Characterizing Passenger Flow for a Transportation Hub Based on Mobile Phone Data

As the vital node of a passenger transportation network, the transportation hub is the connection between multiple travel modes and the important port for the massive passenger flow to enter into or exit from a city area. Transportation operators need to understand the passenger flow pattern for hub management, transportation planning, and so on. However, it is difficult to use traditional methods, such as video detection, to provide such information. With the increasing number of mobile phone users, mobile phone data have shown remarkable potential in detecting the transportation information with high sampling coverage and low cost. This paper utilizes the mobile phone data to characterize the passenger flow of the Hongqiao transportation hub located in Shanghai, China. First, a temporal-spatial clustering method is proposed to identify the passenger active area of the Hongqiao hub in the wireless communication space. Second, a classification process is presented to extract different types of passengers in this transportation hub. Subsequently, the access characteristics of passengers in the city are studied for various time intervals. The results further verify the potential of using mobile phone data to monitor and characterize passenger flow related to the transportation hubs.