A Conflict Detection and Avoidance Strategy for Train Operations Based on Petri Nets

The modeling of train group behaviors is the basis of train operation control on the railway networks. Train operations can be regarded as a typical discrete-event dynamic system. Time colored Petri nets (TCPNs) are a good mathematical tool for describing this type of discrete models and has been widely used in the field of railway transportation. In this paper, a TCPN model is established to describe the train operations of railway networks. The train operations time information is carried by token time assignment. This provides the model basis for analyzing conflict problems during train operations. A conflict detection and avoidance control strategy is developed to check the feasibility of train operation schedule in real time. When a train operation schedule is delayed or generates conflicts by unforeseen events, the strategy can generate a new conflict-free train operation schedule to ensure safe operations of trains. Finally, the correctness and effectiveness of the control strategy are verified by example analyses.