Dynamic reinforcement learning enabled heavy haul train group cooperative control method and system, terminal and medium

• Main Authors: ZHANG RUI, CHEN BIN, REN WANWAN, YANG YINGZE, LI HENG, LI WEI, PENG JUN, YU XIAOQUAN
• Format: Patent
• Language: Chinese; English
• Published: 31.05.2024
• Subjects: ENSURING THE SAFETY OF RAILWAY TRAFFIC; GUIDING RAILWAY TRAFFIC; PERFORMING OPERATIONS; RAILWAYS; TRANSPORTING

The invention discloses a dynamic reinforcement learning enabled heavy-load train group cooperative control method and system, a terminal and a medium. The method comprises the following steps: acquiring real-time operation information of trains in a heavy-load train group; designing a train group cooperative control law according to the deviation between the real-time speed and the reference speed of the train, the speed deviation of the front and rear trains and the distance between the front and rear trains; a reinforcement learning model is established for each train in a train group and is used for dynamically adjusting the weight of a speed deviation item and a distance deviation item in a corresponding train control law, so that the system can learn and adapt to different operation environments in training, and a reward function considers control targets of speed coordination and safe distance, so that the system is more reliable. A penalty function is introduced to process the condition of deviating f