Light Rail Intelligent Dispatching System Based on Reinforcement Learning
The light rail (LR) regarded as the ideal solution for a city that has grown too large for buses, yet cannot be supported by heavy rail with fully dedicated light rails and elevated guide-ways. To improve the efficiency of LR, it is important to develop appropriate dispatching system. The light rail intelligent dispatching system (LRIDS) proposed in this paper is established according to the status of light rail operating including vehicle location and number of passengers, making the best use of reinforcement learning (RL). The algorithm uses a team of RL agents, each of which is responsible for controlling one route. Finally, the developed algorithm is implemented with light rail network of Beijing City. The results demonstrate the power of RL on light rail dispatching problem