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Application of the social force modelling method to evacuation dynamics involving pedestrians with disabilities

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  • Fu, Libi
  • Qin, Huigui
  • He, Yangjian
  • Shi, Yongqian

Abstract

With the development of urban architecture, the growing demand for larger public buildings is becoming challenging for indoor human evacuation under emergencies such as fires. However, the indoor fire evacuation behaviour of heterogeneous crowds when including individuals with disabilities have not been adequately explained. Therefore, this paper aims to study indoor evacuation characteristics of a crowd involving individuals with different types of disabilities (i.e., individuals on crutches and wheelchair users) through a modified social force model. The computation and simulation is performed in a room with an exit in 15 scenarios involving varying number of agents (i.e., 20, 40 and 60). The real-time trajectories and coordinates of agents are obtained. It is found that with an increase in the proportion of pedestrians with disabilities, individual evacuation time of agents increases. This tendency is consistent with results obtained from a previously controlled experiment. The average evacuation speed of agents is negatively impacted by the mixture proportion of individuals with disabilities. The fundamental diagrams acquired from the simulation are similar with the experimental results. Furthermore, it is discovered that the presence of individuals of disabilities in a scenario triggers higher crowd pressure compared to scenarios involving all non-disabled individuals. With an increase in the proportion of pedestrians with disabilities, the crowd danger of agents increases, as also consistent with the experimental findings. These findings are helpful for computer-aided safe evacuation design to decrease heterogeneous crowd congestion during in-building fire evacuation.

Suggested Citation

  • Fu, Libi & Qin, Huigui & He, Yangjian & Shi, Yongqian, 2024. "Application of the social force modelling method to evacuation dynamics involving pedestrians with disabilities," Applied Mathematics and Computation, Elsevier, vol. 460(C).
  • Handle: RePEc:eee:apmaco:v:460:y:2024:i:c:s0096300323004666
    DOI: 10.1016/j.amc.2023.128297
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    References listed on IDEAS

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    1. Fu, Libi & Liu, Yuxing & Shi, Yongqian & Zhao, Yongxiang, 2021. "Dynamics of bidirectional pedestrian flow in a corridor including individuals with disabilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    2. Liu, Xiaodong & Song, Weiguo & Fu, Libi & Fang, Zhiming, 2016. "Experimental study of pedestrian inflow in a room with a separate entrance and exit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 224-238.
    3. Hou, Lei & Liu, Jian-Guo & Pan, Xue & Wang, Bing-Hong, 2014. "A social force evacuation model with the leadership effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 93-99.
    4. Kirchner, Ansgar & Schadschneider, Andreas, 2002. "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 260-276.
    5. Hu, Yanghui & Zhang, Jun & Song, Weiguo, 2019. "Experimental study on the movement strategies of individuals in multidirectional flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    6. Song, Weiguo & Xu, Xuan & Wang, Bing-Hong & Ni, Shunjiang, 2006. "Simulation of evacuation processes using a multi-grid model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 492-500.
    7. Parisi, Daniel R. & Gilman, Marcelo & Moldovan, Herman, 2009. "A modification of the Social Force Model can reproduce experimental data of pedestrian flows in normal conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3600-3608.
    8. Steffen, B. & Seyfried, A., 2010. "Methods for measuring pedestrian density, flow, speed and direction with minimal scatter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1902-1910.
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    Cited by:

    1. Shi, Jiguang & Ding, Ning & Wang, Yang & Zhang, Erhao, 2024. "Individual route choice behavior in evacuation considering avoidance and phototropism: An experimental study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 651(C).
    2. Zhang, Zhao & Fei, Yuhan & Fu, Daocheng, 2024. "A deep reinforcement learning traffic control model for Pedestrian and vehicle evacuation in the parking lot," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 646(C).
    3. Tian, Jiangtao & Li, Xingli & Guo, Qinghua & Kuang, Hua, 2024. "Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).

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