Qualitative simulation of the panic spread in large-scale evacuation

Wang, Jinghong; Lo, Siuming; Sun, Jinhua; Wang, Qingsong; Mu, Honglin

doi:10.1177/0037549712456884

Cited by 38 publications

(21 citation statements)

References 23 publications

(23 reference statements)

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“…Liu et al, [13] and Chen and Xiao [14] used linear programming to evacuation route rerouting; Wang et al, [15] used systems dynamics to explore the spread of panic in evacuations; and qualitative studies of evacuees' decision processes was conducted by Robinson and Khattak [16]. Pedestrians are also model in evacuation simulations [17][18][19].…”

Section: Existing Evacuation Simulationsmentioning

confidence: 99%

Integrating a Simple Traffic Incident Model for Rapid Evacuation Analysis

Collins¹,

Robinson²,

Foytik³

et al. 2016

IJT

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Section: Existing Evacuation Simulationsmentioning

confidence: 99%

Integrating a Simple Traffic Incident Model for Rapid Evacuation Analysis

Collins¹,

Robinson²,

Foytik³

et al. 2016

IJT

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“…Most significantly, in a crisis situation, factors such as panic spread, people pushing, jamming up and overlooking alternative exits prevent a crowd from following an optimal plan [11,12]. Therefore, it is important that information about both hazards and people are continuously updated to always provide the best overview for rescue personnel and an update plan.…”

Section: Communicate Planmentioning

confidence: 99%

Escape planning in realistic fire scenarios with Ant Colony Optimisation

2014

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An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when predefined escape routes are blocked by a hazard, and there is a need to re-think which escape route is safest. This paper addresses automatically finding the safest escape routes in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering dynamic spread of fires, movability impairments caused by the hazards and faulty unreliable data. Special focus in this paper is on empirical tests for the proposed algorithms. This paper brings together the Ant Colony approach with a realistic fire dynamics simulator, and shows that the proposed solution is not only able to outperform comparable alternatives in static and dynamic environments, but also in environments with realistic spreading of fire and smoke causing fatalities. The aim of the solutions is usage by both individuals, such as from a personal smartphone of one of the evacuees, or for emergency personnel trying to assist large groups from remote locations.

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“…Most significantly, in a crisis situation factors such as panic spread, people pushing, jamming up and overlooking alternative exits prevent a crowd from following an optimal plan [10] [11]. Therefore, it is important that information about both hazards and people are continuously updated to always provide the best plan.…”

Section: Communicate Planmentioning

confidence: 99%

Ant Colony Optimisation for Planning Safe Escape Routes

Goodwin

Granmo

Radianti

et al. 2013

Recent Trends in Applied Artificial Intelligence

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Abstract. An emergency requiring evacuation is a chaotic event filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when a predefined escape route is blocked by a hazard, and there is a need to re-think which escape route is safest.This paper addresses automatically finding the safest escape route in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering both dynamic spread of hazards and congestion avoidance.The solution can be used both on an individual bases, such as from a personal smart phone of one of the evacuees, or from a remote location by emergency personnel trying to assist large groups.

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Qualitative simulation of the panic spread in large-scale evacuation

Cited by 38 publications

References 23 publications

Integrating a Simple Traffic Incident Model for Rapid Evacuation Analysis

Integrating a Simple Traffic Incident Model for Rapid Evacuation Analysis

Escape planning in realistic fire scenarios with Ant Colony Optimisation

Ant Colony Optimisation for Planning Safe Escape Routes

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