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arXiv 2004.10589physics.soc-phcs.MA
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洪水应急期间行人响应的基于主体的建模:流动行为规则和洪水风险分析的含义

Agent-based modelling of pedestrian responses during flood emergency: mobility behavioural rules and implications for flood risk analysis

Mohammad Shirvani, Georges Kesserwani, Paul Richmond

摘要:

一个基于代理的模型(ABM),用于模拟洪水行人的相互作用,特别是探索更现实的反应疏散行人在洪水期间。反弹道导弹系统内的行人代理人遵循管理其在干旱地区移动的导航规则。当在洪水中时,行人代理被分配额外的行为规则,以考虑他们的稳定性和步行速度,以及他们不同的身高和体重。ABM被应用于复制一个被淹没的购物中心的合成测试案例,考虑越来越复杂的配置模式的疏散行人的行为规则。模拟结果进行了分析的基础上的空间和时间指标告知洪水风险状态的动态变化的洪水淹没行人在一个常用的洪水危险等级(HR)度量,可变的步行速度,由于倾倒和/或滑动的不稳定性。我们的分析显示,随着稳定性和步行速度行为规则变得更加复杂,疏散时间和风险暴露水平显着延长。它还允许识别由于不稳定的行人而导致的更保守的HR阈值,以及一个新的公式来直接估计作为洪水中稳定行人的HR的函数的步行速度状态。提供了软件可访问性的附带详细信息。

英文摘要:

An agent-based model (ABM) for simulating flood-pedestrian interaction is augmented to particularly explore more realistic responses of evacuating pedestrians during flooding. Pedestrian agents within the ABM follow navigation rules of governing their movement in dry areas. When in floodwater, pedestrian agents are assigned extra behavioural rules to factor in their states of stability and walking speed, and their different body height and weight. The ABM is applied to replicate a synthetic test case of a flooded shopping centre, considering increasingly sophisticated configuration modes for the behavioural rules of the evacuating pedestrians. Simulation results are analysed based on spatial and temporal indicators informing on the dynamic variations of flood risk states of flooded pedestrians in terms of a commonly used flood Hazard Rating (HR) metric, variable walking speed, and instability due to toppling and/or sliding. Our analysis reveal significantly prolonged evacuation times and risk exposure levels as stability and walking speed behavioural rules become more sophisticated. It also allows to identify more conservative HR thresholds due to unstable pedestrians, and a new formula to directly estimate walking speed states as function of HR for stable pedestrian in floodwater. Accompanying details for software accessibility are provided.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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