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Assessing offshore emergency evacuation behavior in a virtual environment using a Bayesian Network approach


Musharraf, M and Smith, J and Khan, FI and Veitch, B and MacKinnon, S, Assessing offshore emergency evacuation behavior in a virtual environment using a Bayesian Network approach, Reliability Engineering and System Safety, 152 pp. 28-37. ISSN 0951-8320 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 Elsevier Ltd.

DOI: doi:10.1016/j.ress.2016.02.001


In the performance influencing factor (PIF) hierarchy, person-based influencing factors reside in the top level along with machine-based, team-based, organization-based and situation/stressor-based factors. Though person-based PIFs like morale, motivation, and attitude (MMA) play an important role in shaping performance, it is nearly impossible to assess such PIFs directly. However, it is possible to measure behavioral indicators (e.g. compliance, use of information) that can provide insight regarding the state of the unobservable person-based PIFs. One common approach to measuring these indicators is to carry out a self-reported questionnaire survey. Significant work has been done to make such questionnaires reliable, but the potential validity problem associated with any questionnaire is that the data are subjective and thus may bear a limited relationship to reality. This paper describes the use of a virtual environment to measure behavioral indicators, which in turn can be used as proxies to assess otherwise unobservable PIFs like MMA. A Bayesian Network (BN) model is first developed to define the relationship between person-based PIFs and measurable behavioral indicators. The paper then shows how these indicators can be measured using evidence collected from a virtual environment of an offshore petroleum installation. A study that focused on emergency evacuation scenarios was done with 36 participants. The participants were first assessed using a multiple choice test. They were then assessed based on their observed performance during simulated offshore emergency evacuation conditions. A comparison of the two assessments demonstrates the potential benefits and challenges of using virtual environments to assess behavioral indicators, and thus the person-based PIFs.

Item Details

Item Type:Refereed Article
Keywords:evacuation process, human error, human factors, human reliability, offshore emergency, Bayesian networks, human engineering, surveys, virtual reality, behavioral indicators, emergency evacuation, evacuation process, human errors, human reliability
Research Division:Information and Computing Sciences
Research Group:Graphics, augmented reality and games
Research Field:Virtual and mixed reality
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, FI (Professor Faisal Khan)
ID Code:120374
Year Published:2016
Web of Science® Times Cited:51
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-23
Last Modified:2017-11-18

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