Analysis of Carsharing Users and Demand SpatioTemporal Characteristics

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.