Passenger transportation hub is important for urban transportation network. However, it’s difficult to get the passenger flow pattern within the hub station using traditional method, such as video detection. Mobile signaling data as a kind of big data provide a solution for the problem. In order to improve the accuracy of extracting travel information, we need to address oscillation sequences and locational uncertainty in mobile signaling data firstly. And then, we can obtain the travel information. Finally, we use the method proposed earlier to extract the trip information and analyze the temporal and spatial distribution in Beijing West Railway Station, and verify the effectiveness of the method. The method proposed in this paper is beneficial for hub managers to understand the characteristics of passengers flow and effectively carry on transportation tasks and so on.

CICTP