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

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.