In order to solve the problems of disordered and excess delivery of shared bicycles. This study is endeavored to identify the factors that affect bicycle sharing mobility patterns . On the basis of shared bicycle data from New York City’s Bike Share system, the characteristics of the urban shared bicycle usage and the relationships among the parameters (user type, gender, year of birth, etc.) are examined. A novel multivariate analysis model is adopted to analyze both factorial independent variables and numerical independent variables. The data analysis result is believed to gain a deeper insight into the impact of using shared bicycles on the traffic demand of vehicles along the route in time and space, and it is expected to provide reference for the further development and management of shared bicycles in China.

CICTP