Enhanced Altruistic Behavior by One Significant Experience or Learning in Fire Evacuation Experiment

2020 ◽  
Vol 16 (7) ◽  
pp. 71-84
Author(s):  
Soyoung Kim ◽  
Ik Jae Chung
Keyword(s):  
Altruistic Behavior ◽  
Fire Evacuation ◽  
In Fire ◽  
Evacuation Experiment

scholarly journals A Framework for an Intelligent and Personalized Fire Evacuation Management System

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3128 ◽  
Author(s):  
Jinyue Zhang ◽  
Jianing Guo ◽  
Haiming Xiong ◽  
Xiangchi Liu ◽  
Daxin Zhang
Keyword(s):  
Information Modeling ◽  
Risk Level ◽  
Management Framework ◽  
Fire Evacuation ◽  
Building Information ◽  
Evacuation Management ◽  
Evacuation Route ◽  
In Fire ◽  
Real Time Location System

Many research studies have focused on fire evacuation planning. However, because of the uncertainties in fire development, there is no perfect solution. This research proposes a fire evacuation management framework which takes advantage of an information-rich building information modeling (BIM) model and a Bluetooth low energy (BLE)-based indoor real-time location system (RTLS) to dynamically push personalized evacuation route recommendations and turn-by-turn guidance to the smartphone of a building occupant. The risk score (RS) for each possible route is evaluated as a weighted summation of risk level index values of all risk factors for all segments along the route, and the route with the lowest RS is recommended to the evacuee. The system will automatically re-evaluate all routes every 2 s based on the most updated information, and the evacuee will be notified if a new and safer route becomes available. A case study with two testing scenarios was conducted for a commercial office building in Tianjin, China, in order to verify this framework.

The application of ant colony algorithm in fire evacuation

2021 ◽  
Author(s):  
Xujie Wang ◽  
Xiaohai Zheng ◽  
Qilong Wang ◽  
Tenghui Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Fire Evacuation ◽  
In Fire

scholarly journals Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Chen Wang ◽  
Lincoln C. Wood ◽  
Heng Li ◽  
Zhenye Aw ◽  
Abolfazl Keshavarzsaleh
Keyword(s):  
Artificial Bee Colony ◽  
Clearance Time ◽  
Evacuation Time ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Fire Evacuation ◽  
Bee Colony Optimization ◽  
Emergency Exit ◽  
Evacuation Routing ◽  
In Fire

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 Bee-Fire 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.

Investigating Human Factors in Fire Evacuation: A Serious-Gaming Approach

2013 ◽  
pp. 1113-1121 ◽  
Author(s):  
K. Schatz ◽  
J. Schlittenlacher ◽  
D. Ullrich ◽  
U. Rüppel ◽  
W. Ellermeier
Keyword(s):  
Human Factors ◽  
Serious Gaming ◽  
Fire Evacuation ◽  
In Fire

scholarly journals Risk perception in fire evacuation behavior revisited: definitions, related concepts, and empirical evidence

2015 ◽  
Vol 4 (1) ◽  
Author(s):  
Max T Kinateder ◽  
Erica D Kuligowski ◽  
Paul A Reneke ◽  
Richard D Peacock
Keyword(s):  
Risk Perception ◽  
Empirical Evidence ◽  
Fire Evacuation ◽  
Evacuation Behavior ◽  
In Fire

Study on the Human Behavior in Metro Fire

2013 ◽  
Vol 353-356 ◽  
pp. 1456-1460 ◽  
Author(s):  
Guo Min Zhao
Keyword(s):  
Statistical Study ◽  
Personal Information ◽  
Rapid Development ◽  
Behavioral Responses ◽  
Subway Station ◽  
Surrounding Environment ◽  
Fire Condition ◽  
Fire Evacuation ◽  
In Fire ◽  
Passenger Behavior

With the rapid development of city subway, subway disaster problems aroused people's attention. Subway fire especially priority among priorities in subway disaster. This research mainly rely on the way of questionnaire survey, conducted a statistical study on metro fire evacuation behavior. The author has carried on questionnaire investigation to the passengers of some subway station in Tianjin Metro Line 1. The author sent out 116 questionnaires, received effective questionnaires 100 copies. The questionnaire content mainly includes the basic personal information, the surrounding environment and the passenger behavior in fire condition. The author analyzes the first behavior survey of different sex, different age, different education, different frequency and different subway fire experience reaction. Management departments according to the behavioral responses of passengers improve and optimize the subway facilities and fire evacuation passage.

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