An accident causation model for the railway industry: Application of the model to 80 rail accident investigation reports from the UK

• Published in: Safety science Vol. 60; pp. 57 - 68
• Main Authors: Kim, Dong San, Yoon, Wan Chul
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier India Pvt Ltd 01.12.2013; Elsevier
• Subjects: Accident analysis; Accident causation model; Accident sequence; Applied sciences; Biological and medical sciences; Exact sciences and technology; Ground, air and sea transportation, marine construction; Medical sciences; Miscellaneous; Public health. Hygiene; Public health. Hygiene-occupational medicine; Rail; Railway safety; Railway transportation and traffic; United Kingdom; Europe; British Isles; Accident sequence; Rail; Accident causation model; Railway safety; Accident analysis; Railway; Railway industry; Accident; Cause; Traffic safety; Models; Rail transportation; Rail traffic; Application
• ISSN: 0925-7535; 1879-1042
• DOI: 10.1016/j.ssci.2013.06.010

•An accident causation model for the railway industry is proposed.•The model is applied to 80 railway accident reports from the UK.•Its usefulness in explaining how an accident/incident or near miss occurs is proved.•Several interesting relations between the model’s components are revealed.•Results from this study can be transferred to other safety-critical domains. Although many models of accident causation have been developed and have contributed to improving our understanding of how accidents occur, relatively few published studies have evaluated such models with accident data. An accident causation model for the railway industry, proposed earlier by the authors, was reviewed, and 80 railway accident investigation reports from the UK were analyzed to evaluate the model’s usefulness and examine the presence of any significant correlations between the components of the model. Overall, it was proved that our model is useful in explaining how a railway accident/incident or near miss occurs and that every component of the model is essential. Human failures, technical failures, and external intrusions were all observed in about one half of the accidents. Human responses were observed in most cases, and responses by protective systems were also reported in many cases. The frequencies of other components such as feedback loops were not negligible. The analysis also revealed several interesting relationships between the components, some of which have implications for preventing or reducing the number of railway accidents and incidents. The results from this study can be transferred to other safety-critical domains such as aviation, maritime, and medicine.