An Intelligent System for train overtaking using distributed coordination

This paper presents an Intelligent System, based on a dynamic time table definition, which coordinates the overtaking process of trains traveling in the same section of a railroad through a crossing loop. Each train involved on the overtaking process is represented by an intelligent agent capable of taken his actions based on his relative position on the railroad and his scheduling. The main goal of these agents is to react during the driving to avoid that more than one train stays on the same section of track at the same time (resource concurrency), and also to avoid unnecessary halts. The agents actions are previously defined, based on a simulation of the journey to the next crossing loop. For each stretch the agents selects another agent to be his coordinator, based on specific criteria. Then, each agent creates its action policy based on his local view and the data of the coordinator. The coordinator receives the actions and validates them generating a time table containing the actions for the next stretch, called dynamic time table. The definition of the action policy occurs dynamically, as each agent simulates the next step of the journey virtually and takes the decisions at runtime. The communication between the agents is done through the environment, where each agent updates his relative location and time. The main goal of the Intelligent System is the coordination of the trains focusing on reducing fuel consumption and also reducing the travel time. This is chased avoiding unnecessary halts, collisions of the trains and driving the trains with a Cruising Speed. The best simulations results achieved a 33.72% reduction in fuel consumption and a 33.30% reduction on travel time.