Passenger Queuing Analysis Method of Security Inspection and Ticket-Checking Area without Archway Metal Detector in Metro Stations

Authors

  • Bin He Department of Rail Transit, Hebei Jiaotong Vocational and Technical College https://orcid.org/0000-0001-9262-7887
  • Yaping Liu Department of Rail Transit, Hebei Jiaotong Vocational and Technical College
  • Xiaocheng Gao Department of Rail Transit, Hebei Jiaotong Vocational and Technical College
  • Fei An Department of Rail Transit, Hebei Jiaotong Vocational and Technical College
  • Xikui Lv School of Traffic and Transportation, Shijiazhuang Tiedao University

DOI:

https://doi.org/10.7307/ptt.v35i5.266

Keywords:

metro station, security inspection area, ticket-checking area, passenger queuing, transit time, passenger flow recursion

Abstract

In order to avoid the congestion in front of the entrance gate units, it is necessary to analyse and optimise the queuing situation at the planning and design stage. The security inspection area and the ticket-checking area were jointly considered, and a queuing congestion analysis method was proposed. Firstly, the research problem was stated. Then, the problem of calculating the number of passengers in each subarea at any time was transformed into the problem of calculating the transit time of each passenger in each subarea. The transit time was divided into basic transit time and additional transit time. Based on the velocity-density relationship, a quantisation method for basic transit time was proposed related to passenger arrival time. The additional transit time was determined by the moment when the passengers left the subarea according to the sequence of arrival of passengers, the number of queuing passengers in the subarea and the congestion of the subarea to be entered. Finally, the queuing situation of passengers in each subarea at any moment was obtained through passenger flow recursion. Examples showed that the proposed method can deal with multiple working conditions and avoid the tedious and time-consuming scene construction process of the microsimulation software.

References

Liao M, Liu G. Modelling passenger behavior in non-payment areas at rail transit stations. Transportation Research Record. 2015;2534:101-108. DOI: 10.3141/2534-13.

Liao M, Liu G, Qiu T. Passenger traffic characteristics of service facilities in rail transit stations of Shanghai. Journal of Transportation Engineering. 2013;139(2):223-229. DOI: 10.1061/(ASCE)TE.1943-5436.0000481.

He B, Gu B. Passenger flow assignment algorithm and software implementation of pedestrian streamline network of urban mass transit station. Journal of Tongji University (Natural Science edition) 2018;46(8):1089-1097. DOI: 10.11908/j.issn.0253-374x.2018.08.012.

Soltani E, Kashi, E. Pedestrian simulation and PLOS analysis in the subway station. Innovative Infrastructure Solutions 7. 2022. DOI: 10.1007/s41062-021-00662-2.

Hoogendoorn SP, Hauser M, Rodrigues N. Applying microscopic pedestrian flow simulation to railway station design evaluation in Lisbon, Portugal. Transportation Research Record. 2004;1878:83-94. DOI: 10.3141/1878-11.

Zhao G, Zhang G, Chen Y, Ping, W. Pedestrian simulation research of subway station in special events. ICCTP 2009: Critical Issues in Transportation Systems Planning, Development, and Management, Proceedings of Ninth International Conference of Chinese Transportation Professionals, ICCTP 2009, 5-9 Aug. 2009, Harbin, China. Reston: American Society of Civil Engineers (ASCE); 2009. p. 1351-1358.

Lei W, et al. Simulation of pedestrian crowds’ evacuation in a huge transit terminal subway station. Physica A: Statistical Mechanics and its Applications. 2012;391(22):5355-5365. DOI: 10.1016/j.physa.2012.06.033.

King D, Srikukenthiran S, Shalaby A. Using simulation to analyze crowd congestion and mitigation at Canadian subway interchanges: Case of Bloor-Yonge Station, Toronto, Ontario. Transportation Research Record. 2014;2417:27-36. DOI: 10.3141/2417-04.

Yang Y, Li J, Zhao Q. Study on passenger flow simulation in urban subway station based on Anylogic. Journal of Software. 2014;9(1):140-146.

Hoy G, Morrow E, Shalaby A. Use of agent-based crowd simulation to investigate the performance of large-scale intermodal facilities: Case study of union station in Toronto, Ontario, Canada. Transportation Research Record. 2016;2540:20-29. DOI: 10.3141/2540-03.

Chen X, et al. A multiagent-based model for pedestrian simulation in subway stations. Simulation Modelling Practice and Theory. 2017;71:134-148. DOI: 10.1016/j.simpat.2016.12.001.

Ni W, et al. Study on optimization of passenger flow at a metro station based on AnyLogic: Case study of Youfangqiao Station of Nanjing metro line 2. Complex System Modelling and Simulation. 2021;1(3):242-252. DOI: 10.23919/CSMS.2021.0009.

Zhu Q. Passenger flow simulation of Xiamafang metro station based on AnyLogic. Highlights in Science, Engineering and Technology. 2023;37:142-156. DOI: 10.54097/hset.v37i.6069.

Kim JY, Kim, YO. Analysis of pedestrian behaviors in subway station using agent-based model: Case of Gangnam Station, Seoul, Korea. Buildings. 2023;13:537. DOI: 10.3390/buildings13020537.

Lin X, Cheng L, Zhang S, Wang Q. Simulating the effects of gate machines on crowd traffic based on the modified social force model. Mathematics. 2023;11:780. DOI: 10.3390/math11030780.

Yamada T, Utaka M. Evaluating ticket gate directional restrictions using simulations of pedestrian flow considering stationary people in a railroad station concourse, Journal of Asian Architecture and Building Engineering. 2023;22(4):2058-2073. DOI: 10.1080/13467581.2022.2153063.

Marin DV, Bachar K, Fabien L. On pedestrian traffic management in railway stations: Simulation needs and model assessment. Transportation Research Procedia. 2019;37:3-10. DOI: 10.1016/j.trpro.2018.12.159.

Guo C, Gu B. Network creation and travel time calculation of pedestrian flow in urban mass transit station. Journal of Tongji University (Natural Science). 2014;42(3):429-434+440. DOI: 10.3969/j.issn.0253-374x.2014.03.016.

Guo C. Network creation and travel time calculation of pedestrian flow in urban rail transit station. PhD thesis. Tongji University; 2016.

Jiang Y, Luo N. Urban rail transit station automatic fare collection configuration research and simulation. ICTE 2013: Safety, Speediness, Intelligence, Low-Carbon, Innovation: Proceedings of the Fourth International Conference on Transportation Engineering, ICTE 2013, 19-20 Oct. 2013, Chengdu, China. Reston: American Society of Civil Engineers (ASCE); 2013. p. 1142-1149.

Xu X, Liu J, Li H, Hu J. Analysis of subway station capacity with the use of queueing theory. Transportation Research Part C: Emerging Technologies. 2014;38(1):28-43. DOI: 10.1016/j.trc.2013.10.010.

Khattak A, Jiang Y, Zhu J, Hu L. A new simulation-optimization approach for the circulation facilities design at urban rail transit station. Archives of Transport. 2017;43(3):69-90. DOI: 10.5604/01.3001.0010.1795.

Zhang X. The study of optimization method to the allocation of automatic ticket checking machine in subway station. MA thesis. Changan University; 2018.

Liu J, He S, Zhang H. Optimization analysis for serial bottleneck system of urban rail transit station. Journal of Computer Applications. 2016;36(1):271-274+286. DOI: 10.11772/j.issn.1001-9081.2016.01.0271.

Tang G. Research on optimization of the allocation of double-check system for urban rail transit. MA thesis. Changan University; 2020.

Cao S. Analysis and modelling on passengers traffic characteristics for urban rail transit. PhD thesis. Beijing Jiaotong University; 2009.

Downloads

Published

30-10-2023

How to Cite

He, B., Liu, Y., Gao, X., An, F., & Lv, X. (2023). Passenger Queuing Analysis Method of Security Inspection and Ticket-Checking Area without Archway Metal Detector in Metro Stations. Promet - Traffic&Transportation, 35(5), 772–785. https://doi.org/10.7307/ptt.v35i5.266

Issue

Section

Articles