Real-time dispatching optimization of high-speed rail based on model predictive control under partial interruption

The high-speed railway network has a huge structure and interruption problems occur from time to time. The automatic and intelligent train operation adjustment is of great significance to assist dispatchers in decision-making. In this paper, the mixed integer linear programming (MILP) model was established in the case of the failure of one-way passing capacity in local network interval, and the model predictive control (MPC) algorithm was introduced into the study of railway interruption problem, so as to reduce the impact of interruption on train operation and effectively shorten the calculation time of this large-scale problem. Taking into account the uncertainty of the scene in the case of interruption, online optimization was realized through the feedback control algorithm. In addition, we studied the spread of the delay caused by a partial interruption of a line to adjacent lines. The intersection of Beijing-Shanghai high-speed rail and Tianjin-Qin high-speed rail was employed as a case to verify its effectiveness.