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Understanding the spatiotemporal road network accessibility during ahurricane evacuation, the level of ease of residents in an area in reachingevacuation destination sites through the road network, is a critical componentof emergency management. While many studies have attempted to measure roadaccessibility (either in the scope of evacuation or beyond), few haveconsidered both dynamic evacuation demand and characteristics of a hurricane.This study proposes a methodological framework to achieve this goal. In aninterval of every six hours, the method first estimates the evacuation demandin terms of number of vehicles per household in each county subdivision byconsidering the hurricane's wind radius and track. The closest facilityanalysis is then employed to model evacuees' route choices towards thepredefined evacuation destinations. The potential crowdedness index (PCI), ametric capturing the level of crowdedness of each road segment, is thencomputed by coupling the estimated evacuation demand and route choices.Finally, the road accessibility of each sub-county is measured by calculatingthe reciprocal of the sum of PCI values of corresponding roads connectingevacuees from the sub-county to the designated destinations. The method isapplied to the entire state of Florida during Hurricane Irma in September 2017.Results show that I-75 and I-95 northbound have a high level of congestion, andsub-counties along the northbound I-95 suffer from the worst roadaccessibility. In addition, this research performs a sensitivity analysis forexamining the impacts of different choices of behavioral response curves onaccessibility results.

Estimating Road Network Accessibility during a Hurricane Evacuation: A Case Study of Hurricane Irma in Florida