TY - GEN
T1 - Trajectory Planning of Train Platoons in Urban Rail Networks
T2 - 28th International Conference on Intelligent Transportation Systems, ITSC 2025
AU - Yu, Runhan
AU - Yin, Jiateng
AU - Zheng, Wei
AU - Li, Kaicheng
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - With the application of virtual coupling technology (VCT) in railways, the concept of train platoons - where multiple train units operate with extremely short inter-unit distances - has gained significant research attention. A key challenge in this context is the optimal design of train platoon trajectories to ensure both efficiency and safety, given the highly nonlinear characteristics of railway systems (e.g., track resistance, safety constraints for train following). To address this, this paper develops a mixed-integer linear programming (MILP) model based on a time-indexed formulation to generate trajectories for two groups of train units merging at a bottleneck zone. The model also incorporates binary variables to determine the optimal merging order and enforces safety constraints through a set of nonlinear conditions tailored for a moving block system. To facilitate tractable optimization, we propose linearization techniques to transform nonlinear terms into linear expressions. Case studies using real-world data from the Beijing Metro Yizhuang Line demonstrate the effectiveness and applicability of the proposed approach.
AB - With the application of virtual coupling technology (VCT) in railways, the concept of train platoons - where multiple train units operate with extremely short inter-unit distances - has gained significant research attention. A key challenge in this context is the optimal design of train platoon trajectories to ensure both efficiency and safety, given the highly nonlinear characteristics of railway systems (e.g., track resistance, safety constraints for train following). To address this, this paper develops a mixed-integer linear programming (MILP) model based on a time-indexed formulation to generate trajectories for two groups of train units merging at a bottleneck zone. The model also incorporates binary variables to determine the optimal merging order and enforces safety constraints through a set of nonlinear conditions tailored for a moving block system. To facilitate tractable optimization, we propose linearization techniques to transform nonlinear terms into linear expressions. Case studies using real-world data from the Beijing Metro Yizhuang Line demonstrate the effectiveness and applicability of the proposed approach.
KW - Mixed-integer linear programming
KW - Train speed management
KW - Trajectory planning
KW - Virtual coupling
UR - https://www.scopus.com/pages/publications/105036964942
U2 - 10.1109/ITSC60802.2025.11423828
DO - 10.1109/ITSC60802.2025.11423828
M3 - 会议稿件
AN - SCOPUS:105036964942
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1073
EP - 1078
BT - IEEE Intelligent Transportation Systems Conference, ITSC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 18 November 2025 through 21 November 2025
ER -