Deep Reinforcement Learning for Energy-efficient Train Operation of Automatic Driving

Abstract

With the rapid development of urban rail transit and the improvement of machine learning technology, the application of deep reinforcement learning to train operation control has become a research hotspot. In this paper, the train operation control method based on deep reinforcement learning is established for urban rail transit. A subway line is employed to perform simulation, and the developed method is verified. The simulation results revealed the applicability and practicability of the method.