Abstract
In disaster situations, special support for the disaster weak are crucial to keep them safe. Common evacuation strategies guide individuals to the shelters closest to their present locations. If evacuees are unevenly distributed across areas, some shelters will not be able to accommodate all arriving evacuees due to the limited capacity of shelters. To tackle this, the existing method decides the destinations for each evacuee considering congestion in disaster areas. However, this method does not consider the disaster weak and can be burdensome for them. Giving that the priority to the disaster weak for shelter decision would be effective to lessen burdens for them, but not all evacuees follow the guidance. When a shelter accepts arriving evacuees unconditionally, some evacuees are rejected, causing a delay in evacuation. If the disaster weak are rejected, the delay will be increased. In this paper, we propose two evacuation shelter decision methods considering the capacity of shelters, the disaster weak, and evacuees’ selfish behavior to realize quick evacuation for the disaster weak: (1) Fixed-rate Reduction Method (FRM), which reduces the assignment number of evacuees less than the capacity at the same percentage to all shelters. (2) Simulation-based Reduction Method (SRM), which reduces the assignment number to shelters that will be crowded based on simulation of an evacuation scenario. Then, these methods decide the destinations for evacuees, with the priority given to the disaster weak. To evaluate the efficiency of the proposed methods, we conducted multi-agent simulation assuming the scenario of evacuation of 30,000 visitors for the Gion Festival including the disaster weak. Through the simulation, we compared our methods with conventional methods including the nearest shelter selection method and the exiting method. As a result, our methods can reduce evacuation time of the disaster weak compared to conventional methods with sufficient cooperation by evacuees.
Funder
Japan Society for the Promotion of Science
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development
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