How to Evacuate: Model for Understanding the Routing Strategies during Hurricane Evacuation

Sadri, Arif Mohaimin; Ukkusuri, Satish V.; Murray‐Tuite, Pamela; Gladwin, Hugh

doi:10.1061/(asce)te.1943-5436.0000613

Cited by 81 publications

(43 citation statements)

References 43 publications

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“…The method detailed in Hasan et al (2013) and Sadri et al (2014b) is employed in this study. The whole data were divided into two sections, namely sample group 1 and sample group 2.…”

Section: Validation Of Model Specificationmentioning

confidence: 99%

A household-level flood evacuation decision model in Quezon City, Philippines

Lim

Piantanakulchai

et al. 2015

Nat Hazards

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Evacuation is one of the important preparedness measures in disaster management. It requires careful modeling and planning to minimize chaos and confusion during evacuation operations. The choice of decision-makers, whether to evacuate or stay in the area threatened by hazard, is an important aspect of evacuation travel behavior research. This is considered an essential input for evacuation modeling and planning. This study investigates the effects of various factors determining evacuation decision. A discrete choice model is proposed using the data collected through a face-to-face post-event survey from flood-affected households in Quezon City, Philippines. The model allows a choice among three alternatives of full, partial, and no evacuation. Results show that evacuation decision is determined by a combination of household characteristics and capacity-related factors (gender, educational level, presence of children, and number of years living in the residence, house ownership, number of house floor levels, type of house material), as well as hazard-related factors (distance from source of flood, level of flood damage, and source of warning). Findings in the study provide insights that can be considered by policy-makers in preparing for future evacuations. Appropriate programs can be designed to encourage full evacuation compliance of households that live nearest to the flood source and those living in houses with two or more floor levels who are more likely not to evacuate.Households with children can also be educated for full evacuation compliance since these households have higher probability to partially evacuate.

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“…The method detailed in Hasan et al (2013) and Sadri et al (2014b) is employed in this study. The whole data were divided into two sections, namely sample group 1 and sample group 2.…”

Section: Validation Of Model Specificationmentioning

confidence: 99%

A household-level flood evacuation decision model in Quezon City, Philippines

Lim

Piantanakulchai

et al. 2015

Nat Hazards

View full text Add to dashboard Cite

show abstract

“…These discrete‐choice models describe individual evacuation choices as a function of their risk recognition, which in turn is a function of various characteristics of the individual in combination with available disaster information. The discrete choice model can be applied to analyze evacuees' behaviors, namely, evacuation choice, destination choice, transport mode choice, and route choice . Incorporating factors such as risk education and risk information into these models enables us to evaluate the impact on parameters such as the evacuation response rate.…”

Section: Earlier Studies On Risk Recognitionmentioning

confidence: 99%

People's Risk Recognition Preceding Evacuation and Its Role in Demand Modeling and Planning

Urata

Pel

2017

Risk Analysis

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Evacuation planning and management involves estimating the travel demand in the event that such action is required. This is usually done as a function of people's decision to evacuate, which we show is strongly linked to their risk awareness. We use an empirical data set, which shows tsunami evacuation behavior, to demonstrate that risk recognition is not synonymous with objective risk, but is instead determined by a combination of factors including risk education, information, and sociodemographics, and that it changes dynamically over time. Based on these findings, we formulate an ordered logit model to describe risk recognition combined with a latent class model to describe evacuation choices. Our proposed evacuation choice model along with a risk recognition class can evaluate quantitatively the influence of disaster mitigation measures, risk education, and risk information. The results obtained from the risk recognition model show that risk information has a greater impact in the sense that people recognize their high risk. The results of the evacuation choice model show that people who are unaware of their risk take a longer time to evacuate.

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“…2.2 we modelled the evacuees as independent acting agents with different preference types. As known from Sadri et al (2014), who analysed the route choice behaviour during hurricane Ivan (2004), most people try to take a familiar route, in most cases the shortest or fastest route. To consider this findings in the computational study we take three different preference types.…”

Section: Experimental Designmentioning

confidence: 99%

“…So we concentrate on the traffic routing from the dangerous zone to the safe areas. In such a situation it might be impossible to communicate the best route to every evacuee moreover it is difficult to ensure that every evacuee would take this route (Sadri et al 2014). With our approach we investigate how the street network has to be redesigned to reach an optimal evacuation under the condition that the evacuees take their routes selfishly.…”

Section: Introductionmentioning

confidence: 99%