Electric vehicle sharing (EVS) is a new low-carbon and environment-friendly mode of public transport based on the sharing economy, which has boomed in Chinese major cities. This study quantifies the impact of individual attributes and travel characteristics on the use of EVS and the willingness of transferring to EVS related travel modes. The research data comes from the household survey results of travel modes in Beijing. The object is the travel chain combined with EVS and rail transit (subway and light rail). With the Pearson coefficient analysis, three models were established by the Mixed Logit: the individual attribute-travel time model, the various factors-usage frequency of EVS model, various factors-transfer willingness model and various factors-future prospect of EVS, to identify the factors of significantly influencing travel time, to quantify the connection of usage frequency of EVS and personal features, to grasp the effects of various explanatory variables on the usage willingness degree of EVS and to make prognostication of the future prospect of EVS in accordance with individual travel characteristics, respectively. The results reveal that the mainly influencing factors on travelers choosing EVS include age, education degree and the absence of cars, travel distance and EVS; and the younger with higher education and medium monthly income but without car and children are the main users of EVS. The results can provide some reference for the daily operation scheduling, service optimization of EVS and the improvement of urban integrated transportation policies.

CICTP