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Journal Article

Citation

Gehlot H, Sadri AM, Ukkusuri SV. Transportation (Amst) 2019; 46(6): 2419-2440.

Copyright

(Copyright © 2019, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s11116-018-9958-4

PMID

unavailable

Abstract

Hurricanes are costly natural disasters periodically faced by households in coastal and to some extent, inland areas. A detailed understanding of evacuation behavior is fundamental to the development of efficient emergency plans. Once a household decides to evacuate, a key behavioral issue is the time at which individuals depart to reach their destination. An accurate estimation of evacuation departure time is useful to predict evacuation demand over time and develop effective evacuation strategies. In addition, the time it takes for evacuees to reach their preferred destinations is important. A holistic understanding of the factors that affect travel time is useful to emergency officials in controlling road traffic and helps in preventing adverse conditions like traffic jams. Past studies suggest that departure time and travel time can be related. Hence, an important question arises whether there is an interdependence between evacuation departure time and travel time? Does departing close to the landfall increases the possibility of traveling short distances? Are people more likely to depart early when destined to longer distances? In this study, we present a model to jointly estimate departure and travel times during hurricane evacuations. Empirical results underscore the importance of accommodating an inter-relationship among these dimensions of evacuation behavior. This paper also attempts to empirically investigate the influence of social ties of individuals on joint estimation of evacuation departure and travel times. Survey data from Hurricane Sandy is used for computing empirical results.

RESULTS indicate significant role of social networks in addition to other key factors on evacuation departure and travel times during hurricanes.


Language: en

Keywords

Departure time; Hurricane evacuation; Joint modelling; Social networks; Travel time

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