An approach for modeling human cognitive behavior in evacuation models

Pires, Tiago Ancelmo

doi:10.1016/j.firesaf.2004.10.004

Cited by 78 publications

(37 citation statements)

References 18 publications

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“…Compared to the particle swarm optimization (PSO) based behavioral and probabilistic fire evacuation model produced by [10], Bee-Fire developed in this study has the advantages that it can directly lay out those guidance signs. During fire, the condition inside the building will become chaotic with low visibility, low environmental familiarity, and high anxiety; thus evacuees highly rely on the emergency exit guidance signs [4].…”

Section: Discussion On Resultsmentioning

confidence: 99%

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Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

Chen

Wood

et al. 2018

Journal of Applied Mathematics

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Every minute counts in an event of fire evacuation where evacuees need to make immediate routing decisions in a condition of low visibility, low environmental familiarity, and high anxiety. However, the existing fire evacuation routing models using various algorithm such as ant colony optimization or particle swarm optimization can neither properly interpret the delay caused by congestion during evacuation nor determine the best layout of emergency exit guidance signs; thus bee colony optimization is expected to solve the problem. This study aims to develop a fire evacuation routing model "Bee-Fire" using artificial bee colony optimization (BCO) and to test the routing model through a simulation run. Bee-Fire is able to find the optimal fire evacuation routing solutions; thus not only the clearance time but also the total evacuation time can be reduced. Simulation shows that BeeFire could save 10.12% clearance time and 15.41% total evacuation time; thus the congestion during the evacuation process could be effectively avoided and thus the evacuation becomes more systematic and efficient.

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Section: Discussion On Resultsmentioning

confidence: 99%

“…Early in the fire initial phase, human behavior is of utmost importance as to survival [3,4]. The human behavior can be defined as sets of actions taken based on individuals' perception of a situation, intention to act, as well as preaction considerations [5].…”

Section: Introductionmentioning

confidence: 99%

Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

Chen

Wood

et al. 2018

Journal of Applied Mathematics

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“…Some of them studied the fire advance [25,26], while some other [9,11,15,17,21,24,27] studied the people behavior when evacuating a building. However in this paper we propose a new approach to define the best evacuation route, after analyzing, from an optimization point of view, the different alternative routes from each corridor cross to the different exit doors.…”

Section: Discussionmentioning

confidence: 99%

A model for defining evacuation policies for emergency escape from buildings

Adenso‐Díaz

González-Torre

Ordóñez

et al. 2008

Int. J. Simul. Multidisci. Des. Optim.

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-Over the last 10 years, the need to guarantee safety in the habitability of buildings has led to the development of different models (which are usually classified either as optimization, simulation, or risk assessment approaches) that help define how urgent evacuation of the building should take place in the event of a fire or any other circumstance that requires such a measure. This paper presents an optimization model embedded in a simulation model that enables the user to define which evacuation routes should be used to minimize the time needed to evacuate all occupants. The system is presented here along with an experimental framework designed to assess the quality of the proposed solutions and the system's performance with respect to different types of buildings. Results analysis show improvements around 9% of the time needed to evacuate a building, using an experimental framework that considers three main factors: type of building, number of exit doors and capacity flow in the corridors.

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“…Al hacer una revisión de la literatura de los trabajos publicados en diferentes bases de datos bibliográficas se logró evidenciar que no existen estudios publicados donde se tengan en cuenta los centros de servicio, y a nivel mundial se observan algunos intentos por modelar dicho comportamiento en distintos ambientes [2], [5], [8], [9], [27], [35], [59]- [62], [70]- [73].…”

Section: Comportamiento Humanounclassified

Modelación y simulación de comportamientos humanos en situaciones de emergencia en un call center: una revisión crítica de literatura

2018

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[7]. En las organizaciones, y para establecer planes de emergencia efectivos, cumplir con las normas colombianas y salvaguardar el bienestar y la vida de las personas que laboran en un espacio empresarial determinado, se han dedicado esfuerzos considerables en estudios e investigaciones con el fin de elaborar, mejorar y aplicar nuevos planes de emergencia [8].Cada empresa tiene dentro de sus instalaciones personas trabajando en diversas labores. A cada puesto de trabajo se le asigna una persona la cual fue previamente seleccionada por sus aptitudes técnicas, físicas y comportamentales entre otras. Esas aptitudes, además del pánico generado por los eventos de emergencia, influyen en la reacción de cada individuo ante una situación de emergencia [5]Así, poder comprender, modelar y simular el comportamiento de las personas en diferentes situaciones de emergencia, constituye un problema de investigación pertinente, de modo que permita orientar y Resumen. En este trabajo se presenta una revisión de literatura de la modelación y simulación de comportamientos humanos en situaciones de emergencia en un call center. Para la búsqueda se consultaron bases de datos bibliográficas como Scopus, Sciencedirect, y Emerald entre otras, en las que, tras realizar un proceso estructurado de revisión bibliográfica, se encontraron más de 50 artículos. La clasificación de los artículos encontrados se hizo en cuatro categorías: (1) tipo de análisis, (2) tipo de emergencia, (3) tipo de entorno y (4) tipo de comportamiento. En los tipos de análisis de los artículos se encontró que la mayoría se enfocan en estudios estadísticos y heurísticos; los entornos analizados se enfocan principalmente en edificios de oficinas y de otros tipos como vivienda, y locales comerciales; el evento más analizado es el incendio; y en cuanto al tipo de comportamiento se encuentra que son diversas las formas en las cuales las personas reaccionan ante eventos de emergencia. Se encuentra en la literatura consultada la caracterización de los posibles comportamientos de las personas que pueden tener en un evento de emergencia, esto con el fin de tener una aproximación de tales comportamientos dentro de la simulación de eventos de emergencia. Abstract. This paper presents

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An approach for modeling human cognitive behavior in evacuation models

Cited by 78 publications

References 18 publications

Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

A model for defining evacuation policies for emergency escape from buildings

Modelación y simulación de comportamientos humanos en situaciones de emergencia en un call center: una revisión crítica de literatura

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