Modeling Passenger Behavior in Nonpayment Areas at Rail Transit Stations
The nonpayment area at urban transit stations in China usually becomes extremely crowded during peak hours because many passengers queue to buy tickets and pass through the fare gates. How to evaluate the performance of these activities is a critical issue for the design and management of the nonpayment area. This study used microscopic simulation models to investigate passenger behavior in the nonpayment area. The study developed a queue choice model, a passenger movement model, and a path navigation model. Some new ideas were involved. First, the study introduced the concepts of dynamic queue length and dynamic distance between the current passenger and alternative queues into the queue choice model. Second, a new factor, called direction of goal, was proposed to navigate a passenger through the dynamic end of a queue or other goals. This factor was used to construct the transition probability function of a cellular automata model. Finally, the proposed models were calibrated and verified on the basis of a field survey and sensitivity analysis. The results show that the proposed models can capture passenger behaviors in the nonpayment area and perform well for queue estimation.
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Availability:
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Authors:
- Liao, Mingjun
- Liu, Gang
- Publication Date: 2015
Language
- English
Media Info
- Media Type: Print
- Features: Figures; Glossary; Photos; References; Tables;
- Pagination: pp 101–108
- Monograph Title: Public Transportation: Passenger Rail and Terminals, Volume 2
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Serial:
- Transportation Research Record: Journal of the Transportation Research Board
- Issue Number: 2534
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Behavior; Cellular automata; Crowds; Passenger handling; Passenger traffic; Pedestrian flow; Rail transit stations; Traffic queuing
- Geographic Terms: China
- Subject Areas: Planning and Forecasting; Public Transportation; Terminals and Facilities; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01552991
- Record Type: Publication
- ISBN: 9780309369398
- Report/Paper Numbers: 15-3427
- Files: PRP, TRIS, TRB, ATRI
- Created Date: Feb 9 2015 10:44AM