Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory

Wong, Scott T.; Pel, Adam J.; Shaheen, Susan; Chorus, Caspar

doi:10.1016/j.trd.2020.102227

Cited by 41 publications

(27 citation statements)

References 48 publications

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“…Wong et al (2018) reviews hurricane evacuation behavioral modeling and developed RUM models for evacuation choices. Other hurricane evacuation work has extended these models by employing different distributions through a probit model (Solis et al, 2010), creating choice nesting structures through a nested logit (Mesa-Arango et al, 2013), including random parameters through a mixed logit (Sadri et al, 2014;Sarwar et al, 2018), developing dynamic models through a sequential logit (Fu and Wilmot, 2004;Fu et al, 2006), considering decisions as multi-dimensional and joint (Wong et al, 2020), or accounting for different lifestyle preferences through a latent class choice model for tsunamis (Urata and Pel, 2018) and wildfires (McCaffrey et al, 2018). Despite this work, models continue to focus on demographic variables, risk perceptions, or hazard characteristics, not choice attributes.…”

Section: Utility Maximization and Evacuation Behaviormentioning

confidence: 99%

A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study

Wong

Chorus

Shaheen

et al. 2020

Travel Behaviour and Society

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Regret is often experienced for difficult, important, and accountable choices. Consequently, we hypothesize that random regret minimization (RRM) may better describe evacuation behavior than traditional random utility maximization (RUM). However, in many travel related contexts, such as evacuation departure timing, specifying choice sets can be challenging due to unknown attribute levels and near-endless alternatives, for example. This has implications especially for estimating RRM models, which calculates attribute-level regret via pairwise comparison of attributes across all alternatives in the set. While stated preference (SP) surveys solve such choice set problems, revealed preference (RP) surveys collect actual behavior and incorporate situational and personal constraints, which impact rare choice contexts (e.g., evacuations). Consequently, we designed an RP survey for RRM (and RUM) in an evacuation context, which we distributed from March to July 2018 to individuals impacted by the 2017 December Southern California Wildfires (n=226). While we hypothesized that RRM would outperform RUM for evacuation choices, this hypothesis was not supported by our data. We explain how this is partly the result of insufficient attributelevel variation across alternatives, which leads to difficulties in distinguishing non-linear regret from linear utility. We found weak regret aversion for some attributes, and we identified weak class-specific regret for route and mode choice through a mixed-decision rule latent class choice model, suggesting that RRM for evacuations may yet prove fruitful. We derive methodological implications beyond the present context toward other RP studies involving challenging choice sets and/or limited attribute variability.

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Section: Utility Maximization and Evacuation Behaviormentioning

confidence: 99%

A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study

Wong

Chorus

Shaheen

et al. 2020

Travel Behaviour and Society

Self Cite

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“…All scenarios assume that a Category 3 hurricane is approaching southeast Florida and that people living in Palm Beach, Broward, Miami-Dade, and Monroe Counties are ordered to evacuate. Based on studies of evacuation compliance and behavior in this region for Category 3+ hurricanes, we estimate that 48% of each county's population would evacuate 7,[10][11][12][13][14][15][16][17]. Assuming that 19% of evacuees relocate elsewhere within their respective counties, this leads to a total of 2.3 million evacuees leaving the four affected counties 7,[16][17][18][19][20] .…”

Section: Full Model Simulations Of Hurricane Evacuation Scenariosmentioning

confidence: 99%

“…For each scenario, evacuees were assigned to a different set of destination counties based on a list of 165 possible destinations across 26 states identified during post-Hurricane Irma surveys 7,17 . In the baseline scenario, evacuees were assigned to all 165 destination counties in proportion to observed evacuation choices during Hurricane Irma.…”

Section: Full Model Simulations Of Hurricane Evacuation Scenariosmentioning

confidence: 99%

“…Because many people living outside of the mandatory evacuation zones voluntarily choose to evacuate during hurricanes as well, we used the same approach to calculate the percent of the population living outside of mandatory evacuation zones but within the affected counties that would evacuate. Based on four studies of this "shadow evacuation" phenomenon, we determined that an average of 47% of county residents outside mandatory evacuation zones would also evacuate 7,[13][14][15]17 . The mandatory and voluntary evacuees together represent 48% of each origin county's population.…”

Section: Hurricane Evacuation Scenario Developmentmentioning

confidence: 99%

“…The mandatory and voluntary evacuees together represent 48% of each origin county's population. We then determined that 19% of these evacuees would relocate within their respective counties based on the average from four evacuation behavior studies 7,[16][17][18][19][20] .…”

Section: Hurricane Evacuation Scenario Developmentmentioning

confidence: 99%

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Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States

Pei

Dahl

Yamana

et al. 2020

Preprint

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Current projections and unprecedented storm activity to date suggest the 2020 Atlantic hurricane season will be extremely active and that a major hurricane could make landfall during the global COVID-19 pandemic. Such an event would necessitate a large-scale evacuation, with implications for the trajectory of the pandemic. Here we model how a hypothetical hurricane evacuation from four counties in southeast Florida would affect COVID-19 case levels. We find that hurricane evacuation increases the total number of COVID-19 cases in both origin and destination locations; however, if transmission rates in destination counties can be kept from rising during evacuation, excess evacuation-induced case numbers can be minimized by directing evacuees to counties experiencing lower COVID-19 transmission rates. Ultimately, the number of excess COVID-19 cases produced by the evacuation depends on the ability of destination counties to meet evacuee needs while minimizing virus exposure through public health directives.

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Towards modelling of evacuation behavior and planning for emergency logistics due to the Philippine Taal Volcanic eruption in 2020

Lim

Rojas

2022

Nat Hazards

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Emergency evacuation is the immediate escape of people away from a place of an imminent threat to a place of safety. The ability of the households to evacuate is a crucial component in reducing disaster risk. Logistical issues such as a lack of resources during and after the evacuation, as well as road congestion, might arise, especially in short and no-notice calamities such as a volcanic eruption. This study examines the relationship of variables of evacuation logistics of Barangay Banga, Talisay, Batangas in the context of the 2020 Taal Volcanic eruption. A survey was conducted based on the experience of the households during the volcanic eruption. A descriptive statistical analysis was performed for all the variables on household evacuation logistics to understand the behavior of households as they make decisions during emergencies. These variables include the type of evacuation, departure timing, evacuation mode choice, and destination choice. Additionally, a pairwise correlation was employed to identify the in uential factors related to household evacuation logistics such as socio-demographic and household characteristics, hazard-related factors as well as their experience with Taal Volcano's recurring activities. The results of this study aim to provide insights to a better understanding of the evacuation behavior of households in the context of a volcanic eruption and be useful in the evacuation logistics planning of the country.

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Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory

Cited by 41 publications

References 48 publications

A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study

A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study

Compound risks of hurricane evacuation amid the COVID-19 pandemic in the United States

Towards modelling of evacuation behavior and planning for emergency logistics due to the Philippine Taal Volcanic eruption in 2020

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