A Study on the Formation and Distribution Mechanisms of the Demand for Shared Electric Vehicles

IF 2.6 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiaohui Sun, Yuling Fu, Feiyan Wang
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Abstract

With the decarbonization of the transportation sector and the diversification of travel demand, the development of shared electric vehicles has become crucial. Based on survey data of travel mode and destination of shared electric vehicles in Beijing, this paper aims to explore the formation and distribution mechanisms of the demand for shared electric vehicles. First of all, a multi-index and multi-cause (MIMIC) model was established to quantify the psychological latent variables that cannot be directly observed and to analyze the mechanisms between individual socio-demographic attributes and latent variables. Secondly, these psychological latent variables were added to mixed logit (ML) models as explanatory variables to form hybrid choice models to explore the travel mode choice behavior and travel destination choice behavior, respectively, when using shared electric vehicles for leisure travel. The results show that potential users of shared electric vehicles are characterized by higher education, employees of enterprises, no car availability and high driving years, and most of them travel for the purpose of connecting to transport hubs. Latent variables such as individual carbon trading, subjective norms, risks and behavioral intentions all affect the demand for shared electric vehicles; in-car time, out-of-car time, travel cost and the number of subway stations have negative impacts on the demand, while mall properties and the number of parking lots have positive impacts on the demand. Furthermore, the use of shared electric vehicles is highly correlated with the use of cars and subways, and part of the travel demand could be transferred to shared electric vehicles by taking certain measures.
共享电动汽车需求形成与分布机制研究
随着交通运输部门的脱碳和出行需求的多样化,共享电动汽车的发展变得至关重要。本文以北京市共享电动车出行方式和目的地调查数据为基础,探讨共享电动车需求的形成和分布机制。首先,建立多指标多原因(MIMIC)模型,量化不能直接观察到的心理潜变量,分析个体社会人口学属性与潜变量之间的作用机制。其次,将这些心理潜变量作为解释变量加入到混合logit (ML)模型中,形成混合选择模型,分别探讨使用共享电动车进行休闲出行时的出行方式选择行为和出行目的地选择行为。结果表明,共享电动车的潜在用户以高学历、企业员工、无车可用性、高驾驶年限为特征,出行目的多为连接交通枢纽。个体碳交易、主观规范、风险、行为意向等潜在变量均影响共享电动汽车需求;车内时间、车外时间、出行成本和地铁站数量对需求有负向影响,而商场属性和停车场数量对需求有正向影响。此外,共享电动车的使用与汽车和地铁的使用高度相关,通过采取一定措施可以将部分出行需求转移到共享电动车上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
World Electric Vehicle Journal
World Electric Vehicle Journal Engineering-Automotive Engineering
CiteScore
4.50
自引率
8.70%
发文量
196
审稿时长
8 weeks
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