Heuristic Priority Ranking of Emergency Evacuation Staging to Reduce Clearance Time

Mitchell, Steven W.; Radwan, Essam

doi:10.3141/1964-24

Cited by 27 publications

(13 citation statements)

References 9 publications

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“…More recently, a large number of evacuation studies are conducted using well-established dynamic traffic simulation models developed for regular day-to-day traffic applications, including both microscopic models, such as PARAMICS (Cova and Johnson 2003), CORSIM (Williams et al 2007), VISSIM (Han and Yuan 2005), and INTEGRA-TION (Mitchell and Radwan 2006), and mesoscopic or macroscopic models, such as DYNASMART (Murray-Tuite 2007), DynaMIT (Balakrishna et al 2008), DynusT (Noh et al 2009), TransCAD (Wang et al 2010), and INDY (Klunder et al 2009). In a number of studies using microscopic models, model parameters describing driving behaviour (such as headway, acceleration, reaction time) have been adjusted for the case of emergency evacuation (e.g., Tu et al 2010).…”

Section: Past and Current Evacuation Traffic Simulation Modelsmentioning

confidence: 99%

“…Evacuation studies using the en-route route choice model are scarce. One possible example is the study by Mitchell and Radwan (2006) using INTEGRATION (Rakha and van Aerde 2004) to study the impact of evacuation staging on network clearance time. However, it should be mentioned that INTEGRATION provides both pretrip and en-route route choice models and it is not fully clear which route choice model alternative was used in this study.…”

Section: En-route Route Choice Modelsmentioning

confidence: 99%

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A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

2011

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Dynamic traffic simulation models are frequently used to support decisions when planning an evacuation. This contribution reviews the different (mathematical) model formulations underlying these traffic simulation models used in evacuation studies and the behavioural assumptions that are made. The appropriateness of these behavioural assumptions is elaborated on in light of the current consensus on evacuation travel behaviour, based on the view from the social sciences as well as empirical studies on evacuation behaviour. The focus lies on how travellers' decisions are predicted through simulation regarding the choice to evacuate, departure time choice, destination choice, and route choice. For the evacuation participation and departure time choice we argue in favour of the simultaneous approach to dynamic evacuation demand prediction using the repeated binary logit model. For the destination choice we show how further research is needed to generalize the current preliminary findings on the location-type specific destination choice models. For the evacuation route choice we argue in favour of hybrid route choice models that enable both following instructed routes and en-route switches. Within each of these discussions, we point at current limitations and make corresponding suggestions on promising future research directions.

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Section: Past and Current Evacuation Traffic Simulation Modelsmentioning

confidence: 99%

Section: En-route Route Choice Modelsmentioning

confidence: 99%

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

2011

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“…Various studies have focused on different aspects of evacuation planning, such as demand modeling (Mei 2002;Wilmot 2004;Fu 2007), departure scheduling (Malone 2001;Mitchell 2006;Sbyati 2006;Chien 2007;Chen 2008), route choice (Cova 2003;Afshar 2008;Chiu 2008;Yazici 2010;Zheng 2010;Xie 2011;), contra-flow operation (Theodoulou 2004;Wolshon 2005;Tuydes 2006;Xie 2010) and relief operation (Haghani 1996;Barbarosoglu 2004;Ozbay 2007;Xie 2009). Most of these are specific to the control and management of passenger car flows.…”

Section: Literature Reviewmentioning

confidence: 99%

A Transit-Based Evacuation Model for Metropolitan Areas

Zhang¹,

Chang²

2014

JPT

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“…Several demand time profiles are defined and simulated through mesoscopic [15] or microscopic simulators [16] and compared with the simultaneous departures scenario. Evacuation demand scheduling is also treated through a pseudo-dynamic approach [2].…”

Section: Literature Review Of Dta Models In Emergency Conditionsmentioning

confidence: 99%

Safety of users in road evacuation: calibration of cost functions and simulation

Vitetta¹,

Musolino²,

Marciano³

2008

WIT Transactions on the Built Environment

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Advancements regarding Dynamic Traffic Assignment (DTA) microscopic models for the simulation of supply and demand-supply interaction of a road transportation system in emergency conditions are presented. They are related to link and node models specified in the research project SICURO, carried out by the Laboratory for Transport Systems Analysis (LAST) of the Mediterranea University of Reggio Calabria (Italy). Microscopic link (car-following) and gap-acceptance (rejection) models for non-signalized intersections are calibrated from data observed during a real simulation of evacuation. An application is performed in order to reproduce the observed evacuation phases through a set of performance indicators.

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Heuristic Priority Ranking of Emergency Evacuation Staging to Reduce Clearance Time

Cited by 27 publications

References 9 publications

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

A review on travel behaviour modelling in dynamic traffic simulation models for evacuations

A Transit-Based Evacuation Model for Metropolitan Areas

Safety of users in road evacuation: calibration of cost functions and simulation

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