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Energy-efficient receding horizon trajectory planning of high-speed trains using real-time traffic information
DefengHE,LongZHOU,ZheSUN
0
(College of Information Engineering, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China)
摘要:
Optimal trajectory planning of high-speed trains (HSTs) aims to obtain such speed curves that guarantee safety, punctuality, comfort and energy-saving of the train. In this paper, a new shrinking horizon model predictive control (MPC) algorithm is proposed to plan the optimal trajectories of HSTs using real-time traffic information. The nonlinear longitudinal dynamics of HSTs are used to predict the future behaviors of the train and describe variable slopes and variable speed limitations based on real-time traffic information. Then optimal trajectory planning of HSTs is formulated as the shrinking horizon optimal control problem with the consideration of safety, punctuality, comfort and energy consumption. According to the real-time position and running time of the train, the shrinking horizon is updated to ensure the recursive feasibility of the optimization problem. The optimal speed curve of the train is computed by online solving the optimization problem with the Radau Pseudo-spectral method (RPM). Simulation results demonstrate that the proposed method can satisfy the requirements of energy efficiency and punctuality of the train.
关键词:  High-speed trains, model predictive control, optimal trajectory planning, Radau Pseudo-spectral method
DOI:https://doi.org/10.1007/s11768-020-0001-x
基金项目:This work was supported by the National Natural Science Foundation of China (No. 61773345) and the Zhejiang Provincial Natural Science Foundation (No. LR17F030004).
Energy-efficient receding horizon trajectory planning of high-speed trains using real-time traffic information
Defeng HE,Long ZHOU,Zhe SUN
(College of Information Engineering, Zhejiang University of Technology, Hangzhou Zhejiang 310023, China)
Abstract:
Optimal trajectory planning of high-speed trains (HSTs) aims to obtain such speed curves that guarantee safety, punctuality, comfort and energy-saving of the train. In this paper, a new shrinking horizon model predictive control (MPC) algorithm is proposed to plan the optimal trajectories of HSTs using real-time traffic information. The nonlinear longitudinal dynamics of HSTs are used to predict the future behaviors of the train and describe variable slopes and variable speed limitations based on real-time traffic information. Then optimal trajectory planning of HSTs is formulated as the shrinking horizon optimal control problem with the consideration of safety, punctuality, comfort and energy consumption. According to the real-time position and running time of the train, the shrinking horizon is updated to ensure the recursive feasibility of the optimization problem. The optimal speed curve of the train is computed by online solving the optimization problem with the Radau Pseudo-spectral method (RPM). Simulation results demonstrate that the proposed method can satisfy the requirements of energy efficiency and punctuality of the train.
Key words:  High-speed trains, model predictive control, optimal trajectory planning, Radau Pseudo-spectral method