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Application of Human Factors Analysis and Classification System (HFACS) to UK rail safety of the line incidents

Lookup NU author(s): Dr David GolightlyORCiD


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© 2016 Elsevier Ltd Minor safety incidents on the railway cause disruption, and may be indicators of more serious safety risks. The following paper aimed to gain an understanding of the relationship between active and latent factors, and particular causal paths for these types of incidents by using the Human Factors Analysis and Classification System (HFACS) to examine rail industry incident reports investigating such events. 78 reports across 5 types of incident were reviewed by two authors and cross-referenced for interrater reliability using the index of concordance. The results indicate that the reports were strongly focused on active failures, particularly those associated with work-related distraction and environmental factors. Few latent factors were presented in the reports. Different causal pathways emerged for memory failures for events such a failure to call at stations, and attentional failures which were more often associated with signals passed at danger. The study highlights a need for the rail industry to look more closely at latent factors at the supervisory and organisational levels when investigating minor safety of the line incidents. The results also strongly suggest the importance of a new factor – operational environment – that captures unexpected and non-routine operating conditions which have a risk of distracting the driver. Finally, the study provides further demonstration of the utility of HFACS to the rail industry, and of the usefulness of the index of concordance measure of interrater reliability.

Publication metadata

Author(s): Madigan R, Golightly D, Madders R

Publication type: Article

Publication status: Published

Journal: Accident Analysis and Prevention

Year: 2016

Volume: 97

Pages: 122-131

Print publication date: 01/12/2016

Online publication date: 10/09/2016

Acceptance date: 19/08/2016

ISSN (print): 0001-4575

ISSN (electronic): 1879-2057

Publisher: Elsevier Ltd


DOI: 10.1016/j.aap.2016.08.023

PubMed id: 27620858


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