Incorporating individual differences in human reliability analysis: An extension to the virtual experimental technique
Artikel i vetenskaplig tidskrift, 2018

The data required to perform Human Reliability Analysis (HRA) for emergency conditions are not readily available and are difficult to retrieve from accident investigations. In the absence of emergency conditions data, the conventional approach of gathering data for HRA is using expert judgment. Expert judgment often suffers from uncertainty, subjectivity, and incompleteness, which makes the reliability of this data collection technique questionable. A more recent approach is to collect data by conducting experiment in virtual environments with human subjects. Though virtual experimental technique addresses the issues of uncertainty, subjectivity, and incompleteness, it still does not consider individual differences while assigning the influence of different factors on human performance. This paper proposes to advance the virtual experimental technique by enabling the consideration of individual differences. An experiment using virtual environment was done to observe performances of 36 individuals during offshore emergency evacuation. By integrating the data collected from the virtual environment into an HRA model, the reliability of each individual was assessed. Sensitivity analysis was then performed to identify the most influential factors that contributed to failure in emergency conditions. This analysis can help identify specific weaknesses that a participant might have. For example, if a participant is found to be more sensitive to a particular factor, then training scenarios with different variations of the factor can be provided to the participant until an accepted level of competency is reached. Identification of a weakness can be combined with adaptive human factor training so that each individual can obtain competence more quickly.

Virtual environment

Human factors

Safety training

Adaptive training

Human reliability


Mashrura Musharraf

Memorial University of Newfoundland

Jennifer Smith

Memorial University of Newfoundland

Faisal Khan

Memorial University of Newfoundland

Brian Veitch

Memorial University of Newfoundland

Scott MacKinnon

Chalmers, Mekanik och maritima vetenskaper, Maritima studier

Safety Science

0925-7535 (ISSN) 18791042 (eISSN)

Vol. 107 216-223


Annan data- och informationsvetenskap

Tillämpad psykologi

Bioinformatik och systembiologi



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