共享汽车用户及出行时空特征分析

Analysis of Carsharing Users and Demand SpatioTemporal Characteristics

摘要:

共享汽车在中国是一种重要但尚存争议的新型出行方式.因管理部门尚未明确其对道路交通的影响，而无法确定合理的管理导向.针对这一问题，研究基于上海最大的汽车共享公司EVCARD的订单及用户数据，通过描述性统计分析出行总量、需求时空分布，分别用多元线性回归和二项logistic回归分析高频用户和通勤时段出行用户的特征.结果表明，当前EVCARD用车需求和高峰时段出行主要发生在城市外围区域，城市中心区域无通勤特征；高需求用户与通勤时段高频出行者特征并不一致且部分特征相异.因此，上海EVCARD出行不会对城市道路交通拥堵产生显著负面影响.

Abstract:

Carsharing is a new but controversy mobility service in China. The government is unable to determine the appropriate policy direction since the impacts of carsharing on traffic system is not yet clear. However, this problem was addressed based on transaction and user data from the largest carsharing company, EVCARD, in Shanghai. Descriptive statistics was used to analysis carsharingtrip amount and demand spatiotemporal distribution. Multiple linear regression and binary logistic regression were developed to draw characteristics of highfrequency users and users travelling at peak hours, respectively. The results show that most carsharingtrips and peakhour travels occur at the outskirt of city. The travels within the central area of the city have no commuting characteristics. Meanwhile, there are no similar features between highfrequency users and peakhourtrip users, and sometimes, there are even opposite features. Therefore, it is concluded that the carsharingtrip has no significant negative impact on traffic congestion in Shanghai.