Emerging Hurricane Evacuation Issues: Hurricane Floyd and South Carolina

Dow, Kirstin; Cutter, Susan L.

doi:10.1061/(asce)1527-6988(2002)3:1(12)

Cited by 229 publications

(137 citation statements)

References 10 publications

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“…transportation networks, levees, evacuation shelters), the characteristics of which can influence a community's place vulnerability (Piegorsch et al 2007). One such infrastructure feature is a road network (Dow & Cutter 2002), particularly in instances where evacuation and emergency response are integral to the mitigation of impacts. During certain hazardous events, the affected communities have the option to evacuate (Cova & Johnson 2002.…”

Section: Introductionmentioning

confidence: 99%

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Incorporating evacuation potential into place vulnerability analysis

Yorke

Zhan

et al. 2013

Geomatics, Natural Hazards and Risk

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The purpose of this research is to illustrate a three-component operationalization of the Hazards-of-Place Model (HPM) by integrating urban infrastructure (using the capacity of road networks to facilitate evacuation as an example) to describe place vulnerability. This approach is informed by the HPM first articulated by Cutter (Vulnerability to environmental hazards. Prog Hum Geog. 20:529-39, 1996). The HPM is a conceptual framework through which place vulnerability is defined as a combination of social characteristics (expressed by selected socioeconomic demographics) and geophysical risk (expressed by probabilities of occurrence). Using a geographic information system (GIS), the study models the capacity of road networks to facilitate evacuation and used it as an example of urban infrastructure within which place vulnerability occurs. The output of the model was integrated with a geophysical risk layer and social vulnerability index layer as components for assessing the overall place vulnerability. The threecomponent approach to operationalizing the HPM provides a detailed and nuanced illustration of place-based vulnerability. As an applied tool, the threecomponent approach presents emergency planners with a new method of integrating diverse geographic data when illustrating spatial patterns of vulnerability to environmental hazards.

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Section: Introductionmentioning

confidence: 99%

“…These factors include weather conditions during the time of the evacuation, the size of the vulnerable population and the capacity of road networks (Southworth 1991;Dow & Cutter 2002;Sorensen et al 2002). Of particular importance to this research is the capacity of road networks to facilitate evacuation.…”

Section: Introductionmentioning

confidence: 99%

Incorporating evacuation potential into place vulnerability analysis

Yorke

Zhan

et al. 2013

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

show abstract

“…The simulation must be able to reproduce the driver behaviours observed in real-life evacuations but with the constraint of there being limited opportunity to gain real-world data. Studies of real-life evacuations have revealed patterns of traffic behaviour in which a perceived degree of physical danger causes drivers to ignore road maps and choose routes similar to those of others, so as to avoid being isolated [6,15]. This leads to a disproportionate increase in use of major routes and a spread of routes across the road network with suboptimum flow rates for evacuation.…”

Section: Introductionmentioning

confidence: 99%

An agent-based social forces model for driver evacuation behaviours

Handford

Rogers

2012

Prog Artif Intell

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Realistic modelling of driver behaviour during evacuation scenarios is vitally important for creating effective training environments for disaster management. However, few current models have satisfactorily incorporated the level of complexity required to model the unusual driver behaviours which occur in evacuations. In particular, few state-of-the-art traffic simulators consider desires of a driver other than to travel the quickest route between two points. Whereas in real disaster settings, empirical evidence suggests other key desires such as that of being near to other vehicles. To address this shortcoming, we present an agentbased behaviour model based on the social forces model of crowds, which explicitly includes these additional factors. We demonstrate, by using a metric of route similarity, that our model is able to reproduce the real-life evacuation behaviour whereby drivers follow the routes taken by others. The model is compared to the two most commonly used route choice algorithms, that of quickest route and real-time re-routing, on three road networks: an artificial "ladder" network, and those of Louisiana, USA and Southampton, UK. When our route choice forces model is used our measure of route similarity increases by 21-169 %. Furthermore, a qualitative comparison demonstrates that the model can reproduce patterns of behaviour observed in the 2005 evacuation of the New Orleans area during Hurricane Katrina.

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“…To this end, the use of agent-based models of individual drivers has proven to be an effective way of modelling traffic systems [3], in which the aggregation of driver behaviours reproduces real-life patterns of overall traffic behaviour. During real-life evacuations, studies have shown patterns of traffic behaviour in which a perceived degree of physical danger causes drivers to choose routes similar those of others, so as to avoid being isolated [5,12]. In the evacuation of the New Orleans area during Hurricane Katrina in 2005 this interdependence in driver behaviour led to situations in which, despite there being two possible escape routes, a disproportionate number of drivers used just one over the other.…”

Section: Introductionmentioning

confidence: 99%

“…Here the drivers are able to re-plan their escape routes, factoring in real-time knowledge of the congestion on other roads. However, this causes a repulsive behaviour between drivers, the opposite of what is actually observed in real-life evacuations, where drivers desire to use routes which they believe others will be using [5]. Neither of the offered algorithms are able to replicate the observed patterns of behaviour in evacuations and thus their use for disaster management simulation is significantly impaired [4].…”

Section: Introductionmentioning

confidence: 99%

Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management

Handford

Rogers

2011

Advances in Intelligent and Soft Computing

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Accurate modelling of driver behaviour in evacuations is vitally important in creating realistic training environments for disaster management. However, few current models have satisfactorily incorporated the variety of factors that affect driver behaviour. In particular, the interdependence of driver behaviours is often seen in real-world evacuations, but is not represented in current state-of-the art traffic simulators. To address this shortcoming, we present an agent-based behaviour model based on the social forces model of crowds. Our model uses utility-based path trees to represent the forces which affect a driver's decisions. We demonstrate, by using a metric of route similarity, that our model is able to reproduce the real-life evacuation behaviour whereby drivers follow the routes taken by others. The model is compared to the two most commonly used route choice algorithms, that of quickest route and real-time re-routing, on three road networks: an artificial "ladder" network, and those of Lousiana, USA and Southampton, UK. When our route choice forces model is used our measure of route similarity increases by 21%-93%. Furthermore, a qualitative comparison demonstrates that the model can reproduce patterns of behaviour observed in the 2005 evacuation of the New Orleans area during Hurricane Katrina.

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Emerging Hurricane Evacuation Issues: Hurricane Floyd and South Carolina

Cited by 229 publications

References 10 publications

Incorporating evacuation potential into place vulnerability analysis

Incorporating evacuation potential into place vulnerability analysis

An agent-based social forces model for driver evacuation behaviours

Modelling Driver Interdependent Behaviour in Agent-Based Traffic Simulations for Disaster Management

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