Due to the great diversity and complexity of travel demand, the analysis of spatiotemporal evolution characteristics of travel demand is of a significance to the planning and management of urban traffic system. To investigate the spatiotemporal evolution characteristics of travel demand, this research obtains massive order data from Didi Platform in Haikou, including longitude and latitude of departure and destination point of orders as well as the time stamp. Based on these data, characteristics that affect travel demand from May to October and the main factors are analyzed. A model is established to describe the relationship between travel demand and the service level of public bus in Haikou. The conclusions of this research can contribute to the planning of public transportation network, and provide effective reference TO citizens’ travel choices under special weather conditions.

CICTP