A Study on a Methodology for Selecting Optimal Alternatives for Train Operation Safety Based on the Bow-Tie Model and Optimization Algorithms

Railway accidents are low-frequency, high-consequence events. Railway operators must balance safety investment costs and accident risk under limited budgets and resources. This study formulates railway accident risk as a function of occurrence frequency and consequence severity to identify optimal combinations of safety measures. A Bow-Tie model is developed to construct accident scenarios and evaluate outcomes resulting from combinations of system successes and failures. The optimization considers various safety measures, including automatic train control (ATC), and the presence or absence of a driver. The results show that an optimal combination of safety measures can minimize costs while satisfying the allowable risk constraint.