A Spatial Analysis of Commuting Patterns of Electric Vehicle Drivers: The Case of Maryland

A Spatial Analysis of Commuting Patterns of Electric Vehicle Drivers: The Case of Maryland

Amirreza Nickkar (Morgan State University, USA), Hyeon-Shic Shin (Morgan State University, USA), and Z. Andrew Farkas (Morgan State University, USA)
Copyright: © 2020 |Pages: 18
DOI: 10.4018/IJSVST.2020010103
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Abstract

This article explores the possible socio-demographic characteristics and factors that contribute to electric vehicle (EV) owner commuting patterns and travel behavior. The objective of the study is to inform decision makers of EV policies by identifying these influencing attributes. In total, 1,257 EV owners in Maryland completed usable surveys. Researchers employed a set of statistical analysis methods to analyze the data. They constructed a multinomial logistic regression to examine the associations between EV owner characteristics and their commuting patterns and compared the results to the spatial travel patterns of drivers of internal combustion engine vehicles (ICEV) in Maryland. The results of this study showed that socio-demographic factors including age, education, income, household size, the number of vehicles in the house, and political affiliation played a significant role in the commuting behavior and patterns of EV drivers. Moreover, about 60% of EV commuting trips originated from suburban areas, and 30% of all of EV commutes were suburban to suburban.
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Background

Overall, little knowledge is available about EV users and their geographical commuting patterns and commuting behavior, as well as geographic and spatial attributes of their general travel patterns. The authors did not find many studies that were able to determine the spatial analysis of commuting patterns of EV users, not only in the U.S. but also in the world. The importance of knowing the EV travel pattern issues and the value of a spatial analysis of EV users’ commutes are not detailed in past studies.

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