Title :
Modeling panic in ship fire evacuation using dynamic Bayesian network
Author :
Sarshar, Parvaneh ; Radianti, Jaziar ; Gonzalez, Jose J.
Author_Institution :
Dept. of Inf. & Commun. Technol., Univ. i Agder, Grimstad, Norway
Abstract :
In this paper, we model passengers´ panic during a ship fire by considering its most influential factors. The qualitative factors are quantified, allowing us to study passengers´ panic in a probabilistic manner. Considering the time-varying nature of these factors, we update the state of the factors over time. We utilize a dynamic Bayesian network (DBN) to model passengers´ panic, this allows us to represent probabilistic and dynamic elements. By defining several worst-case scenarios and running the simulations, we demonstrate how panic can dynamically vary from passenger to passenger with different physical (mental) conditions. Furthermore, we show how this panic can threaten passengers´ health during the evacuation process. The impact of panic on the evacuation time is also investigated. The results in this paper are valuable inputs for rescue teams and marine organizations that aim to mitigate property damages and human fatalities.
Keywords :
Bayes methods; behavioural sciences; emergency management; fires; marine safety; ships; DBN; dynamic Bayesian network; dynamic element representation; evacuation process; evacuation time; human fatality mitigation; marine organization; mental condition; passenger health; passenger panic modeling; physical condition; probabilistic element representation; property damage mitigation; qualitative factor quantification; rescue team; ship fire evacuation; worst-case scenario; Bayes methods; Fires; Marine vehicles; Mathematical model; Organizations; Standards organizations; Dynamic Bayesian network (DBN); evacuation time; panic; ship fire;
Conference_Titel :
Innovative Computing Technology (INTECH), 2013 Third International Conference on
Conference_Location :
London
Print_ISBN :
978-1-4799-0047-3
DOI :
10.1109/INTECH.2013.6653668