Effective Traffic Signal Control with Offline-to-Online Reinforcement Learning
Jinming Ma,Feng Wu,Jinming Ma,Feng Wu
Reinforcement learning (RL) has emerged as a promising approach for optimizing traffic signal control (TSC) to ensure the efficient operation of transportation networks. However, the traditional trial-and-error technique in RL is usually impractical in real-world applications. Offline RL, which trains models using pre-collected datasets, is a more practical approach. However, this presents challen...
