Analysis of spatio-temporal distribution characteristics of passenger travel behaviour based on online ride-sharing trajectory data

With the rapid development of information technology, the travel mode of " Internet + Transportation " has brought convenience to residents while causing a series of urban traffic problems. Based on GPS data from Didi Chuxing, this paper relates the residents' travel behaviour to their daily activities, and studies the regularity of the pick-up and drop-off activities of residents from the dimensions of time and space. The results are as follows: Firstly, the daily variation trend of residents' travel is unbalanced. At the same time, the travel volume of residents is at a higher level during night. Secondly, the travel of urban residents is closely related to urban areas and urban functional structures. On the administrative scale, the distribution of residents' travel is concentric, and the farther the distance from the downtown area is, the smaller the number of orders is. On the functional scale, the hot functional areas of residents' travel are related to residents' needs. At last, mastering the distribution of residents' travel hot spots and time will help to understand the residents' travel mode and the current situation of urban traffic, and provide new ideas for solving traffic problems in big cities.