Adjustment of Train Interval Time Based on Dynamic Programming Algorithm

The optimization of the tracking interval time is the main research field for improving the railway transportation capacity. At present, tracking interval time of high-speed railway has basically reached the 5-minute or 3-minute in China. To further shorten the train tracking interval time, this paper selects the line gradient parameter as the optimization parameter to establish the multi-stage decision model based on dynamic programming, and uses COADP algorithm (an improved algorithm based on dynamic programming) to optimize the braking distance of the train. Basing on Bellman's theorem, the COADP algorithm optimizes the line gradient reduction program and solves the phase variable optimal solution, state variable optimal solution, optimal decision sequence, optimal index function and optimal value function. By obtaining the optimal objective function of the EMU braking distance, the algorithm optimizes the tracking interval time of EMU and enhances the high-speed railway transportation capacity.