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<p>Crowd evacuation simulations provide guidance for emergency response to personnel emergencies in public places. Existing path planning methods fail to account for the impact of crowd panic, thus reducing the crowd evacuation in reality. To address this issue, we propose a panic emotion aware path planning method for crowd evacuation. First, the ResNet-RP (Residual Neural Network - Recognition Panic) model with spatiotemporal similarity constraints accurately identifies individual panic emotions, and calculates the panic level of the crowd based on the degree of individual aggregation. Second, the proportion of panicked people is predicted via the mean-field method on the basis of the panic degree of the crowd. Finally, the predicted proportion of panicked people is introduced into the reward function of the multi-agent deep deterministic policy gradient algorithm (P-MAD) to realize emotion-aware evacuation path planning. The experimental results show that our proposed method can effectively achieve panic emotion awareness and panic avoidance path planning for crowd evacuation.</p>

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Panic emotion aware path planning for crowd evacuation

  • 期刊论文

  • 发表日期：

    2026年3月4日

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  • Baoxu An,
  • Guijuan Zhang,
  • Chuanmiao Zhao,
  • Pingshan Liu,
  • Dianjie Lu

摘要

Crowd evacuation simulations provide guidance for emergency response to personnel emergencies in public places. Existing path planning methods fail to account for the impact of crowd panic, thus reducing the crowd evacuation in reality. To address this issue, we propose a panic emotion aware path planning method for crowd evacuation. First, the ResNet-RP (Residual Neural Network - Recognition Panic) model with spatiotemporal similarity constraints accurately identifies individual panic emotions, and calculates the panic level of the crowd based on the degree of individual aggregation. Second, the proportion of panicked people is predicted via the mean-field method on the basis of the panic degree of the crowd. Finally, the predicted proportion of panicked people is introduced into the reward function of the multi-agent deep deterministic policy gradient algorithm (P-MAD) to realize emotion-aware evacuation path planning. The experimental results show that our proposed method can effectively achieve panic emotion awareness and panic avoidance path planning for crowd evacuation.