Abstract

Purpose: This study systematically analyzes the characteristics of human error accidents among railway trackside workers to identify dominant patterns and propose safety management strategies. Research design, data and methodology: This quantitative study analyzed 10 years (2012-2021) of KORAIL accident records. Incidents were classified using the Human Error Analysis and Reduction (HEAR) framework. The analysis primarily involved descriptive statistics to examine the distribution of error types, causes, and outcomes, with a supplementary job analysis. Results: The analysis revealed that incidents in the Facilities sector were twice as frequent as in the Electrical sector. The most prevalent error type was Decision-Making Error (56.9%), showing accidents primarily stem from flawed judgments and procedural violations rather than simple execution slips. Worker injury was the most common outcome, and accidents were concentrated in specific high-risk tasks like turnout maintenance and signal equipment inspection. Conclusions: This study concludes that human errors in trackside operations are systemic issues rooted in decision-making and procedural compliance. The findings support multi-faceted countermeasures, including enhanced scenario-based training, adopting advanced safety technologies to reduce cognitive load, improving fatigue management through scheduling, and robust safety feedback systems.