Modeling the preference of electric shared mobility drivers in choosing charging stations

Yuntao Guo; Xinwu Qian; Tian LeiShuocheng GuoLei Gong

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Modeling the preference of electric shared mobility drivers in choosing charging stations

机译：Modeling the preference of electric shared mobility drivers in choosing charging stations

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摘要

Electric vehicles for urban shared mobility services are important customers at public charging stations, and understanding their charging behavior is essential to the charging infrastructure planning and charging demand management. This study investigates the influencing factors on drivers' charging station selections for a large-scale and fully electrified taxi fleet with nearly 20,000 unique vehicles and over 35,000 drivers. Drivers' preference for a charging station is approximated by the driving time to it, and quantile regression models are estimated with explanatory variables on personal, charging station configuration, and built-environment factors. Study results suggest that whether a driver serves single- or double-shift, his or her charging habit, the charging station's accessibility to subway stations, and the charging duration are important factors affecting the choice outcomes. Insights derived in this study have important implications for planning charging infrastructure and managing charging demand for city-wide electric vehicles.

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《Transportation research, Part D. Transport and environment》 |2022年第9期|103399.1-103399.19|共19页
作者
Yuntao Guo; Xinwu Qian; Tian LeiShuocheng GuoLei Gong;
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作者单位

Key Laboratory of Road and Traffic Engineering, Ministry of Education, Department of Traffic Engineering, Tongji University, 4800 Cao'an Road, Shanghai 201804, China;

Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, 35487, AL, United States;

College of Urban Transportation and Logistics, Shenzhen Technology University, Shenzhen, 518118, China;

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正文语种英语
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关键词
Electric taxi; Charging behavior; Driver habit; Quantile regression;

Modeling the preference of electric shared mobility drivers in choosing charging stations

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