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A novel grid-based mesoscopic model for evacuation dynamics

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  • Shi, Meng
  • Lee, Eric Wai Ming
  • Ma, Yi

Abstract

This study presents a novel grid-based mesoscopic model for evacuation dynamics. In this model, the evacuation space is discretised into larger cells than those used in microscopic models. This approach directly computes the dynamic changes crowd densities in cells over the course of an evacuation. The density flow is driven by the density–speed correlation. The computation is faster than in traditional cellular automata evacuation models which determine density by computing the movements of each pedestrian. To demonstrate the feasibility of this model, we apply it to a series of practical scenarios and conduct a parameter sensitivity study of the effect of changes in time step δ. The simulation results show that within the valid range of δ, changing δ has only a minor impact on the simulation. The model also makes it possible to directly acquire key information such as bottleneck areas from a time-varied dynamic density map, even when a relatively large time step is adopted. We use the commercial software AnyLogic to evaluate the model. The result shows that the mesoscopic model is more efficient than the microscopic model and provides more in-situ details (e.g., pedestrian movement pattern) than the macroscopic models.

Suggested Citation

  • Shi, Meng & Lee, Eric Wai Ming & Ma, Yi, 2018. "A novel grid-based mesoscopic model for evacuation dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 198-210.
    • Handle: RePEc:eee:phsmap:v:497:y:2018:i:c:p:198-210
    DOI: 10.1016/j.physa.2017.12.139
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    References listed on IDEAS

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    Cited by:

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    3. Kunxiang Deng & Qingyong Zhang & Hang Zhang & Peng Xiao & Jiahua Chen, 2022. "Optimal Emergency Evacuation Route Planning Model Based on Fire Prediction Data," Mathematics, MDPI, vol. 10(17), pages 1-23, September.
    4. Liu, Zongtuan & Dong, Gang & Gui, Yunmiao, 2023. "Data-driven emergency evacuation decision for cruise ports under COVID-19: An improved genetic algorithm and simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    5. Ding, Ning & Zhu, Yu & Liu, Xinyan & Dong, Dapeng & Wang, Yang, 2024. "A modified social force model for crowd evacuation considering collision predicting behaviors," Applied Mathematics and Computation, Elsevier, vol. 466(C).

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