A Time-Based Subway Passengers’ Route Choice Model Using AFC Data

The research on the passengers’ route choices of urban rail transit plays an important role in maintaining the order of urban rail transit network operation. It is the criterion by which the scientific and rational distribution of urban rail transit can be kept. At the same time, it is the foundation of passenger flow assignment. The network of urban rail transit is constructed, and the passenger travel time components in urban rail transit are analyzed. The paper estimates the parameters of the passenger travel time components, and determines the efficient paths. Based on KNN-DPC, a model of passengers’ route choices is built. In this model, the travel time set gotten from the AFC data is clustering analyzed in order to obtain the proportion of each class’s passenger number, and the travel time of each cluster center. Then the fuzzy pattern recognition theory can help to fuzzy match the classes to efficient paths by travel time, and calculates the passenger route choice proportions.