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A grouping method based on grid density and relationship for crowd evacuation simulation

Author

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  • Li, Yan
  • Liu, Hong
  • Liu, Guang-peng
  • Li, Liang
  • Moore, Philip
  • Hu, Bin

Abstract

Psychological factors affect the movement of people in the competitive or panic mode of evacuation, in which the density of pedestrians is relatively large and the distance among them is small. In this paper, a crowd is divided into groups according to their social relations to simulate the actual movement of crowd evacuation more realistically and increase the attractiveness of the group based on social force model. The force of group attraction is the synthesis of two forces; one is the attraction of the individuals generated by their social relations to gather, and the other is that of the group leader to the individuals within the group to ensure that the individuals follow the leader. The synthetic force determines the trajectory of individuals. The evacuation process is demonstrated using the improved social force model. In the improved social force model, the individuals with close social relations gradually present a closer and coordinated action while following the leader. In this paper, a grouping algorithm is proposed based on grid density and relationship via computer simulation to illustrate the features of the improved social force model. The definition of the parameters involved in the algorithm is given, and the effect of relational value on the grouping is tested. Reasonable numbers of grids and weights are selected. The effectiveness of the algorithm is shown through simulation experiments. A simulation platform is also established using the proposed grouping algorithm and the improved social force model for crowd evacuation simulation.

Suggested Citation

  • Li, Yan & Liu, Hong & Liu, Guang-peng & Li, Liang & Moore, Philip & Hu, Bin, 2017. "A grouping method based on grid density and relationship for crowd evacuation simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 319-336.
    • Handle: RePEc:eee:phsmap:v:473:y:2017:i:c:p:319-336
    DOI: 10.1016/j.physa.2017.01.008
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    References listed on IDEAS

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    1. Henein, Colin M. & White, Tony, 2007. "Macroscopic effects of microscopic forces between agents in crowd models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 694-712.
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    Citations

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    Cited by:

    1. Sun, Yutong & Liu, Hong, 2021. "Crowd evacuation simulation method combining the density field and social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    2. Delcea, Camelia & Cotfas, Liviu-Adrian, 2019. "Increasing awareness in classroom evacuation situations using agent-based modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1400-1418.
    3. Feng, Jiaojiao & Wang, Jinghong & Li, Jia & Li, Jiachen & Xu, Shuangyan & Liu, Juan & Li, Jiapeng & Wang, Yan, 2022. "Study on the law of vertical evacuation behavior during earthquakes considering social relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    4. Zhang, Bosi & Chen, Wenyan & Ma, Xian & Qiu, Ping & Liu, Fupeng, 2020. "Experimental study on pedestrian behavior in a mixed crowd of individuals and groups," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    5. Liu, Weisong & Zhang, Jun & Rasa, Abdul Rahim & Li, Xudong & Ren, Xiangxia & Song, Weiguo, 2023. "Understanding step synchronization in social groups: A novel method to recognize group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    6. Zhiqiang Wang & Jing Huang & Huimin Wang & Jinle Kang & Weiwei Cao, 2020. "Analysis of Flood Evacuation Process in Vulnerable Community with Mutual Aid Mechanism: An Agent-Based Simulation Framework," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    7. Can Liao & Kejun Zhu & Haixiang Guo & Jian Tang, 2019. "Simulation Research on Safe Flow Rate of Bidirectional Crowds Using Bayesian-Nash Equilibrium," Complexity, Hindawi, vol. 2019, pages 1-15, January.
    8. Zhang, Jianxin & Liu, Hong & Li, Yan & Qin, Xin & Wang, Shouna, 2018. "Video-driven group behavior simulation based on social comparison theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 620-634.
    9. Subramanian, Gayathri Harihara & Choubey, Nipun & Verma, Ashish, 2022. "Modelling and simulating serpentine group behaviour in crowds using modified social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).

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