Modeling evacuation demand during no-notice emergency events: Tour formation behavior

Golshani, Nima; Shabanpour, Ramin; Mohammadian, Abolfazl; Auld, Joshua; Ley, Hubert

doi:10.1016/j.trc.2020.102713

Modeling evacuation demand during no-notice emergency events: Tour formation behavior

Journal Article · Tue Jul 14 00:00:00 EDT 2020 · Transportation Research Part C: Emerging Technologies

DOI:https://doi.org/10.1016/j.trc.2020.102713· OSTI ID:1812749

Golshani, Nima ^[1]; Shabanpour, Ramin ^[1]; Mohammadian, Abolfazl ^[1]; Auld, Joshua ^[2]; Ley, Hubert ^[2]

Univ. of Illinois, Chicago, IL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)

Disastrous events have been drastically increasing – both in frequency and destructive capacity – over the past few years. While advance-notice events have received a great deal of attention in the literature of disaster management, not much attention so far has been given to the no-notice events mainly because of the scarcity of data. As an attempt to address this critical gap, the current study proposes a disaggregate evacuation demand framework to understand evacuees’ travel behavior in case of no-notice emergency events. Here, the proposed framework comprises four main steps of evacuation decision, evacuation planning, tour formation, and activity schedule update. This article is dedicated to the introduction of the framework structure and elaboration on the tour formation step. In this step, we first estimate the total number of intermediate stops, travel time, and distance of the evacuation tours for those who decide to evacuate through a joint modeling structure and then, determine the type of each intermediate stop (if any). It is found that a broad range of factors including evacuees’ demographic profiles, built-environment attributes, and characteristics of the disastrous event plays a significant role in people’s evacuation behavior during no-notice emergency events. The findings of this study can assist responsible agencies in understanding evacuees’ complex behavior, and consequently, in devising effective strategies to alleviate economic damages and casualties resulted by such events.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: U.S. Department of Transportation; USDOE

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1812749

Journal Information:: Transportation Research Part C: Emerging Technologies, Journal Name: Transportation Research Part C: Emerging Technologies Vol. 118; ISSN 0968-090X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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