Autonomous routing research based on vehicle-centralized train control system

Abstract

In vehicle-centralized train control design, the routing function is transferred from interlocking equipment to vehicle, which asks for the ability of train to schedule feasible route autonomously. This paper describes an autonomous routing schedule (ARS) model based on graph theory. Firstly, by converting key elements of rail network into directed graph nodes and marking the weights of arcs based on section transit time’s prediction, a topological graph model reflecting railway structure’s characteristic is set up. According to the graph model, a heuristic algorithm is used to search the feasible route with shortest transit time. Considering the limitation of rail state’s information gathered by trains in decentralized control design, arc’s weight (the prediction of transit time in rail section) is updated in real time based on the communication between trains so that the routing schedule can be dynamically adjusted based on section’s availability. The computational tests are performed on Beijing Daxing Airport Station. The result shows the feasibility of model in searching route with reasonable transit time. It’s potential for rerouting based on disturbances and resolve delays is also analyzed.