Development and Assessment of Taxonomy for Performance-Shaping Factors for Railway Operations

Miltos Kyriakidis · Arnab Majumdar · Gudela Grote · Washington Yotto Ochieng

34 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Risk and Safety Analysis Human-Automation Interaction and Safety Transportation Systems and Safety

Abstract

Human performance is a significant contributor to railway incidents and accidents. The literature shows that train drivers, signalers, and controllers most affect network safety. Several studies have been conducted in the field of human factors and human performance in the railway domain to investigate operators' influence on the railway system. However, most studies are based on previous studies from other domains, which are not well suited and can be difficult to apply reliably to railway-specific operations. In light of the current limitations, this paper proposes a new approach referred to as the human performance railway operational index (HuPeROI). HuPeROI aims not only to estimate the human error probability for railway operations but also to propose mitigation strategies to minimize phenomena such as operators' degraded performance. HuPeROI is based on a performance-shaping factors taxonomy designed for the rail industry, referred to as the railway performance-shaping factor (R-PSF) taxonomy. The R-PSF taxonomy was developed on the basis of an extensive literature review of the field of human factors and subsequently validated against the findings derived from the analysis of 179 railway accident and incident reports, as well as targeted interviews with subject matter experts. This paper presents the taxonomy and the underlying theory, as well as the results of the validation process based on the analysis of 179 reports and the assessment of R-PSFs for four different scenarios based on a subject matter expert elicitation process. The R-PSF taxonomy and HuPeROI should enable researchers to address and deal with the effect of degraded performance of railway operators.

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References

2016Managing the Risks of Organizational Accidents 1983Handbook of human-reliability analysis with emphasis on nuclear power plant applications. Final report 1996Probabilistic Risk Assessment and Management for Engineers and Scientists 2017A Guide to Practical Human Reliability Assessment 1998Cognitive reliability and error analysis method 1995A guide to practical human reliability assessment 2003A data-based method for assessing and reducing human error to improve operational performance 2002Development and application of a human error identification tool for air traffic control

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