This study presents an agent-based model (ABM) developed to simulate the resilience of a community to hurricane-induced infrastructure disruptions, focusing on the interdependencies between electric power and transportation networks. In this ABM approach, agents represent the components of a system, where interactions within a system shape intra-dependency of a system and interactions among systems shape interdependencies. To study household resilience subject to a hurricane, a library of agents has been created including electric power network, transportation network, wind/flooding hazards, and household agents. The ABM is applied over the household and infrastructure data from a community (Zip code 33147) in Miami-Dade County, Florida. Interdependencies between the two networks are modeled in two ways, (i) representing the role of transportation in fuel delivery to power plants and restoration teams' access, (ii) impact of power outage on transportation network components. Restoring traffic signals quickly is crucial as their outage can slow down traffic and increase the chance of crashes. We simulate three restoration strategies: component based, distance based, and traffic lights based restoration. The model is validated against Hurricane Irma data, showing consistent behavior with varying hazard intensities. Scenario analyses explore the impact of restoration strategies, road accessibility, and wind speed intensities on power restoration. Results demonstrate that a traffic lights based restoration strategy efficiently prioritizes signal recovery without delaying household power restoration time. Restoration of power services will be faster if restoration teams do not need to wait due to inaccessible roads and fuel transportation to power plants is not delayed.

翻译：本研究提出了一种基于智能体的模型（ABM），用于模拟社区在飓风引发基础设施中断时的韧性，重点关注电力网络与交通网络之间的相互依赖关系。在该ABM方法中，智能体代表系统的组成部分，系统内部的相互作用塑造系统内依赖性，而系统间的相互作用则塑造相互依赖性。为研究飓风条件下的家庭韧性，我们构建了一个智能体库，包括电力网络、交通网络、风灾/洪灾危害以及家庭智能体。该ABM应用于佛罗里达州迈阿密-戴德县某社区（邮政编码33147）的家庭及基础设施数据。两个网络之间的相互依赖性通过两种方式建模：（i）交通在燃料输送至发电厂及维修团队通行中的作用；（ii）停电对交通网络组件的影响。快速恢复交通信号灯至关重要，因为其失效会减缓交通并增加事故概率。我们模拟了三种恢复策略：基于组件的恢复、基于距离的恢复及基于交通灯的恢复。模型利用飓风伊尔玛数据进行验证，结果表明在不同灾害强度下模型行为具有一致性。情景分析探讨了恢复策略、道路可达性及风速强度对电力恢复的影响。结果显示，基于交通灯的恢复策略能高效优先恢复信号灯，且不会延迟家庭电力恢复时间。若维修团队无需因道路不通而等待，且燃料运输至发电厂未受延误，则电力服务恢复将更快。