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Optimizing underground shelter location and mass pedestrian evacuation in urban community areas: A case study of Shanghai

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  • Jin, Jian Gang
  • Shen, Yifan
  • Hu, Hao
  • Fan, Yiqun
  • Yu, Mingjian

Abstract

In recent years, natural disasters happening over the world pose severe challenges to emergency evacuation systems, especially for highly-populated urban community areas. Underground spaces not systematically utilized yet provide a new development direction for the construction of emergency shelters. Emergency response for mitigating negative impacts of disasters calls for well-designed shelter system and effective management of pedestrian evacuation. In this paper, we study the location selection of underground emergency shelters in urban community areas, along with pedestrian evacuation planning once disaster happens. The aim is to effectively use the existing underground space and sidewalk network to satisfy pedestrian evacuation demand as much as possible. We formulate the problem as a network flow model, and develop a minimum-cost-maximum-flow solution approach. A real-world case study based on the East Nanjing Road community area in central Shanghai is conducted. The results show that sidewalks are the bottleneck of the pedestrian evacuation network due to their limited capacity. Reserving vehicle lanes, implementing one-way evacuation, and opening local small-scale underground shelters, are shown to be effective measures for improving the pedestrian evacuation performance. Overall, the proposed methodology and managerial insights based on the case study in Shanghai show a great potential of employing underground space as shelters for pedestrian evacuation system design in urban community areas.

Suggested Citation

  • Jin, Jian Gang & Shen, Yifan & Hu, Hao & Fan, Yiqun & Yu, Mingjian, 2021. "Optimizing underground shelter location and mass pedestrian evacuation in urban community areas: A case study of Shanghai," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 124-138.
    • Handle: RePEc:eee:transa:v:149:y:2021:i:c:p:124-138
    DOI: 10.1016/j.tra.2021.04.009
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    References listed on IDEAS

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    2. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

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