Simulation of High-Speed Railway Train Operation Based on Cellular Automata

To accurately analyze the dynamic characteristics of train operations under different scenarios and provide valuable information for avoiding train delays, an improved cellular automata model is presented to simulate train operations under different scenarios. We first build a CA model under the quasi-moving block system by combining the characteristics of railway lines and equipment in stations, and analyze the speed and location update rules of trains and the rules of trains entering and leaving the station. We propose innovation by decomposing the train route into two parts: the turnout group and the track, which effectively solves the train route conflict problem in the model and makes the model more realistic. Then we select an actual high-speed railway line for simulation under four scenarios. The results show that the simulation is consistent with the actual operation of the railway line, and the model can objectively and reasonably reproduce the dynamic characteristics of high-speed train operation. We analyze the relationship between the total train delay time and the equipment failure duration. The results indicate that the total train delay time grows in power with the equipment failure duration, and the redundancy time can help to mitigate the growth of train delays.