Analyzing evacuation decisions using multi-attribute utility theory (MAUT)

Emergency managers are faced with critical evacuation decisions. These decisions must balance conflicting objectives as well as high levels of uncertainty. Multi-Attribute Utility Theory (MAUT) provides a framework through which objective trade-offs can be analyzed to make optimal evacuation decisions. This paper is the result of data gathered during the European Commission Project, Evacuation Responsiveness by Government Organizations (ERGO) and outlines a preliminary decision model for the evacuation decision. The illustrative model identifies levels of risk at which point evacuation actions should be taken by emergency managers in a storm surge scenario with forecasts at 12 and 9 hour intervals. The results illustrate how differences in forecast precision affect the optimal evacuation decision. Additional uses for this decision model are also discussed along with improvements to the model through future ERGO data-gathering

Evacuation responsiveness by government organisations (ERGO):the evacuation preparedness assessment workbook

This Evacuation Preparedness Assessment Workbook (EPAW) is a tool to assess the level of preparedness of Government Organisations (GOs) for the mass evacuation of their public. It has its origins in the results of a three-year, EU-funded research project called Evacuation Preparedness by Government Organisations (ERGO) which sought to research and strengthen the preparedness activities for the evacuation of cities, regions or even countries. This EPAW presents a list of tasks to be carried out at the different phases of evacuation preparedness. It also provides an assessment facility to evaluate how much progress GOs have made against each task, as well as indications of standard and best practices for each task. A brief background to the need for evacuation, the ERGO project and the development of the workbook is given next. After this, the application process of the workbook is explained and illustrated with an example

Decision theory to support evacuation in advance of catastrophic disaster including modular influence diagrams and spatial data analysis.

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A model evaluating effect of disaster warning issuance conditions on "cry wolf syndrome" in the case of a landslide

This study proposes a model that clarifies how disaster warning issuance conditions affect "cry wolf' syndrome. The disaster assumed in this study is landslide caused by heavy rainfall. Local authorities that issue disaster warnings are thought to tend to avoid the situation where casualty occurs without the issuance to residents of a disaster warning. As a result, the issuance conditions may be relaxed. Under this circumstance, however, the residents are thought to tend to ignore disaster warnings, since such warnings are inaccurate. Thus may emerge the "cry wolf' syndrome. In this study, a simulation model that expresses the behaviors of the local authority and the residents has been developed. For the purpose of demonstrating the model, numerical experiments were then carried out. In the numerical experiments, the effects of optimal issuance conditions for disaster warnings on the cost incurred by the resident were evaluated by using assumed parameters for the model

Evacuation responsiveness by government organisations: evacuation preparedness assessment workbook

This Evacuation Preparedness Assessment Workbook (EPAW) is a tool to assess the level of preparedness of Government Organisations (GOs) for the mass evacuation of their public. It has its origins in the results of a three-year, EU-funded research project called Evacuation Preparedness by Government Organisations (ERGO) which sought to research and strengthen the preparedness activities for the evacuation of cities, regions or even countries. This EPAW presents a list of tasks to be carried out at the different phases of evacuation preparedness. It also provides an assessment facility to evaluate how much progress GOs have made against each task, as well as indications of standard and best practices for each task. A brief background to the need for evacuation, the ERGO project and the development of the workbook is given next. After this, the application process of the workbook is explained and illustrated with an example