Real-Time Network-Level Traffic Signal Control: An Explicit Multiagent Coordination Method

no code implementations • 15 Jun 2023 • Wanyuan Wang, Tianchi Qiao, Jinming Ma, Jiahui Jin, Zhibin Li, Weiwei Wu, Yichuan Jian

Key to the challenge of TSC includes 1) the essential of real-time signal decision, 2) the complexity in traffic dynamics, and 3) the network-level coordination.

Reinforcement Learning (RL)

Effective Multimodal Reinforcement Learning with Modality Alignment and Importance Enhancement

no code implementations • 18 Feb 2023 • Jinming Ma, Feng Wu, Yingfeng Chen, Xianpeng Ji, Yu Ding

Specifically, we observe that these issues make conventional RL methods difficult to learn a useful state representation in the end-to-end training with multimodal information.

reinforcement-learning Reinforcement Learning (RL)

Feudal Multi-Agent Reinforcement Learning with Adaptive Network Partition for Traffic Signal Control

no code implementations • 27 May 2022 • Jinming Ma, Feng Wu

To do this, we propose two approaches: one is directly to use graph neural network (GNN) to generate the network partition, and the other is to use Monte-Carlo tree search (MCTS) to find the best partition with criteria computed by GNN.

Multi-agent Reinforcement Learning reinforcement-learning +1