Quantitative Modeling of Congestion in Metro Station Based on Passenger Time Perceptions. Issue 5 (May 2020)

• Record Type: Journal Article
• Authors: Teng, Jing; Pan, Weiwei; Zhang, Cen
• Is Part Of: Transportation research record. Volume 2674:Issue 5(2020)
• Page Start: 270
• Page End: 281
• Publication Date: 2020-05
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198120914900
• Languages: English
• ISSNs: 0361-1981

Abstract

In the metro station, passengers' psychological state can be affected by space congestion, slow walking speed, increasing queue length, and other factors, resulting in a time-lapse effect, which can be described as people feeling that they spend more time than the actual. To measure the effect, this paper develops congestion indexes for the walking and queuing areas in metro stations, and designs stated preference (SP) and revealed preference (RP) surveys and scene simulation experiments. Based on the survey and experiment data, we attempt to describe the psychological state and space–time perception of passengers in metro stations and propose quantitative models of congestion indexes at different service levels. Furthermore, on the basis of these models, thresholds of walking distance and waiting time can be calculated for different service levels. The results can provide a reference for real-time passenger flow monitoring and theoretical supports for metro operators to measure passenger flow status and adopt passenger flow management strategies under different conditions. Overall, this study offers promising insights into passenger flow monitoring and management, but some limitations need to be addressed in future work.