Scholarlink

<p>Urban flood disasters have become increasingly frequent due to extreme weather, posing significant risks to pedestrian safety. This study proposes a dynamic simulation framework for pedestrian evacuation by coupling a two-dimensional hydrodynamic model, a cellular automata (CA) model, and an Artificial Bee Colony (ABC) algorithm. The framework integrates flood evolution, pedestrian instability assessment, and path optimisation. Two case studies, a hypothetical shopping centre and a real urban area in Senigallia, Italy, are used for validation. Results show that the model can effectively reproduce pedestrian behaviours such as movement, detouring, and instability under dynamic flood conditions. Evacuation efficiency is strongly affected by exit configuration and crowd density. In the single-exit scenario, evacuation time increases with population and stabilises at about 15.6&#xa0;min when exceeding 500 people. In contrast, the multi-exit scenario maintains a stable evacuation time of approximately 11.5&#xa0;min with improved efficiency. The proportion of unstable pedestrians increases approximately linearly with crowd size. These findings highlight the importance of exit layout and provide support for flood emergency planning and decision-making.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Dynamic Simulation of Pedestrian Evacuation under Flood Conditions Using a Swarm Intelligence Approach

  • 期刊论文

  • 发表日期：

    2026年5月12日

查看全文
  • Bingyao Li,
  • Jingming Hou,
  • Dandan Cai,
  • Fang Liu,
  • Yongyong Ma,
  • Qingshi Zhou

摘要

Urban flood disasters have become increasingly frequent due to extreme weather, posing significant risks to pedestrian safety. This study proposes a dynamic simulation framework for pedestrian evacuation by coupling a two-dimensional hydrodynamic model, a cellular automata (CA) model, and an Artificial Bee Colony (ABC) algorithm. The framework integrates flood evolution, pedestrian instability assessment, and path optimisation. Two case studies, a hypothetical shopping centre and a real urban area in Senigallia, Italy, are used for validation. Results show that the model can effectively reproduce pedestrian behaviours such as movement, detouring, and instability under dynamic flood conditions. Evacuation efficiency is strongly affected by exit configuration and crowd density. In the single-exit scenario, evacuation time increases with population and stabilises at about 15.6 min when exceeding 500 people. In contrast, the multi-exit scenario maintains a stable evacuation time of approximately 11.5 min with improved efficiency. The proportion of unstable pedestrians increases approximately linearly with crowd size. These findings highlight the importance of exit layout and provide support for flood emergency planning and decision-making.