Perspicuity of Evacuation Behavior in Communities during Hurricanes using Large-scale Mobility Patterns and Communal Characteristics

2023 57th Annual Conference on Information Sciences and Systems (CISS)(2023)

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摘要
The announcement of evacuation orders during hurricanes is an integral part of an emergency preparedness and response plan, specifically for reducing social and economic distress. Although such orders are generally assumed to be followed in theory, in practice, evacuation rates in response to an evacuation order vary widely among communities. The purpose of this study is to examine how socioeconomic and demographic factors affect the evacuation decisions of communities in response to government-issued evacuation orders. Particularly, we harness passively collected high-fidelity mobility data in conjunction with the community characteristics to analyze the disparate evacuation pattern of 2, 617 census block groups (CBGs) in Florida during Hurricane Dorian. Our finding suggests that the lead time of evacuation orders, median age, and a racial minority percentage of CBGs affect the shift in evacuation rate once orders are issued. The study results, along with the comprehensive discussion, contribute to a deeper understanding of the factors that influence evacuation behavior during hurricanes. This can assist emergency management stakeholders in making strategic decisions to maximize community response to evacuation orders.
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community behavior,evacuation orders,mobility,big data,machine learning,hurricane Dorian
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