A Fully Data-Driven Approach for Realistic Traffic Signal Control Using Offline Reinforcement Learning

no code implementations • 27 Nov 2023 • Jianxiong Li, Shichao Lin, Tianyu Shi, Chujie Tian, Yu Mei, Jian Song, Xianyuan Zhan, Ruimin Li

Specifically, we combine well-established traffic flow theory with machine learning to construct a reward inference model to infer the reward signals from coarse-grained traffic data.

Offline RL Reinforcement Learning (RL)