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Simulating Pedestrians’ Motion in Different Scenarios with Modified Social Force Model

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 12044)

Abstract

A model created by Helbing, Molnar, Farkas and Vicsek [1] in the beginning of 21st century considers each agent in pedestrian movement as separate individual who obeys Newton’s laws. The model has been implemented and simulated by numbers of different authors who proved its reliability through realism of agents’ behaviour. To describe the motion as accurately as possible, many of them modified it by presenting their own approach of used formulas and parameters. In this work, authors consider combination of various model modifications as well as present adequate factors values, which allows to observe correct, consistent simulation of different evacuation scenarios and to track changes of Crowd Pressure in subsequent stages of visualization, depending on used exit design.

Keywords

  • Crowd Pressure
  • Social Force Model
  • Pedestrian dynamics

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  • DOI: 10.1007/978-3-030-43222-5_41
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References

  1. Helbing, D., Farkas, I., Molnar, P., Vicsek, T.: Simulation of pedestrian crowds in normal and evacuation situations, vol. 21, pp. 21–58, January 2002

    Google Scholar 

  2. Helbing, D., Molnar, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51 (1998). https://doi.org/10.1103/PhysRevE.51.4282

  3. Helbing, D., Molnar, P., Farkas, I., Bolay, K.: Self-organizing pedestrian movement. Environ. Plann. B Plann. Design 28, 361–383 (2001). https://doi.org/10.1068/b2697

    CrossRef  Google Scholar 

  4. Kirchner, A., Nishinari, K., Schadschneider, A.: Friction effects and clogging in a cellular automaton model for pedestrian dynamics. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 67, 056122 (2003). https://doi.org/10.1103/PhysRevE.67.056122

    CrossRef  Google Scholar 

  5. Lakoba, T., Kaup, D., Finkelstein, N.: Modifications of the Helbing-Molnár-Farkas-Vicsek social force model for pedestrian evolution. Simulation 81, 339–352 (2005). https://doi.org/10.1177/0037549705052772

    CrossRef  Google Scholar 

  6. Moussaïd, M., Helbing, D., Garnier, S., Johansson, A., Combe, M., Theraulaz, G.: Experimental study of the behavioural mechanisms underlying self-organization in human crowds. Proc. Biol. Sci. R. Soc. 276, 2755–62 (2009). https://doi.org/10.1098/rspb.2009.0405

    CrossRef  Google Scholar 

  7. Moussaïd, M., Helbing, D., Theraulaz, G.: How simple rules determine pedestrian behavior and crowd disasters. Proc. Natl. Acad. Sci. U.S.A. 108, 6884–6888 (2011). https://doi.org/10.1073/pnas.1016507108

    CrossRef  Google Scholar 

  8. Porzycki, J., Wąs, J., Hedayatifar, L., Hassanibesheli, F., Kułakowski, K.: Velocity correlations and spatial dependencies between neighbors in a unidirectional flow of pedestrians. Phys. Rev. E 96, 022307 (2017). https://doi.org/10.1103/PhysRevE.96.022307

    CrossRef  Google Scholar 

  9. Wang, P.: Understanding social-force model in psychological principles of collective behavior. Ph.D. thesis, May 2016

    Google Scholar 

  10. Wąs, J., Lubaś, R., Myśliwiec, W.: Proxemics in discrete simulation of evacuation. In: Sirakoulis, G.C., Bandini, S. (eds.) ACRI 2012. LNCS, vol. 7495, pp. 768–775. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33350-7_80

    CrossRef  Google Scholar 

  11. Weidmann, U.: Transporttechnik der fugänger. Schriftenreihe des Institut für Verkehrsplanung, Transporttechnik, Straen-Und Eisenbahnbau 78, 62–64 (1993)

    Google Scholar 

  12. Yanagisawa, D., et al.: Introduction of frictional and turning function for pedestrian outflow with an obstacle. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 80, 036110 (2009). https://doi.org/10.1103/PhysRevE.80.036110

    CrossRef  Google Scholar 

  13. Yu, W., Johansson, A.: Modeling crowd turbulence by many-particle simulations. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 76, 046105 (2007). https://doi.org/10.1103/PhysRevE.76.046105

    CrossRef  Google Scholar 

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Correspondence to Karolina Tytko , Maria Mamica , Agnieszka Pękala or Jarosław Wąs .

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Tytko, K., Mamica, M., Pękala, A., Wąs, J. (2020). Simulating Pedestrians’ Motion in Different Scenarios with Modified Social Force Model. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2019. Lecture Notes in Computer Science(), vol 12044. Springer, Cham. https://doi.org/10.1007/978-3-030-43222-5_41

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  • DOI: https://doi.org/10.1007/978-3-030-43222-5_41

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