Evaluation of Linear-Quadratic Optimal Control in Automatic Train Operation (ATO) during Unplanned Event

Automatic Train Operation (ATO) systems have become essential in urban rail networks with the aim of minimizing human error, improving punctuality, and optimizing energy consumption. However, unplanned incidents, such as post-automatic train protection (ATP) or driver interventions, reduce the performance of the designed ATO. This study aims to evaluate the ability of the optimal quadratic control strategy to deal with ATO during unplanned events, including driver intervention. By simulating various scenarios and analyzing key performance indicators, this research provides information on the robustness, adaptability, and overall contribution of the strategy to the reliability of ATO systems. The findings inform improvements in control algorithms, ultimately improving the resilience and efficiency of urban rail systems.