Reducing Bidirectional Pedestrian Conflict Based on Lane Formation Phenomenon in Subway Corridors
With the rapid increase of the subway passenger volume, the conflict among passengers emerges as a significant issue which affects subway serviceability, especially in the bidirectional flow. The aim of this study is to explore the characteristics of the bidirectional flow of pedestrians in a subway corridor. Pedestrian experiments were conducted to investigate microscopic characteristics of the pedestrian flow. It was found that the microscopic characteristics, including the walking speed and turning angle, were time-dependent and had a generalized trend with time. It was also found that different pedestrian volumes affected the microscopic characteristics. Based on the trend of the microscopic characteristics, the lane formation phenomenon was observed and quantitatively studied, identifying three phases: conflict phase, lane formation phase, and steady lane phase. To alleviate the bidirectional pedestrian conflict, additional pedestrian experiments for the countermeasure of adding separating strap in the corridor, which was based on the lane formation analysis, was conducted. The effectiveness of the countermeasure was demonstrated through a before-and-after comparison. The results showed that adding the separation between the adjacent lanes had the best performance in reducing the conflicts. The results would provide a rationale for subway managers in optimizing the corridor bidirectional pedestrian flow.
Beijing Municipal Transportation Operations Coordination Center. Beijing transport annual report. Volume 1. Beijing: Beijing Municipal Commission of Transport Publishing Service; 2013.
Campanella M, Hoogendoorn SP, Daamen W. Effects of heterogeneity on self-organized pedestrian flows. Transportation Research Record:Journal of the Transportation Research Board. 2009;2124(1): 148-156. doi: 10.3141/2124-14
Johansson A. Constant-net-time headway as a key mechanism behind pedestrian flow dynamics. Physical Review E. 2009;80(2): 1-7. doi: 10.1103/PhysRevE.80.026120
Seyfried A, Passon O, Steffen B, Boltes M, Rupprecht T, Klingsch W. New insights into pedestrian flow through bottlenecks. Transportation Science. 2009;43(3):395-406. doi: 10.1287/trsc.1090.0263
Older SJ. Movement of pedestrians on footways in shopping streets. Traffic engineering & control. 1968;10(4): 160-163.
Helbing D, Farkas IJ, Molnar P, Vicsek T. Simulation of pedestrian crowds in normal and evacuation situations. International Conference on Pedestrian and Evacuation Dynamics; 2001 APR 04-06; Duisburg, Germany. Berlin: Springer; 2002.
Guo RY, Wong SC, Huang HJ, Zhang P, Lam WH. A microscopic pedestrian-simulation model and its application to intersecting flows. Physica A: Statistical Mechanics and its Applications. 2010;389(3): 515-526. doi: 10.1016/j.physa.2009.10.008
Xie S, Wong SC, Lam WH, Chen A. Development of a bidirectional pedestrian stream model with an oblique intersecting angle. Journal of Transportation Engineering. 2013;139(7): 678-685. doi: 10.1061/(ASCE)
Blue V, Adler J. Bi-directional emergent fundamental pedestrian flows from cellular automata microsimulation. Transportation and Traffic Theory. 1999;14: 235-254.
Blue VJ, Adler JL. Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transportation Research Part B: Methodological. 2001;35(3): 293-312. doi: 10.1016/S0191-2615(99)00052-1
Hoogendoorn S, Daamen W. Self-organization in Pedestrian Flow, In: Hoogendoorn S, Luding S, Bovy P, et al. (eds.) Traffic and Granular Flow ’03. Berlin: Springer-Verlag, 2005; p. 373-382.
Zhang J, Song W, Xu X. Experiment and multi-grid modeling of evacuation from a classroom. Physica A: Statistical Mechanics and its Applications. 2008;387(23): 5901-5909. doi: 10.1016/j.physa.2008.06.030
Chertock A, Kurganov A, Polizzi A, Timofeyev I. Pedestrian flow models with slowdown interactions. Mathematical Models and Methods in Applied Sciences. 2014;24(2):249-275. doi: 10.1142/
Hughes RL. The flow of large crowds of pedestrians. 3rd IMACS Symposium on Mathematical Modelling; 2000 FEB 02-04; Vienna, Austria. Amsterdam: Elsevier; 2000.
Hughes RL. A continuum theory for the flow of pedestrians. Transportation Research Part B: Methodological. 2002;36(6): 507-535. doi: 10.1016/S0191-2615(01)00015-7
Helbing D. A stochastic behavioral model and a ‘microscopic’ foundation of evolutionary game theory. Theory and Decision. 1996;40(2): 149-179.
Lam WH, Lee JY, Cheung CY. A study of the bi-directional pedestrian flow characteristics at Hong Kong signalized crosswalk facilities. Transportation. 2002;29(2): 169-192. doi: 10.1023/A:1014226416702
Lam WH, Lee JY, Chan KS, Goh PK. A generalised function for modeling bi-directional flow effects on indoor walkways in Hong Kong. Transportation Research Part A: Policy and Practice. 2003;37(9): 789-810. doi: 10.1016/S0965-8564(03)00058-2
Daamen W, Hoogendoorn SP. Experimental research of pedestrian walking behaviour. 82nd Annual Meeting of the Transportation-Research-Board; 2003 JAN 12-16. Washington, D.C. USA.
Helbing D, Buzna L, Johansson A, Werner T. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions. Transportation Science. 2005;39(1): 1-24. doi: 10.1287/trsc.1040.0108
Kretz T, Grünebohm A, Kaufman M, Mazur F, Schreckenberg M. Experimental study of pedestrian counterflow in a corridor. Journal of Statistical Mechanics: Theory and Experiment. 2006;2006(10): 1-22. doi:
Zhang J, Klingsch W, Schadschneider A, Seyfried A. Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram. Journal of Statistical Mechanics: Theory and Experiment. 2012;P02002(02): 1-20. doi: 10.1088/1742-5468/2012/02/P02002
Golas A, Narain R, Curtis S, Lin MC. Hybrid long-range collision avoidance for crowd simulation. IEEE Transactions on Visualization and Computer Graphics. 2014;20(7): 1022-1034. doi: 10.1109/TVCG.2013.235
Transit Cooperative Research Program. Transit Capacity and Quality of Service Manual. Volume 7. Washington DC: Transportation Research Board of the National Academies Publishing Service; 2003.
Sun L, Luo W, Yao LY, Qiu S, Rong J. A comparative study of funnel shape bottlenecks in subway stations. Transportation Research Part A: Policy & Practice. 2017;98: 14-27.
Sun L, Yang Z, Rong J, Liu XM. Study on the Weaving Behaviour of High Density Bidirectional Pedestrian Flow. Mathematical Problems in Engineering, 2014;2014: 1-9. doi: 10.1155/2014/765659
Stauffer C, Grimson WEL. Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis & Machine Intelligence. 2000;22(8): 747-757. doi: 10.1109/34.868677
Piccoli B, Tosin A. Pedestrian flows in bounded domains with obstacles. Continuum Mechanics and Thermodynamics. 2009;21(2): 85-107. doi: 10.1007/s00161-009-0100-x
Cancho RFI, Solé RV. Least effort and the origins of scaling in human language. Proceedings of the National Academy of Sciences. 2003;100(3): 788-791. doi: 10.1073/pnas.0335980100
Johansson A, Helbing D, Al-Abideen HZ, Al-Bosta S. From crowd dynamics to crowd safety: a video-based analysis. Advances in Complex Systems. 2008;11(04): 497-527. doi: 10.1142/S0219525908001854
Cristiani E, Piccoli B, Tosin A. Multiscale modeling of granular flows with application to crowd dynamics. Multiscale Modeling & Simulation. 2011;9(1): 155-182. doi: 10.1137/100797515
Antonini G, Bierlaire M, Weber M. Discrete choice models of pedestrian walking behaviour. Transportation Research Part B: Methodological. 2006;40(8): 667-687. doi: 10.1016/j.trb.2005.09.006
Teknomo K. Application of microscopic pedestrian simulation model. Transportation Research Part F: Traffic Psychology and Behaviour. 2006;9(1): 15-27.
Sarmady S, Haron F, Talib AZ. A cellular automata model for circular movements of pedestrians during Tawaf. Simulation Modelling Practice and Theory. 2011;19(3): 969-985. doi: 10.1016/j.simpat.2010.12.004
Sano T, Shida K, Tatebe K. An experimental study on pedestrian crossing conflicts by physical index: Study on characteristics of pedestrian crossing flow. Journal of Architecture Planning & Environmental Engineering. 2001;(8): 127-132.
Daamen W, Hoogendoorn S. Calibration of pedestrian simulation model for emergency doors by pedestrian type. Transportation Research Record: Journal of the Transportation Research Board. 2012;2316(1):
-75. doi: 10.3141/2316-08
Weng WG, Shen SF, Yuan HY, Fan WC. A behaviour-based model for pedestrian counter flow. Physica A Statistical Mechanics & Its Applications. 2007;375(2): 668-678. doi: 10.1016/j.physa.2006.09.028
Li MH, Yuan ZZ, Xu Y, Tian JF. Randomness analysis of lane formation in pedestrian counter flow based on improved lattice gas model. Acta Physica Sinica. 2015;64(1): 018903. doi: 10.7498/aps.64.018903
Lee J, Kim T, Chung JH, Kim J. Modeling lane formation in pedestrian counter flow and its effect on capacity. KSCE Journal of Civil Engineering. 2016;20(3): 1099-1108. doi: 10.1007/s12205-016-0741-9
Kretz T, Kaufman M, Schreckenberg M. Counterflow Extension for the FAST-Model. 8th International Conference on Cellular Automata for Research and Industry; 2008 Sep 23-26. Yokohama, Japan.
Alonsomarroquin F, Lozano C, Ramirezgomez A, Busch J. Simulation of counter flow pedestrian dynamics in hallways using spheropolygons. Physical Review E: Statistical Nonlinear & Soft Matter Physics. 2013;90(6): 063305. doi: 10.1103/PhysRevE.90.063305
Xiong T, Zhang P, Wong SC, Shu CW, Zhang MP. A macroscopic approach to the lane formation phenomenon in pedestrian counterflow. Chinese Physics Letters. 2011;28(10): 108901. doi: 10.1088/0256-307X/28/10/108901
Guo W, Wang X, Zheng X. Lane formation in pedestrian counterflows driven by a potential field considering following and avoidance behaviours. Physica A: Statistical Mechanics & Its Applications. 2015;432: 87-101. doi: 10.1016/j.physa.2015.03.020
Nowak S, Schadschneider A. Quantitative analysis of pedestrian counterflow in a cellular automaton model. Physical Review E: Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics. 2012;85(2): 482-510. doi: 10.1103/PhysRevE.85.066128
Helbing D. Traffic Dynamics: New Physical Modeling Concepts. Berlin: Springer-Verlag; 1997.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).