How the Passengers Flow in Complex Metro Networks?

Abstract

The understanding of passenger flow assignment in metro network is critical for public transit management. However, the route chosen by one passenger is difficult to be directly obtained according to the transaction records only including each trip's tap-in and tap-out time stamp and stations. In this paper, a two-stage framework for calculating passenger flow assignment in complex metro networks is proposed, named PaFA (Passenger Flow Assignment), by using smart card data. First, we design an acceleration search process to obtain all routes for each O-D pair and select the candidate routes under rules. Then, inspired by topic model, we realize similar latent relationships also can be found among O-D pair, candidate routes and passenger's travel time. Along this line, we obtain the distribution of passenger flow in different candidate routes. Finally, a comprehensive evaluation with real-world data is conducted. The results demonstrate the enhanced performance of the proposed method.