A hybrid human and organisational analysis method for railway accidents based on STAMP-HFACS and human information processing. (September 2019)

• Record Type: Journal Article
• Authors: Li, Chenling; Tang, Tao; Chatzimichailidou, Maria Mikela; Jun, Gyuchan Thomas; Waterson, Patrick
• Is Part Of: Applied ergonomics. Volume 79(2019)
• Page Start: 122
• Page End: 142
• Publication Date: 2019-09
• Subjects: Human and organisational factors -- STAMP -- HFACS -- Human information processing -- Accident analysis -- Yong-Wen railway accident; Human engineering -- Periodicals; 620.82
• DOI: 10.1016/j.apergo.2018.12.011
• Languages: English
• ISSNs: 0003-6870

Abstract

Abstract: Safety is a constant priority for the railway industry and there are numerous hazards in and around the rail system which may result in damage to train and environment, human injury and fatalities. Low levels of human and organisational performance have been shown to be a prime cause of railway accidents and a number of accident models and methods have been developed in order to probe deeper into the role played by organisational factors in accident causation. The Systems–Theoretical Accident Modelling and Processes (STAMP) method for example, represents a promising systematic and systemic way of examining sociotechnical systems such as the railway. Another method, the Human Factors Analysis and Classification System (HFACS), based upon Reason's model of human error in an organisational context, has also proved popular as a human factors accident analysis framework. However, human factors elements are still somewhat limited and under-specified and these managerial and social issues within an organisation are simply regarded as sources of failure in the control constraints of STAMP. HFACS likewise, categorises accident data rather than analysing it in more depth. In this context, a hybrid human and organisational analysis method based on HFACS-STAMP (HFACS-STAMP method for railway accidents, HS-RAs) is proposed to identify and analyse human and organisational factors involved in railway accidents. Using the categories of human errors derived from HFACS and the structured systematic analysis process of STAMP, the HS-RAs method provides a mechanism by which active failures can promulgate across organisations and give a systemic analysis of human error in accidents. Combined with human information processing, the HS-RAs method gives a detailed causal analysis of human errors from receiving information to implement control actions. At last, the HS-RAs method is demonstrated using a case study of the 2011 Yong-Wen railway collision. A number of prominent accident causes of human factors are revealed and necessary countermeasures are proposed to avoid the recurrence of similar accidents. The HFACS-STAMP hybrid method has several advantages and can contribute to railway safety by providing a detailed analysis of the role of human error in railway accidents. Highlights: A hybrid human and organisational analysis method is combined HFACS and STAMP. STAMP human and organisational error taxonomies have been extended by HFACS. The analysis is based on human information processing from human to organisation. Analysis presents traceable process of human and organisational factors. China Yong-wen railway accident was analysed by HS-RAs method.