Critical Station Identification Based on Passenger Propagation in Urban Mass Transit Network

In order to reflect the real-world operation situation of an urban mass transit network, on the basis of complex network theory, the influence of passenger flow was considered to improve the recognition accuracy of the key stations in the network. By analyzing the sources of passenger flow in each section of the urban mass transit network, passenger propagation models were proposed according to the functional characteristics of passenger transport in ordinary stations and transfer stations. The model parameters were determined statistically by network flow assignment according to historical smart card data. Then, in combination with the degree and betweenness concepts in a complex network, four indexes were proposed to identify the critical stations. Taking the subway network of a certain city as an example, the dynamic passenger flow in the whole network was demonstrated and the critical stations were revealed by using smart card data on the morning peak hours of a certain workday. Research results show that the critical lines are Line 1 and Line 10. Passengers become stranded at the South Railway Station, Xi'erqi Station, and Tiantongyuan Station. The stations exposed to huge passenger flows are more vulnerable to the impacts of large passenger flow. The developed passenger propagation model can display the levels and variations in each section and station where passengers become stranded dynamically. The model can also identify the critical stations by considering the indexes of real passenger flow volume, transport capacity, and network structure. This will provide a theoretical reference for security management of urban mass transit with more efficiency.