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Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis

Author

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  • Xiaohong Li

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Jianan Zhou

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Feng Chen

    (School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China
    School of Highway, Chang’an University, Xi’an 710061, China)

  • Zan Zhang

    (China Railway Design Corporation, Tianjin 300142, China)

Abstract

In recent years, accidents always happen in confined space such as metro stations because of congestion. Various researchers investigated the patterns of dense crowd behaviors in different scenarios via simulations or experiments and proposed methods for avoiding accidents. In this study, a classic continuum macroscopic model was applied to simulate the crowded pedestrian flow in typical scenarios such as at bottlenecks or with an obstacle. The Lax–Wendroff finite difference scheme and artificial viscosity filtering method were used to discretize the model to identify high-density risk areas. Furthermore, we introduced a contact crowding force test of the interactions among pedestrians at bottlenecks. Results revealed that in the most dangerous area, the individual on the corner position bears the maximum pressure in such scenarios is 90.2 N, and there is an approximate exponential relationship between crowding force and density indicated by our data. The results and findings presented in this paper can facilitate more reasonable and precise simulation models by utilizing crowding force and crowd density and ensure the safety of pedestrians in high-density scenarios.

Suggested Citation

  • Xiaohong Li & Jianan Zhou & Feng Chen & Zan Zhang, 2018. "Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis," Sustainability, MDPI, vol. 10(2), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:2:p:385-:d:129848
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    References listed on IDEAS

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    Cited by:

    1. Li, Xudong & Telesca, Luciano & Lovallo, Michele & Xu, Xuan & Zhang, Jun & Song, Weiguo, 2020. "Spectral and informational analysis of pedestrian contact force in simulated overcrowding conditions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
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    3. Yicheng Yang & Jia Yu & Chenyu Wang & Jiahong Wen, 2022. "Risk Assessment of Crowd-Gathering in Urban Open Public Spaces Supported by Spatio-Temporal Big Data," Sustainability, MDPI, vol. 14(10), pages 1-25, May.

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