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Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey

arXiv 2005.00935 ↗First posted 2 May 2020cs.LG cs.MA cs.SYcited by 94

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Abstract (arXiv)

Latest technological improvements increased the quality of transportation. New data-driven approaches bring out a new research direction for all control-based systems, e.g., in transportation, robotics, IoT and power systems. Combining data-driven applications with transportation systems plays a key role in recent transportation applications. In this paper, the latest deep reinforcement learning (RL) based traffic control applications are surveyed. Specifically, traffic signal control (TSC) applications based on (deep) RL, which have been studied extensively in the literature, are discussed in detail. Different problem formulations, RL parameters, and simulation environments for TSC are discussed comprehensively. In the literature, there are also several autonomous driving applications studied with deep RL models. Our survey extensively summarizes existing works in this field by categorizing them with respect to application types, control models and studied algorithms. In the end, we discuss the challenges and open questions regarding deep RL-based transportation applications.

Key facts. Cited by 94 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 May 2020.

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Citing papers per year: 2021: 11; 2022: 14; 2023: 21; 2024: 12; 2025: 32; 2026: 4.

94 papers.

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  1. 2021Efficient Deep Reinforcement Learning with Imitative Expert Priors for Autonomous Drivingcited by 46
  2. 2025Towards General-Purpose Model-Free Reinforcement Learningcited by 40
  3. 2023Prompt to Transfer: Sim-to-Real Transfer for Traffic Signal Control with Prompt Learningcited by 36
  4. 2025A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Modelscited by 36
  5. 2021Reinforcement Learning for Ridesharing: An Extended Surveycited by 35
  6. 2022Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizabilitycited by 32
  7. 2022Graph Neural Networks in IoT: A Surveycited by 27
  8. 2023Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Drivingcited by 26
  9. 2025Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmapcited by 26
  10. 2021Efficient Pressure: Improving efficiency for signalized intersectionscited by 24
  11. 2023Neurosymbolic Reinforcement Learning and Planning: A Surveycited by 24
  12. 2025Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directionscited by 23
38 more
  1. 2025Mixture-of-Personas Language Models for Population Simulationcited by 20
  2. 2023Can ChatGPT Enable ITS? The Case of Mixed Traffic Control via Reinforcement Learningcited by 18
  3. 2021A Survey on Deep Reinforcement Learning for Audio-Based Applicationscited by 17
  4. 2023Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problemscited by 15
  5. 2025TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learningcited by 13
  6. 2025Towards Human-Centric Autonomous Driving: A Fast-Slow Architecture Integrating Large Language Model Guidance with Reinforcement Learningcited by 11
  7. 2022The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Realitycited by 8
  8. 2024ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularizationcited by 8
  9. 2024Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Surveycited by 8
  10. 2021Machine Learning for Security in Vehicular Networks: A Comprehensive Surveycited by 7
  11. 2023Multi-Agent Reinforcement Learning Based on Representational Communication for Large-Scale Traffic Signal Controlcited by 7
  12. 2021Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Controlcited by 6
  13. 2022Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Maskingcited by 6
  14. 2022Modeling driver's evasive behavior during safety-critical lane changes:Two-dimensional time-to-collision and deep reinforcement learningcited by 6
  15. 2022Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search under Trajectory-based Guidancecited by 6
  16. 2023Online Reinforcement Learning in Non-Stationary Context-Driven Environmentscited by 6
  17. 2023Large-Scale Traffic Signal Control Using Constrained Network Partition and Adaptive Deep Reinforcement Learningcited by 6
  18. 2023Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behaviorcited by 6
  19. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  20. 2024Real-time system optimal traffic routing under uncertainties -- Can physics models boost reinforcement learning?cited by 6
  21. 2022Reinforcement Learning in Practice: Opportunities and Challengescited by 5
  22. 2022Causal Counterfactuals for Improving the Robustness of Reinforcement Learningcited by 5
  23. 2023Enhancing Energy-Awareness in Deep Learning through Fine-Grained Energy Measurementcited by 5
  24. 2023Data-efficient Deep Reinforcement Learning for Vehicle Trajectory Controlcited by 4
  25. 2021Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Surveycited by 3
  26. 2021A Reinforcement Learning Approach for GNSS Spoofing Attack Detection of Autonomous Vehiclescited by 3
  27. 2022Self-directed Machine Learningcited by 3
  28. 2022ADLight: A Universal Approach of Traffic Signal Control with Augmented Data Using Reinforcement Learningcited by 3
  29. 2023Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systemscited by 3
  30. 2023Deep Reinforcement Learning from Hierarchical Preference Designcited by 3
  31. 2024Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Drivingcited by 3
  32. 2024Learning Traffic Signal Control via Genetic Programmingcited by 3
  33. 2024OffLight: An Offline Multi-Agent Reinforcement Learning Framework for Traffic Signal Controlcited by 3
  34. 2025DreamerV3 for Traffic Signal Control: Hyperparameter Tuning and Performancecited by 3
  35. 2025GPLight+: A Genetic Programming Method for Learning Symmetric Traffic Signal Control Policycited by 3
  36. 2025Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approachcited by 3
  37. 2021Reinforcement Learning-based Dynamic Service Placement in Vehicular Networkscited by 2
  38. 2022Real-time Cooperative Vehicle Coordination at Unsignalized Road Intersectionscited by 2

50 most cited of 94 All 94 (JSON)