Traffic Signal Control

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Overview

Traffic signal control decides which movements receive green and for how long, aiming to keep traffic moving while serving pedestrians, transit, and emergency vehicles. Methods range from fixed-time, actuated, and pressure-based rules to deep and multi-agent reinforcement learning, often using graph or attention models to coordinate intersections. Recent approaches also use camera-based sensing, traffic prediction, and language or vision-language models, typically paired with simulation feedback and safety constraints. A central challenge is ensuring that gains seen in simulation transfer to real networks and unseen demand, while balancing efficiency with fairness, safety, and emissions.

Latest papers

CardsList

39 papers4 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. CROSS: A Mixture-of-Experts Reinforcement Learning Framework for Generalizable Large-Scale Traffic Signal Control

    Mar 26, 2026Xibei Chen, Yifeng Zhang, Yuxiang Xiao +3Traffic Signal ControlIntelligent Transportation Systems

    Department of Mechanical Engineering, National University of Singapore, Singapore · Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

  2. CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Control

    Mar 25, 2026Yifeng Zhang, Harsh Goel, Peizhuo Li +3Traffic Signal ControlMulti-Agent Coordination

    Department of Mechanical Engineering, National University of Singapore · Chandra Department of Electrical and Computer Engineering, The University of Texas at Austin · Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

  3. LATS: Large Language Model Assisted Teacher-Student Framework for Multi-Agent Reinforcement Learning in Traffic Signal Control

    Mar 25, 2026Yifeng Zhang, Peizhuo Li, Tingguang Zhou +2Traffic Signal ControlLLM-Guided RL

    Department of Mechanical Engineering, National University of Singapore

  4. Emergency Preemption Without Online Exploration: A Decision Transformer Approach

    Mar 20, 2026Haoran Su, Hanxiao Deng, Yandong SunTraffic Signal ControlDecision Transformer

    New York University · University of California, Berkeley

  5. Data-driven generalized perimeter control: Zürich case study

    Mar 17, 2026Alessio Rimoldi, Carlo Cenedese, Alberto Padoan +2Data-Driven ControlTraffic Signal Control

    Automatic Control Laboratory, ETH Zürich · Delft Center for Systems and Control, TU Delft · Dep. of Electrical and Computer Engineering, UBC

  6. Evaluating the Robustness of Reinforcement Learning based Adaptive Traffic Signal Control

    Mar 16, 2026Dickens Kwesiga, Angshuman Guin, Khaled Abdelghany +1Traffic Signal ControlReinforcement Learning

    Research Engineer, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA, 30332 · Principal Research Engineer, School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA, 30332 · Professor, Department of Civil and Environmental Engineering, Southern Methodist University, Dallas, USA, 75205 +1

  7. Video Detector: A Dual-Phase Vision-Based System for Real-Time Traffic Intersection Control and Intelligent Transportation Analysis

    Mar 16, 2026Mustafa Fatih Şen, Halûk Gümüşkaya, Şenol PazarIntelligent Transportation SystemsVideo Object Detection

    Ankageo Co. Ltd., Yıldız Technical University, İkitelli Technopark, 34220 Istanbul, Türkiye · Department of Computer Engineering, Istanbul Arel University, 34537 Istanbul, Türkiye · Department of Electrical and Electronics Engineering, Biruni University, 34015 Istanbul, Türkiye

  8. HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning

    Feb 21, 2026Ziyan Zhang, Changxin Wan, Peng Hao +5Intelligent Transportation SystemsTraffic Signal Control

    College of Engineering, Center for Environmental Research and Technology, University of California at Riverside, Riverside, CA, 92507. · InfoTech Labs, Toyota Motor North America, Mountain View, CA, 94043.

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

    Feb 19, 2026Xiaocai Zhang, Neema Nassir, Milad HaghaniTraffic Signal ControlMulti-Agent Reinforcement Learning

    Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, VIC 3010, Australia