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Effects of Various Barricades on Human Crowd Movement Flow

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 559))

Abstract

Human crowd movement flow has been studied in various disciplines such as computing science, physics, engineering, urban planning, etc., for many decades. Some studies focused on the management of big crowds in public events whereas others investigated the egress of the crowd in emergency cases. Optimal flows of a human crowd have been a particular interest among many researchers. This paper presents how various physical barricades affect human crowd movement flow using a social force model. Simulation experiments of bidirectional crowd flows were conducted with/without barricades in a straight-line street. The barricades with various lengths and rotations were tested to discover optimal flows of a crowd with various densities of the crowd. The experimental results show that setting up barricades with a particular length and rotation generates a better flow of the crowd compared to the situations without both or either of them. This study can help the management of the crowd in public events by setting up physical barricades strategically to produce optimal flows of a crowd.

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References

  1. Blanke, U., Tröster, G., Franke, T., Lukowicz, P.: Capturing crowd dynamics at large scale events using participatory GPS-localization. In: 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 1–7. IEEE (2014)

    Google Scholar 

  2. Farooq, M.U., Saad, M.N.B., Malik, A.S., Salih Ali, Y., Khan, S.D.: Motion estimation of high density crowd using fluid dynamics. Imaging Sci. J. 68(3), 141–155 (2020)

    Article  Google Scholar 

  3. Granovetter, M.: Threshold models of collective behavior. Am. J. Sociol. 83, 1420–1443 (1978)

    Article  Google Scholar 

  4. Guo, N., Hao, Q.Y., Jiang, R., Hu, M.B., Jia, B.: Uni-and bi-directional pedestrian flow in the view-limited condition: experiments and modeling. Transp. Res. Part C Emerg. Technol. 71, 63–85 (2016)

    Article  Google Scholar 

  5. Helbing, D.: A fluid dynamic model for the movement of pedestrians. arXiv preprint cond-mat/9805213 (1998)

    Google Scholar 

  6. Helbing, D., Buzna, L., Johansson, A., Werner, T.: Self-organized pedestrian crowd dynamics: experiments, simulations, and design solutions. Transp. Sci. 39(1), 1–24 (2005)

    Article  Google Scholar 

  7. Helbing, D., Farkas, I.J., Molnar, P., Vicsek, T.: Simulation of pedestrian crowds in normal and evacuation situations. Pedestr. Evacuation Dyn. 21(2), 21–58 (2002)

    Google Scholar 

  8. Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51(5), 4282 (1995)

    Article  Google Scholar 

  9. Henderson, L.F.: On the fluid mechanics of human crowd motion. Transp. Res. 8(6), 509–515 (1974)

    Article  Google Scholar 

  10. Hoogendoorn, S., Daamen, W.: Self-organization in pedestrian flow. In: Hoogendoorn, S.P., Luding, S., Bovy, P.H.L., Schreckenberg, M., Wolf, D.E. (eds.) Traffic and Granular Flow’03, pp. 373–382. Springer, Heidelberg (2005). https://doi.org/10.1007/3-540-28091-X_36

    Chapter  Google Scholar 

  11. Hughes, R.L.: The flow of human crowds. Annu. Rev. Fluid Mech. 35(1), 169–182 (2003)

    Article  MathSciNet  Google Scholar 

  12. Jager, W., Popping, R., Van de Sande, H.: Clustering and fighting in two-party crowds: Simulating the approach-avoidance conflict. J. Artif. Soc. Soc. Simul. 4(3), 1–18 (2001)

    Google Scholar 

  13. Johansson, A., Kretz, T.: Applied pedestrian modeling. In: Heppenstall, A., Crooks, A., See, L., Batty, M. (eds.) Agent-Based Models of Geographical Systems, pp. 451–462. Springe r, Dordrecht (2012). https://doi.org/10.1007/978-90-481-8927-4_21

    Chapter  Google Scholar 

  14. Le Bon, G.: The Crowd: A Study of the Popular Mind. Fischer, London (1897)

    Google Scholar 

  15. Macal, C.M., North, M.J.: Agent-based modeling and simulation. In: Proceedings of the 2009 Winter Simulation Conference (WSC), pp. 86–98. IEEE (2009)

    Google Scholar 

  16. Manocha, D., Lin, M.C.: Interactive large-scale crowd simulation. In: Arisona, S.M., Aschwanden, G., Halatsch, J., Wonka, P. (eds.) Digital Urban Modeling and Simulation. CCIS, vol. 242, pp. 221–235. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29758-8_12

    Chapter  Google Scholar 

  17. Park, A.J., Ficocelli, R., Patterson, L.D., Spicer, V., Dodich, F., Tsang, H.H.: Modelling crowd dynamics and crowd management strategies. In: 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), pp. 0627–0632. IEEE (2021)

    Google Scholar 

  18. Peng, Y.C., Chou, C.I.: Simulation of pedestrian flow through a “t” intersection: a multi-floor field cellular automata approach. Comput. Phys. Commun. 182(1), 205–208 (2011)

    Article  Google Scholar 

  19. Rozo, K.R., Arellana, J., Santander-Mercado, A., Jubiz-Diaz, M.: Modelling building emergency evacuation plans considering the dynamic behaviour of pedestrians using agent-based simulation. Saf. Sci. 113, 276–284 (2019)

    Article  Google Scholar 

  20. Severiukhina, O., Voloshin, D., Lees, M.H., Karbovskii, V.: The study of the influence of obstacles on crowd dynamics. Procedia Comput. Sci. 108, 215–224 (2017)

    Article  Google Scholar 

  21. Wagner, N., Agrawal, V.: An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster. Expert Syst. Appl. 41(6), 2807–2815 (2014)

    Article  Google Scholar 

  22. Wolfram, S.: Statistical mechanics of cellular automata. Rev. Mod. Phys. 55(3), 601 (1983)

    Article  MathSciNet  Google Scholar 

  23. Yue, H., Guan, H., Zhang, J., Shao, C.: Study on bi-direction pedestrian flow using cellular automata simulation. Phys. A 389(3), 527–539 (2010)

    Article  Google Scholar 

  24. Zacharias, J.: Pedestrian dynamics on narrow pavements in high-density Hong Kong. J. Urban Manag. 10(4), 409–418 (2021)

    Article  Google Scholar 

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Acknowledgment

The authors would like to thank Department of Mathematical Sciences of Trinity Western University for their generous support. The authors would also like to express their gratitude for invaluable insights and feedback from their collaborators.

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Correspondence to Andrew J. Park .

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Park, A.J., Ficocelli, R., Patterson, L., Dodich, F., Spicer, V., Tsang, H.H. (2023). Effects of Various Barricades on Human Crowd Movement Flow. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-031-18461-1_32

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