Evacuation Efficiency under Different Departure Time and Destination Choice Preferences

Abstract

This paper presents a microsimulation analysis of interdependent evacuation decisions concerning departure times and destination choices in the hurricane-vulnerable coastal area of Houston, TX. Utilizing cumulative prospect theory (CPT), two predominant behaviors were identified: those of risk-conscious- and time-cautious evacuees. Risk-conscious evacuees predominantly departed early, leading to clustered departures, whereas time-cautious evacuees displayed a more evenly spread departure pattern, presumably avoiding the final stretch of the allocated 6-h window to prevent late arrivals. Time-cautious evacuations emphasized the early departure of residents from high-risk coastal zones such as Galveston Island, steering them toward safer inland refuges. On the other hand, risk-conscious evacuees tended to elect closer destinations to avoid extended travel, experiencing longer travel times, but arriving at destinations earlier owing to their early departures. Interestingly, a hybrid scenario with an equal blend of both behaviors yielded the best traffic outcomes, highlighting the potential advantages of diversified behavior. When comparing CPT with multinomial logit (MNL) outcomes, the MNL model led to a wider dispersion of departure times and exacerbated traffic conditions. A noteworthy observation was the lack of a staggered evacuation strategy in the time-cautious MNL configurations. However, the results were based on simulation data, and further validation will be needed with real-world evacuation data.