Speed Curve Optimization of High-speed Flying Train Based on Improved Genetic Algorithm

High-speed Flying Train (HFT) with a maximum speed of 4,000km/h can greatly improve the efficiency of travel. The automatic operation control of the train is a very complicated process, requiring high safety but also high comfort and low energy consumption. HFT is automatically controlled using high-speed mode curves, which is a multi-objective optimization problem. To address this problem, this paper proposes an improved genetic algorithm to optimize the multi-objective control model for automatic operating curve. First, a multi-objective model of operation control is established, which is based on the characteristics of HFT. Then, an automatic operation control algorithm based on improved genetic algorithm is developed for HFT, adding a sort operator to make it more suitable for the operation control system. Finally, the algorithm is validated by the simulation on a 50km route with speed limits. The results show that the optimized automatic operation curve can meet the above-mentioned indexes, which proves the effectiveness of the algorithm.