Spatio-temporal dual-stage hypergraph MARL for human-centric multimodal corridor traffic signal control

arXiv:2602.17068 · cs.LG, cs.SY, eess.SY · Submitted 2026-02-19 · Read on arXiv

cs.LG, cs.SY, eess.SY

Submitted: 2026-02-19

Updated: 2026-08-26

Project page: https://cityflow-project.github.io

Terminology

• Reinforcement Learning — 57× in this paper · explained in 4 episodes
• Traffic Signal Control — 55× in this paper
• Hypergraph — 54× in this paper · explained in 2 episodes
• Actor — 29× in this paper · explained in 3 episodes
• Deep Reinforcement Learning — 22× in this paper · explained in 2 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Action Space — 11× in this paper · explained in 1 episode
• Q-learning — 11× in this paper · explained in 3 episodes
• Attention Mechanism — 10× in this paper · explained in 2 episodes
• Embeddings — 10× in this paper · explained in 2 episodes
• Spatio-Temporal Dual-Stage Hypergraph — 7× in this paper
• Ablation Studies — 5× in this paper · explained in 1 episode
• Reward Function — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Cooperation — 4× in this paper · explained in 2 episodes
• GNNs — 4× in this paper · explained in 2 episodes
• Adaptive Signal Control — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Convolutional Neural Network — 3× in this paper
• Core — 3× in this paper · explained in 2 episodes
• Deep Q-Network — 3× in this paper
• Heterogeneous Graph — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Artificial Intelligence — 2× in this paper
• Clustering — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Adversarial Network — 2× in this paper
• Graph Convolutional Network — 2× in this paper
• Graph Neural Network — 2× in this paper
• Multi-Agent System — 2× in this paper · explained in 6 episodes
• Spatio-Temporal Dual-Stage Hypergraph-based Multi-Agent Reinforcement Learning — 2× in this paper
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Actor-Critic Framework — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Decentralized Training and Decentralized Execution — 1× in this paper
• Deep Reinforcement Learning (DRL) — 1× in this paper · explained in 2 episodes
• Double Deep Q-Network — 1× in this paper
• Double Dueling Deep Q-Learning Network — 1× in this paper
• Dynamic Spatio-Temporal Hypergraph — 1× in this paper
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Multi-Agent Reinforcement Learning (MARL) — 1× in this paper · explained in 4 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Phase Transitions — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization — 1× in this paper
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Research Review — 1× in this paper · explained in 6 episodes
• Soft Actor-Critic — 1× in this paper
• Soft Actor-Critic (SAC) — 1× in this paper · explained in 2 episodes
• Split Cycle Offset Optimisation Technique — 1× in this paper
• Sydney Coordinated Adaptive Traffic System — 1× in this paper

Sources

• Deep Reinforcement Learning: An Overview
• Human-Centric Traffic Signal Control for Equity: A Multi-Agent Action Branching Deep Reinforcement Learning Approach

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