The Impact of the Parking Spot' Surroundings on Charging Decision: A Data-Driven Approach

被引：0
|
作者：
Zhou, Xizhen [1 ]
Ji, Yanjie [1 ,2 ]
Lv, Mengqi [3 ]
机构：
[1] Southeast Univ, Dept Transportat Engn, Nanjing 210096, Peoples R China
[2] Southeast Univ, Natl Demonstrat Ctr Expt Rd & Traff Engn Educ, Nanjing 211189, Peoples R China
[3] Shandong Prov Commun Planning & Design Inst, Jinan, Shandong, Peoples R China
来源：
KSCE JOURNAL OF CIVIL ENGINEERING | 2024年 / 28卷 / 05期
基金：
国家重点研发计划;
关键词：
Charging decision; Trajectory; Electric vehicle; Infrastructure; Mixed logit; ELECTRIC VEHICLES; CHOICE; ANXIETY; TAXI;
D O I：
10.1007/s12205-024-0960-4
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
The charging behavior of drivers serves as a valuable reference for planning and managing charging facilities. This study examines the influence of surrounding environments on charging decisions using real trajectory data from electric vehicles. It considers the built environment, vehicle conditions, and the nearest charging station attributes. The mixed binary logit model was applied to capture the impact of unobserved heterogeneity. The findings indicate that the number of fast chargers in the charging station, parking prices, dwell time, and shopping services significantly influence charging decisions, while leisure services, scenic spots, and mileage since the last charging exhibit opposite effects. Additionally, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, and residential areas. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. Overall, the results offer valuable insights for the planning and management of charging facilities.
引用
收藏
页码：2020 / 2033
页数：14
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