Models and algorithms of conflict detection and scheduling optimization for high-speed train operations based on MPC

Abstract

The high-speed train with high transport speed and punctuality rate has become a leading tool of daily traveling. Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. They are implemented under the mechanism of model predictive control (MPC) over the rolling prediction horizon. A train movement prediction model with conflict resolution is established. The mechanism of conflict detection and scheduling optimization is implemented through a case study. The simulation results demonstrate the effectiveness of the proposed mechanism.