mlsanityData to 7 Oct 2026

Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning

arXiv 1704.08883 ↗First posted 28 Apr 2017cs.LGcited by 33

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Abstract (arXiv)

Recent advances in combining deep neural network architectures with reinforcement learning techniques have shown promising potential results in solving complex control problems with high dimensional state and action spaces. Inspired by these successes, in this paper, we build two kinds of reinforcement learning algorithms: deep policy-gradient and value-function based agents which can predict the best possible traffic signal for a traffic intersection. At each time step, these adaptive traffic light control agents receive a snapshot of the current state of a graphical traffic simulator and produce control signals. The policy-gradient based agent maps its observation directly to the control signal, however the value-function based agent first estimates values for all legal control signals. The agent then selects the optimal control action with the highest value. Our methods show promising results in a traffic network simulated in the SUMO traffic simulator, without suffering from instability issues during the training process.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2017.

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Citing papers per year: 2021: 8; 2022: 6; 2023: 7; 2024: 5; 2025: 3; 2026: 4.

33 papers.

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  1. 2025Mixture-of-Personas Language Models for Population Simulationcited by 20
  2. 2021Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Gamescited by 18
  3. 2021Network-wide traffic signal control optimization using a multi-agent deep reinforcement learningcited by 12
  4. 2023UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Controlcited by 12
  5. 2022The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Realitycited by 8
  6. 2021Reinforcement Learning for Traffic Signal Control: Comparison with Commercial Systemscited by 5
  7. 2022Reinforcement learning for traffic signal control in hybrid action spacecited by 5
  8. 2023SocialLight: Distributed Cooperation Learning towards Network-Wide Traffic Signal Controlcited by 5
  9. 2021Multi-intersection Traffic Optimisation: A Benchmark Dataset and a Strong Baselinecited by 4
  10. 2021Design and implementation of an environment for Learning to Run a Power Network (L2RPN)cited by 4
  11. 2022ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learningcited by 3
  12. 2023Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systemscited by 3
21 more
  1. 2024Knowing What Not to Do: Leverage Language Model Insights for Action Space Pruning in Multi-agent Reinforcement Learningcited by 3
  2. 2025A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Controlcited by 3
  3. 2021A Deep Reinforcement Learning Approach for Traffic Signal Control Optimizationcited by 2
  4. 2021Attacking Deep Reinforcement Learning-Based Traffic Signal Control Systems with Colluding Vehiclescited by 2
  5. 2022A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applicationscited by 2
  6. 2023Real-Time Network-Level Traffic Signal Control: An Explicit Multiagent Coordination Methodcited by 1
  7. 2024GuideLight: "Industrial Solution" Guidance for More Practical Traffic Signal Control Agentscited by 1
  8. 2024Reinforcement Learning for Adaptive Traffic Signal Control: Turn-Based and Time-Based Approaches to Reduce Congestioncited by 1
  9. 2024Traffic Co-Simulation Framework Empowered by Infrastructure Camera Sensing and Reinforcement Learningcited by 1
  10. 2025Communication Strategy on Macro-and-Micro Traffic State in Cooperative Deep Reinforcement Learning for Regional Traffic Signal Controlcited by 1
  11. 2026CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Controlcited by 1
  12. 2021Deep Reinforcement Learning-Based Product Recommender for Online Advertisingcited by 0
  13. 2022Cooperative Reinforcement Learning on Traffic Signal Controlcited by 0
  14. 2022Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routingcited by 0
  15. 2023Cooperative Multi-Objective Reinforcement Learning for Traffic Signal Control and Carbon Emission Reductioncited by 0
  16. 2023When Mining Electric Locomotives Meet Reinforcement Learningcited by 0
  17. 2023A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclistscited by 0
  18. 2024An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systemscited by 0
  19. 2026Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learningcited by 0
  20. 2026Momentum Based Reward Design for Low Emission Traffic Signal Controlcited by 0
  21. 2026SIGMA: Symmetry-aware, Intelligent, Geometric, Multi-objective Adaptive Control for Robust, Dependable Traffic Managementcited by 0