  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.
