ATO Operation Optimization Research Based on Artificial Bee Colony Algorithm

Aiming at the safety, efficiency and energy saving of the train ATO operation process, this paper first establishes a multi-objective model from two aspects: the optimization of the train operation strategy and the recommended train speed profile. Secondly, the feasibility of choosing the ABC algorithm as the solution algorithm is demonstrated by comparing the optimization performance of the artificial bee colony algorithm and the particle swarm algorithm, as well as the differential evolution algorithm. Then the ABC algorithm is proposed to solve the maneuvering condition sequence to find the maneuvering condition transition point with the lowest energy consumption under the premise of meeting the operation requirements. Finally, the train operation process is simulated by MATLAB to verify the effectiveness of applying the ABC algorithm to the study of automatic train driving strategy.