nested Logit Models 2008The impact of demographics, built environment attributes, vehicle characteristics, and gasoline prices on household vehicle holdings and use

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