Computer Science ›› 2020, Vol. 47 ›› Issue (2): 88-94.doi: 10.11896/jsjkx.190500055

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Verification and Evaluation of Modified Social Force Model Considering Relative Velocity of Pedestrians

ZHONG Zhen-wei,JI Qing-ge   

  1. (School of Data and Computer Science,Sun Yat-sen University,Guangzhou 510006,China)1;
    (Guangdong Key Laboratory of Big Data Analysis and Processing,Guangzhou 510006,China)2
  • Received:2019-05-10 Online:2020-02-15 Published:2020-03-18
  • About author:ZHONG Zhen-wei,born in 1996,postgraduate.His main research interests include Computer graphic,crowd simulation and virtual reality;JI Qing-ge,born in 1966,Ph.D,associate professor,is member of China ComputerFederation (CCF).His main research interests include Computer graphic,crowd simulation,virtual reality and computer vision.
  • Supported by:
    This work was supported by the Natural Science Foundation of Guangdong Province, China (2016A030313288).

Abstract: In the field of crowd simulation,the social force model is a very classic micro-simulation model proposed by Helbing,which can simulate some self-organizing phenomenon.However,there are still some shortcomings in the social force model such as pedestrian oscillation and pedestrian overlapping.Therefore,many scholars have enriched and improved the social force model in terms of parameter setting,force range and algorithm optimization.Gao et al.proposed a modified social force model considering the relative velocity of pedestrians,which is still the basis and important reference for scholars to study the improved social force model and various simulation experiments.Since Gao et al.showed the advantages of their modified social force model through only two experiments,which is a little lack of reliability,and there is no more self-organizing experiments to show that their modified social force model still retains the original social force model’s advantage that can simulate the self-organizing phenomenon,this paper did the confirmatory experiments and evaluation experiments for the modified social force model proposed by Gao et al.Two experiments conducted by Gao et al.were verified by confirmatory experiments,which confirm the advantages of Gao et al.’s modified social force model.Through the experimental results of the evaluation experiments,it is confirmed that the modified social force model of Gao et al.retains the ability to simulate the self-organizing phenomenon.This paper also discovered and analyzed the pedestrian overlap problem of the improved social force model of Gao et al.

Key words: Crowd simulation, Relative velocity, Self-organizing phenomenon, Social force model

CLC Number: 

  • TP391.9
[1]HENDERSON L F.The statistics of crowd fluids[J].Nature,1971,229(5284):381-383.
[2]PRESTES E,IDIART M A P,NEDEL L P.Simulating pedestrian behavior with potential fields[C]∥International Conference on Advances in Computer Graphics.2006:324-335.
[3]BELTAIEF O,HADOUAJ S E,GHEDIRA K.Multi-agent simu-lation model of pedestrians crowd based on psychological theories[C]∥Interantional Conference on Logistics.Hammamet,IEEE,2011:150-156.
[4]WOLFRAM S.Theory and Applications of Cellular Automata.
[M]∥Theory and applications of cellular automata:World Scientific,1986.
[5]TAJIMA Y,NAGATANI T.Scaling behavior of crowd flow outside a hall[J].Physica A,2001,292(1/2/3/4):545-554.
[6]VAN DEN BERG J,LIN M,MANOCHA D.Reciprocal velocity obstacles for real-time multi-agent navigation[C]∥IEEE International Conference on Robotics and Automation,2008(ICRA2008).IEEE,2008:1928-1935.
[7]ONDREJ J,PETTRE J,OLIVIER A H,et al.A synthetic-vision based steering approach for crowd simulation[J].ACM Tran-sactions on Graphics,2010,29(4):1.
[8]HELBING D,MOLNAR P.Social force model for pedestrian dynamics[J].Physical Review E,1995,51(5):4282.
[9]GAO Y,LUH P B,ZHANG H,et al.A modified social force model considering relative velocity of pedestrians[C]∥IEEE International Conference on Automation Science & Engineering.IEEE,2013.
[10]HELBING D,FRAKAS I J,MOLNAR P,et al.Simulating dynamical features of escape panic[J].Nature,2000,407(6803):487-490.
[11]SEYFRIED A,STEFFEN B,LIPPERT T.Basics of modelling the pedestrian flow[J].Physica A,2006,368(1):232-238.
[12]PARISI D R,GILMAN M,MOLDOVAN H.A modification of the social force model can reproduce experimental data of pedes-trian flows in normal conditions[J].Physica A,2009,388(17):3600-3608.
[13]CHEN T,YING Z G,SHEN S F,et al.Evacuation simulation and analysis of the relative velocity under social force model[J].Progress in Natural Science,2006,16(12):1606-1612.
[14]LAKOBA T I,KAUP D J,FINKELSTEIN N M.Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution[J].Simulation,2005,81(5):399-352.
[15]APEL M.Simulation of Pedestrian Flows Based on the Social Force Model Using the Verlet Link Cell Algorithm[D].Poznan:Poznan University of Technology,2004.
[16]JI Q G,HE H,WANG F C.Short-range social force model under density field[J].Computer Science,2015,42(6):12-17.
[17]LI S S,QIAN D L,WANG J Z.An improved social force model considering pedestrians slowing down[J].Journal of Jilin University (Engineering Edition),2012,42(3):623-628.
[18]QUINN M J,METOYER R A,HUNTER-ZAWORSKI K.Pa-rallel implementation of the social forces model[C]∥Proceedings of the Second International Conference in Pedestrian and Evacua-tion Dynamics.London:CMS Press,2003:63-74.
[19]HELBING D,FARKAS I,VICSEK T.Simulation of pedestrian crowds in normal and evacuation situations[J].Pedestrian andEvacuation Dynamics,2002,21:21-58.
[20]LIU B,LIU H,ZHANG H,et al.A social force evacuation model driven by video data[J].Simulation Modelling Practice and Theory,2018,84:190-203.
[21]JI Q G,WANG F C,ZHU T.VPBS:A Velocity-Perception-Based SFM Approach for Crowd Simulation[C]∥International Conference on Virtual Reality & Visualization.IEEE,2017.
[22]YUAN G,TAO C,LUH P B,et al.Simulation of Building Eva-cuation Considering Information Flow[M]∥Traffic and Granular Flow’13.2015.
[23]HAO Y,XU Z,LIU Y,et al.A Graphical Simulator for Mode-ling Complex Crowd Behaviors[C]∥2018 22nd International Conference Information Visualisation (IV).IEEE Computer Society,2018.
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