Assessment Method for Dynamic Impact of Large Passenger Flow on Urban Rail Transit Network: A Case Study on Chengdu East Railway Station

Document Type

Journal Article

Publication Date

2022

Subject Area

mode - subway/metro, place - asia, place - urban, planning - methods, planning - service level, ridership - demand

Keywords

urban transportation, information systems, spatial data, trip purpose, data visualization, public transportation, rail transit systems, subway, urban, rail, passenger rail transportation, passengers

Abstract

Large-scale activities, holidays, and emergencies often cause a significantly large burst of passenger flow demand in some urban rail transit (URT) stations in a short time, called large passenger flow (LPF). The LPF will propagate through the entire URT network of the city. The impact of the frequent occurrence of LPF on network service levels is crucial and unpredictable. This article describes an analysis of how this LPF propagates through the entire network inspired by how radionuclide imaging is done in clinical medicine. In this study, with LPF of URT as the research object, a propagation model of LPF in URT based on AFC data, train operation data, and URT network topology data was developed, which was inspired by the concept of radionuclide imaging in clinical medicine. In the condition of obtaining the list of passenger route selection ratios, the dynamic propagation state matrix of the LPF in the network is solved. The contribution value matrix of the LPF was proposed to evaluate the impact of the LPF on the URT network. Considering the LPF in Chengdu East Railway Station, China, as an example, the propagation effect of LPF in the Chengdu Metro network was analyzed, and the effectiveness of the proposed model was confirmed.

Rights

Permission to publish the abstract has been given by SAGE, copyright remains with them.

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