mlsanityData to 7 Oct 2026

Using a Deep Reinforcement Learning Agent for Traffic Signal Control

arXiv 1611.01142 ↗First posted 3 Nov 2016cs.LG cs.SY eess.SYcited by 26

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Abstract (arXiv)

Ensuring transportation systems are efficient is a priority for modern society. Technological advances have made it possible for transportation systems to collect large volumes of varied data on an unprecedented scale. We propose a traffic signal control system which takes advantage of this new, high quality data, with minimal abstraction compared to other proposed systems. We apply modern deep reinforcement learning methods to build a truly adaptive traffic signal control agent in the traffic microsimulator SUMO. We propose a new state space, the discrete traffic state encoding, which is information dense. The discrete traffic state encoding is used as input to a deep convolutional neural network, trained using Q-learning with experience replay. Our agent was compared against a one hidden layer neural network traffic signal control agent and reduces average cumulative delay by 82%, average queue length by 66% and average travel time by 20%.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Nov 2016.

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Cited by year (2026 to 7 Oct)

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

26 papers.

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  1. 2025Mixture-of-Personas Language Models for Population Simulationcited by 20
  2. 2022SafeLight: A Reinforcement Learning Method toward Collision-free Traffic Signal Controlcited by 15
  3. 2021Applications of deep learning in traffic congestion detection, prediction and alleviation: A surveycited by 14
  4. 2024TransGPT: Multi-modal Generative Pre-trained Transformer for Transportationcited by 13
  5. 2021Network-wide traffic signal control optimization using a multi-agent deep reinforcement learningcited by 12
  6. 2022The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Realitycited by 8
  7. 2023Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Controlcited by 7
  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. 2026Adaptive traffic signal control optimization using a novel road partition and multi-channel state representation methodcited by 4
  11. 2021Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systemscited by 3
  12. 2021A Deep Reinforcement Learning Approach for Traffic Signal Control Optimizationcited by 2
14 more
  1. 2021Transformer-based Map Matching Model with Limited Ground-Truth Data using Transfer-Learning Approachcited by 2
  2. 2022A Critical Review of Traffic Signal Control and A Novel Unified View of Reinforcement Learning and Model Predictive Control Approaches for Adaptive Traffic Signal Controlcited by 1
  3. 2023Traffic Light Control with Reinforcement Learningcited by 1
  4. 2024Reinforcement Learning for Adaptive Traffic Signal Control: Turn-Based and Time-Based Approaches to Reduce Congestioncited by 1
  5. 2025Communication Strategy on Macro-and-Micro Traffic State in Cooperative Deep Reinforcement Learning for Regional Traffic Signal Controlcited by 1
  6. 2026CoordLight: Learning Decentralized Coordination for Network-Wide Traffic Signal Controlcited by 1
  7. 2021A Methodology for the Development of RL-Based Adaptive Traffic Signal Controllerscited by 0
  8. 2022Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routingcited by 0
  9. 2023A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclistscited by 0
  10. 2024Exploring the impact of traffic signal control and connected and automated vehicles on intersections safety: A deep reinforcement learning approachcited by 0
  11. 2024Using Petri Nets as an Integrated Constraint Mechanism for Reinforcement Learning Taskscited by 0
  12. 2024An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systemscited by 0
  13. 2025HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Controlcited by 0
  14. 2026Learning to Move Cities: Deep Meta-Models and Reinforcement Policies for Calibration and Control in Urban Networkscited by 0