The importance of the human factor in decision-making in rail transport

Abstract

This study presents a railway-specific bibliometric and thematic mapping analysis of research on the human factor in railway decision-making. Using the Web of Science Core Collection, a structured screening procedure was applied to publications indexed between 2014 and 2024. After successive filtering stages, 27 peer-reviewed, railway-focused articles were retained for the railway-specific bibliometric mapping, complemented by 2 methodological references from adjacent high-risk or decision-analytic domains to contextualize underexplored aspects of multi-criteria prioritization and cognitive-error analysis. Bibliometric mapping was conducted with VOSviewer to examine keyword co-occurrence structures and co-authorship networks. The analysis identifies three thematic clusters: formal decision-support and multi-criteria modeling frameworks, operational human performance and safety-related cognitive processes, and integrative socio-technical system perspectives. The findings suggest that automation reshapes rather than eliminates human cognitive demands, reinforcing the importance of situational awareness, workload regulation, and trust calibration in railway operations. The study contributes by moving beyond descriptive mapping toward a railway-specific socio-technical interpretation of how decision-support models, automation, and operator cognition intersect. It also highlights a structural gap: formal railway decision-support models rarely incorporate dynamic cognitive-performance indicators such as workload, fatigue, situational awareness, trust calibration, and human reliability. The findings outline implications for human-centered automation governance and reliability-informed safety management