The growing size and cost of vehicular evacuations to evade hazards in recent decades have drawn attention to a need for more comprehensive evacuation planning. Transportation modeling research focused on road network vulnerability and evacuation potential has increased the available knowledge for decision makers. Despite this need and the availability of new methods and tools for assessing evacuations, most work focuses on hypothetical or simplified networks, or relies on pre-determined route assessments. This work estimates multiple demand scenarios and compiles real road network data using GIS, as well as simulates evacuation using open-source agent-based transportation modeling software, MATSim. The contribution of this research is to pinpoint specific areas most important to the overall evacuation process and determine variations in clearance time. This information can then inform deeper assessment by emergency managers and transportation planners who can use their local expertise to determine the most appropriate mitigation for identified segments, with the overall goal of maintaining road operations and minimizing clearance time. Road segments were analyzed using two metrics, priority and criticality, to identify areas of the network that are most congested and those which are most traveled, respectively. The case study presented, simulated an evacuation of Bay Farm Island, a district within Alameda, CA and adjacent portions of Oakland, CA consisting of a 365 km road network made up of 4,155 individual segments. Approximately 1-3% of the evacuation network (by length) was identified for potential mitigation actions. Finally, a mitigation strategy increasing the capacity on these identified segments was modeled with results indicating reductions in clearance times of 11% on average and as high as 31%. These results provide knowledge of areas within an evacuation network that could be mitigated to help community planners improve overall clearance time of their tsunami evacuation zone.
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