A simulation modeling framework for community-wide evacuation planning

Duanmu, Jun; Chowdhury, Mashrur; Taaffe, Kevin

doi:10.1007/s12198-010-0055-y

Cited by 10 publications

(3 citation statements)

References 4 publications

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“…In particular we analyse how relevant the Tsunami warning system was; aiming to expand on results discussed in Yun and Hamada (2015) or Suppasri et al (2013). Previous research has shown that responses to evacuation orders and warnings differ (Duanmu, Chowdhury, and Taaffe 2011). Our third questions is whether "field effects" are significant, that is, how important the influence of others is on evacuation.…”

Section: Questionsmentioning

confidence: 99%

Evacuation Decisions during the Great East Japan Earthquake

Schmöcker

Ji²,

Belgiawan

et al. 2023

Findings

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We analyse evacuation decisions with data from a survey among 10,384 survivers of the 2011 Great East Japan earthquake. The decisions of individuals and families to evacuate or stay are influenced by the Tsunami warning system as well as the behaviour of the surrounding population which is modelled as the percentage of persons evacuating from a city. We formulate binary choice models with “field effects” where we try to control for the endogeneity with a 2-stage model approach. Our results quantify the field effect and suggest that with each minute the Tsunami warning arrives later, on average 3% less of the population are evacuating and surviving. We also show the importance of other variables, in particular the preparedness measures such as signage and evacuation drills.

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Section: Questionsmentioning

confidence: 99%

Evacuation Decisions during the Great East Japan Earthquake

Schmöcker

Ji²,

Belgiawan

et al. 2023

Findings

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“…In addition, Duanmu et al. () presented a framework for preparing simulation inputs, such as traffic and roadway geometry, a behavioural analysis of potential evacuees, and ultimately developing a simulation model for a community‐wide evacuation process during an emergency. This type of study attempted to determine rational community evacuation systems or ways to identify the rational systems with the use of software such as geographic information systems (GIS) or simulators like the spot oriented agent role simulator (SOARS).…”

Section: Previous Efforts Toward Safer Community Evacuationmentioning

confidence: 99%

A community evacuation planning model against urban earthquakes

Toyoda

Kanegae

2014

Regional Science Policy & Practice

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The lessons from past earthquakes have highlighted the importance of constructing community evacuation systems. This paper reviewed previous studies on promoting safer community evacuation systems and found they are mostly on rational top-down evacuation systems or promoting resident participation but they failed to provide bottom-up approaches to constructing community evacuation systems by involving residents who have specific knowledge of the local vulnerability and capacity. Therefore, using case communities in Kyoto, Japan, this study suggested and verified a practical community evacuation planning (CEP) model for the construction, assessment, and supplementation of community evacuation systems by residents with local knowledge who are the first responders to disaster. JEL classification: D78, D81, D85, L38, O21

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“…Many of these studies employed traffic simulation software to better evaluate traffic patterns and load during primarily evacuation events. There have also been studies to investigate disaster prevention measures for evacuation plans and to develop methods to reduce the evacuation time from disaster-stricken areas [8,9]. The studies that evaluated evacuation strategy methods tested lane-based routing [10,11] and contraflow [12] techniques.…”

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confidence: 99%

Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

Jung

2018

Sustainability

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In this study, we focus on resilience as the ability of specific infrastructure systems at the regional scale to absorb the shocks of extreme events, such as earthquakes. The occurrence of a disaster such as an earthquake leads to a rapid decrease in infrastructure performance. In the case of road networks, performance might refer to the number of drivers using the road within a certain period of time. The objective of this study is to propose a quantitative evaluation method to analyze road network performance (or performance loss) when natural disasters occur. Furthermore, we use cluster analysis and consider the performance loss and asset value in an attempt to propose a method to determine the critical path that should be prioritized for maintenance. This study aimed at analyzing hazard resilience from the network aspect through a scenario analysis depending on damage recovery after disaster occurrence. This study compared the hazard resilience speed to recover existing performance according to the scenario for damage recovery targeting the selected road network. It was found that the total increase in the utility (e.g., total travel time saved) gradually diminished as the restoration cost increased. Keywords: performance loss; resilience; road infrastructure asset value; road network IntroductionRoad network related assets, such as roads, bridges, and tunnels, are critical infrastructure components that support the economic activities of the surrounding population. If disasters or unexpected situations occur that impact the performance of these networks, there is a high probability that the disruption will diffuse into the surrounding area and can result in the paralysis of the larger network due to the resulting chaos. Because road networks play a pivotal role in evacuation, relief, and rescue efforts over both the short and long term in real disaster situations, it is essential that a disaster prevention plan be developed ahead of time and that the road maintenance be performed regularly to ensure the network will function optimally in times of great need.In many developed countries, including the U.S. and Japan, national and local governments collaborate to establish infrastructure related disaster prevention and restoration plans, to designate certain major roads for both emergency evacuation and transportation, and to train and prepare personnel on how best to respond in order to minimize the damage from disasters [1,2].Increases in the amount of unusual weather due to global warming raises the likelihood of various unexpected situations. The Department for Transport in the UK [3] conducted a study predicting the probability of performance reduction in the traffic sector due to various unexpected situations and the Department of Transport in the U.S. [1] classified the absorption and restoration processes of the traffic system in the event of disasters into several stages, including preparation, impact, response, and restoration, and presented strategies to improve the resilience before and after a disa...

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A simulation modeling framework for community-wide evacuation planning

Cited by 10 publications

References 4 publications

Evacuation Decisions during the Great East Japan Earthquake

Evacuation Decisions during the Great East Japan Earthquake

A community evacuation planning model against urban earthquakes

Enhancing Road Network Resilience by Considering the Performance Loss and Asset Value

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