A Real-time Speed Profile Planning Algorithm for Freight Trains Based on Neural Network - ZHU Yuqing; BAI Baoxue; CHEN Honghui; CHEN Nankuang; WANG Qingyuan (Kongzhi Yu Xinxi Jishu)
In order to reduce driver’s operation difficulty and improve transportation efficiency, this paper proposed a real-time speed profile planning algorithm based on neural network to guide the freight train driver’s operation. Firstly, the algorithm determines the input and output forms of the neural network model by analyzing the optimization results of the quadratic programming, and then trains the neural network model with a large number of optimization results as sample data to determine the structure and weights of the model. Finally, the trained model is combined with the input construction module and the traction calculation module to design the entire algorithm flow. In order to verify the correctness, efficiency and energy-saving of the scheduling algorithm, the virtual complex line test and the actual line test were simulated respectively. The results show that the speed profile calculated by this algorithm is identical with the speed profile calculated by the offline global planning algorithm based on quadratic programming, meanwhile, the calculation time can meet real-time requirements. The energy-saving rate is 5.98% as compared to the operation results of experienced drivers.