A Driving Strategy Based Integrated Rescheduling Model for High-Speed Railway by Using the Parallel Intelligent Method

Abstract

With the development of high-speed railway automatic train operation(ATO) systems, the automatic operation system gradually replaces the work and responsibilities of traditional drivers. Under the parallel intelligent method, a real-time rescheduling model combined ATO driving strategy is proposed to restore the train operation from the delay caused by disturbance. The objective of the proposed model is to minimize the total delay when disturbance occurs. We use a commercial solver to solve our model. Finally, two numerical cases are carried out to verify the effectiveness of the proposed model.