Table of Contents Author Guidelines Submit a Manuscript
Journal of Control Science and Engineering
Volume 2018 (2018), Article ID 3473175, 10 pages
Research Article

Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC

1School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China
2Beijing Research and Development Center, Zhongxing Telecommunication Equipment Corporation, Shenzhen, China
3China Railway Communication & Signaling (CRCS) Survey and Design Co., Ltd., Beijing, China

Correspondence should be addressed to Yonghua Zhou; nc.ude.utjb@uohzhy

Received 6 October 2017; Revised 18 February 2018; Accepted 27 February 2018; Published 8 April 2018

Academic Editor: Juan-Albino Méndez-Pérez

Copyright © 2018 Zhihui Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.