Pages 222-227
Year 2024
Issue 3
Volume 13


Author(s): Runkai Hua, Yuming Shi

Doi: 10.7508/aiem.03.2024.222.227

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited


The core of the automatic driving system of urban rail train is to generate the planned speed profile. Based on this, this paper studies the generation algorithm of planned speed profile in order to achieve multiobjective optimization of operating indicators such as safety, punctuality, accurate stopping, energy saving and comfort of automatic driving of urban rail trains. In this paper, offline planning is studied and an offline planning algorithm based on genetic algorithm is proposed. At the same time, online planning is also studied to deal with the unexpected situation of train operation. This paper puts forward an online adjustment method based on genetic algorithm and global optimization algorithm. The simulation results show that both the offline planning algorithm and the online adjustment method can satisfy the basic constraint conditions of safe, punctual and accurate stopping of the train operation. These two methods also reduce the operation energy consumption and improve the operation comfort. Therefore, the methods pro-posed in this paper can achieve multi-objective optimization of the operation index and effectively deal with the unexpected situation of train operation.

Urban Rail, Autonomous Driving, Offline Planning, Online Adjustment, Genetic Algorithm