Train Trajectory Optimization for High-speed Railways under Constraints of Successive Trains

A train trajectory is used to ensure punctual and efficient train operation. When disturbances occur, trains will deviate from the planned operations. To reduce the impact of delayed trains on the operation of subsequent trains, this paper proposes a train trajectory optimization model for high-spee...

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Bibliographic Details
Main Authors: Ning, Lingbin, Zhou, Min, Wu, Wei, Zhang, Zixuan, Liu, Changqing, Dong, Hairong
Format: Conference Proceeding
Language:English
Subjects:
Automation
Block signalling
Delay Recovery
Delays
Energy consumption
Energy efficiency
Minimum Running Time
Numerical models
Rail transportation
Successive Trains Constraints
Train Trajectory Optimization
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Summary:A train trajectory is used to ensure punctual and efficient train operation. When disturbances occur, trains will deviate from the planned operations. To reduce the impact of delayed trains on the operation of subsequent trains, this paper proposes a train trajectory optimization model for high-speed railways considering of constraints of successive trains. The operational constraint of ATP (automatic train protection system) profile based on a block section that the previous train occupied is introduced in the model to guarantee the safe separation for the operation of multiple trains. Based on a quasi-moving block signaling system, the train operation scenarios with different times when the following trains receive the changed operation conditions are studied. An approach based on a genetic algorithm (GA) is applied to optimize the train trajectory for minimizing running time and energy consumption. Four numerical experiments are conducted on the adapted data of a section from the Beijing-Shanghai high-speed railway. The optimized trajectories can be obtained, which could maintain the scheduled arrival headway as much as possible to recover delays while saving energy consumption by eliminating unnecessary braking.
ISSN:2688-0938
DOI:10.1109/CAC53003.2021.9728527