Quantitative Evaluation of Passenger Flow at Metro Stations Based on Coarse-to-Fine Analysis

The dense urban metro network plays an important role in urban transportation, and it is becoming increasingly important to improve the operation and management of metro facilities. The monitoring and management of passenger flow is a main concern in metro operation, and the reliable analysis of passenger flow can greatly improve the operational efficiency and safety of a metro station. Therefore, using the long-time in-and-out smart card data of Shenzhen metro stations, this paper proposes a Coarse-to-Fine passenger flow analysis method for the characterization of passenger flow on multiple time scales. This method, which is proposed from a new perspective based on the time series clustering of metro stations, precisely defines the peak travel hours and then extracts features for the evaluation of the crowdedness and disorderliness at each station. Finally, the metro stations are classified into nine levels according to those features. The stations that need urgent attention in terms of their passenger flow, including Shenzhen North Station, Buji, and Grand Theater, are identified for the reference of city managers.