Train Tracking Interval Optimization Method Based on Cooperative Perception of Train Speed and Communication States

With the increasing passenger of High-Speed Railway (HSR), the Line Passing Capacity (LPC) can not meet the transportation demand. The Train Tracking Interval (TTI) is an important parameter for evaluating LPC. The traditional Train Control System (TCS) considers the transmission latency as a fixed constant measured in the worst environment, which limits the performance of TTI. In this paper, a TTI optimization method is proposed to increase the LPC based on Stochastic Network Calculus (SNC). Different with the existing TCS, SNC can calculate the transmission latency as a dynamic value to reflect the complexity of operation environment and speed. Therefore, a smaller and proper transmission latency can be obtained while guaranteeing the operation safety. In addition, the train operation mode adopts the moving block system to further decrease the TTI which is realized by train-to-train communication. The simulation results illustrate the changing trend of transmission latency depending on the dynamic operation speed and environment. The LPC can be increased by 2% to 9%. Meantime, the control algorithm can prove the efficiency and availability of the TTI adjustment method.