Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing

Radianti, Jaziar; Granmo, Ole‐Christoffer; Bouhmala, Noureddine; Sarshar, Parvaneh; Yazidi, Anis; González, José J.

doi:10.1109/hicss.2013.155

Cited by 31 publications

(23 citation statements)

References 77 publications

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“…Another comprehensive review is given by Gwynne et al (1999b). For a more recent review, see (Radianti et al, 2013). Many of the models reviewed in these papers are commercial products, and for that reason, the details of the models' properties are not usually published.…”

Section: Computational Crowd Modelingmentioning

confidence: 99%

Patient and impatient pedestrians in a spatial game for egress congestion

et al. 2013

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In Today's built environment, it is common that large numbers of people gather in buildings. Also evacuations of such large crowds take place frequently all over the world. Standard safety requirements for buildings cannot always ensure safe evacuation of people in such situations, and thus, computational evacuation simulations have become a common practice in building design. The currently available simulation models are able to produce quite realistic movement and egress flows. However, there has not been much focus on modeling evacuees' behavior and decision making, which may significantly affect the outcome of evacuations.This thesis develops new modeling methods to describe the behavior of pedestrians in evacuation situations. The developed models are implemented in a state-of-the-art simulation software that combines evacuation simulation with fire simulation. The models apply game theory, which is the mathematical framework for describing strategic interaction between individuals.A novel game theoretic model for occupants' exit route selection is proposed. It describes how evacuees react to the surroundings and other evacuees' actions when deciding which exit to use. Another presented model uses spatial game theory to describe pedestrian behavior and interaction in threatening and congested situations at egress route bottlenecks. The model shows that reasonable behavior by pedestrians may lead to pushing and slow down the egress flow. In addition, a new physical approach for modeling pedestrian counterflow is given.The thesis also gives the results of an experimental study on pedestrian behavior and decision making in evacuations. It is observed that, even in simple experimental settings, people are often unable to select the fastest egress route. Another interesting finding is that the participants' attempts to cooperate may lead to slower evacuation.The developed models enable building more realistic tools for evacuation simulation, which help to better assess the safety of different venues. Also, the game theoretic models improve the understanding of how crowd-level movement and phenomena emerge from the behavior and decisions of individual crowd members. The experimental results presented in the thesis provide new insights into human behavior in evacuation situations. The results of the experiments can also be used to validate computational simulation models.Keywords evacuation, simulation, game theory, experiment, crowd, behavior Tiivistelmä Nykyään on yleistä, että suuria ihmismääriä joudutaan evakuoimaan rakennuksista. Pelkkä rakennusmääräysten noudattaminen ei aina takaa evakuoinnin turvallisuutta, joten evakuoinnin tietokonesimulaatiot ovat yleistyneet rakennusten suunnittelussa. Olemassa olevat simulaatiomallit kuvaavat ihmisjoukkojen liikkumista varsin realistisesti. Sen sijaan ihmisten käyttäytymisen ja päätöksenteon mallinnus ei ole yhtä kehittynyttä, huolimatta näiden tekijöiden merkittävästä vaikutuksesta evakuointien lopputuloksiin.Väitöskirjassa kehitetään menetelmiä evakuoitavien...

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Section: Computational Crowd Modelingmentioning

confidence: 99%

Patient and impatient pedestrians in a spatial game for egress congestion

et al. 2013

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“…In addition, the sensor information available in smart phones will communicate presence of hazards using the camera, position using GPS, gyroscope etc. This provides a threat map which is support both for rescue personnel and to automatically determine the best escape routes [3].…”

Section: Introductionmentioning

confidence: 99%

Ant Colony Optimisation for Planning Safe Escape Routes

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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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“…This extension relies upon timely measurements (or estimations) of temperature and radiation levels in emergency situations. Such measurements can be collected from fixed or mobile sensors [3].…”

Section: Hazardsmentioning

confidence: 99%

“…Results from this hazard function are available in Section 4.2. Secondly, the function h 3 (v i , t) is defined to represent realistic probabilities of fatal hazards based on exposure levels of thermal radiation 3 and temperature emitted by the fire [13][14][15]. This extension relies upon timely measurements (or estimations) of temperature and radiation levels in emergency situations.…”

Section: Hazardsmentioning

confidence: 99%

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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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Crowd Models for Emergency Evacuation: A Review Targeting Human-Centered Sensing

Cited by 31 publications

References 77 publications

Patient and impatient pedestrians in a spatial game for egress congestion

Patient and impatient pedestrians in a spatial game for egress congestion

Ant Colony Optimisation for Planning Safe Escape Routes

Escape planning in realistic fire scenarios with Ant Colony Optimisation

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