Improved social force model based on exit selection for microscopic pedestrian simulation in subway station

Abstract

An improved social force model based on exit selection is proposed to simulate pedestrians’ microscopic behaviors in subway station. The modification lies in considering three factors of spatial distance, occupant density and exit width. In addition, the problem of pedestrians selecting exit frequently is solved as follows: not changing to other exits in the affected area of one exit, using the probability of remaining preceding exit and invoking function of exit selection after several simulation steps. Pedestrians in subway station have some special characteristics, such as explicit destinations, different familiarities with subway station. Finally, Beijing Zoo Subway Station is taken as an example and the feasibility of the model results is verified through the comparison of the actual data and simulation data. The simulation results show that the improved model can depict the microscopic behaviors of pedestrians in subway station.

Keywords

exit selection / social force model / exit width / microscopic behavior / subway station

References

[1] YangG-s, PengL-m, ZhangJ-h, AnY-lin. Simulation of people’s evacuation in tunnel fire [J]. Journal of Central South University of Technology, 2006, 13(3): 307-312

[2] HelbingD, MolnarP. Social force model for pedestrian dynamics [J]. Physical Review E, 1995, 51(5): 4282-4286

[3] HelbingD, FarkasI, VicsekT. Simulating dynamical features of escape panic [J]. Nature, 2000, 407(6803): 487-490

[4] LakobaT I, KaupD J, FinkelsteinN M. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution [J]. Simulation, 2005, 81(5): 339-352

[5] ParisiD R, GilmanM, MoldovanH. A modification of the social force model can reproduce experimental data of pedestrian flows in normal conditions [J]. Physica A: Statistical Mechanics and its Applications, 2009, 388(17): 3600-3608

[6] ZanlungoF, IkedaT, KandaT. Social force model with explicit collision prediction [J]. EPL (Europhysics Letters), 2011, 93(6): 68005

[7] MoussaidM, PerozoN, GarnierS, HelbingD, TheraulazG. The walking behaviour of pedestrian social groups and its impact on crowd dynamics [J]. PLOS ONE, 2010, 5(4): e10047

[8] MaP-j, WangB-hong. The escape of pedestrians with view radius [J]. Physica A: Statistical Mechanics and its Applications, 2013, 392(1): 215-220

[9] YuanW, TanK H. An evacuation model using cellular automata [J]. Physica A: Statistical Mechanics and its Applications, 2007, 384(2): 549-566

[10] GuoR-y, HuangH-jun. Logit-based exit choice model of evacuation in rooms with internal obstacles and multiple exits [J]. Chinese Physics B, 2010, 19(3): 030501

[11] HuangH-j, GuoR-yong. Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and multiple exits [J]. Physical Review E, 2008, 78(2): 021131

[12] LoS M, HuangH C, WangP, YuenK K. A game theory based exit selection model for evacuation [J]. Fire Safety Journal, 2006, 41(5): 364-369

[13] LovreglioR, BorriD, Dell’OlioL, IbeasA. A discrete choice model based on random utilities for exit choice in emergency evacuations [J]. Safety Science, 2014, 62: 418-426

[14] HeliövaaraS, KuusinenJ M, RinneT, KorhonenT, EhtamoH. Pedestrian behavior and exit selection in evacuation of a corridor—An experimental study [J]. Safety Science, 2012, 50(2): 221-227

[15] LengB, WangJ-y, ZhaoX-x, FangJ, XiongZhang. Out flow in a virtual MTR station using a local view floor field model [J]. International Journal of Modern Physics C, 2013, 24(6): 1350037

[16] LeiW-j, LiA-g, GaoR, HaoX-p, DengB-shun. Simulation of pedestrian crowds’ evacuation in a huge transit terminal subway station [J]. Physica A: Statistical Mechanics and its Applications, 2012, 391(22): 5355-5365

[17] LiD-w, ZhangL, SunY-xing. Crowd estimation using image processing based on gray scale edge histogram in subway station of Beijing [C]// Measuring Technology and Mechatronics Automation (ICMTMA), 2013 Fifth International Conference on Mechatronics Automation. Hong Kong. IEEE, 2013415-419

[18] YangX-x, DongH-r, WangQ-l, ChenY, HuX-ming. Guided crowd dynamics via modified social force model [J]. Physica A: Statistical Mechanics and its Applications, 2014, 411: 63-73

[19] HoogendoornS P, BovyP H L. Pedestrian route-choice and activity scheduling theory and models [J]. Transportation Research Part B, 2004, 38(2): 169-190

[20] YangY-d, LiJ, ZhaoQ-xin. Study on passenger flow simulation in urban subway station based on anylogic [J]. Journal of Software, 2014, 9(1): 140-146

[21] ShiZ-w, ChenZ-y, ZhouL, LingJ-wen. A cellular automata model of pedestrian evacuation under multi-exit conditions [J]. Systems Engineering, 2010, 28(9): 51-56

[22] YuenJ K K, LeeE W M. The effect of overtaking behavior on unidirectional pedestrian flow [J]. Safety Science, 2012, 50(8): 1704-1714

[23] HelbingD, FarkasI J, MolnarP, VicsekT. Simulation of pedestrian crowds in normal and evacuation situations [J]. Pedestrian and Evacuation Dynamics, 2002, 21(2): 21-58