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End-to-End Race Driving with Deep Reinforcement Learning

arXiv 1807.02371 ↗First posted 6 Jul 2018cs.CV cs.ROcited by 38

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Abstract (arXiv)

We present research using the latest reinforcement learning algorithm for end-to-end driving without any mediated perception (object recognition, scene understanding). The newly proposed reward and learning strategies lead together to faster convergence and more robust driving using only RGB image from a forward facing camera. An Asynchronous Actor Critic (A3C) framework is used to learn the car control in a physically and graphically realistic rally game, with the agents evolving simultaneously on tracks with a variety of road structures (turns, hills), graphics (seasons, location) and physics (road adherence). A thorough evaluation is conducted and generalization is proven on unseen tracks and using legal speed limits. Open loop tests on real sequences of images show some domain adaption capability of our method.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jul 2018.

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Citing papers per year: 2021: 16; 2022: 4; 2023: 6; 2024: 7; 2025: 5.

38 papers.

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  1. 2021Reward (Mis)design for Autonomous Drivingcited by 102
  2. 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racingcited by 56
  3. 2021Autonomous Drone Racing with Deep Reinforcement Learningcited by 51
  4. 2021Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learningcited by 41
  5. 2021Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racingcited by 22
  6. 2024A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismocited by 12
  7. 2021Formula RL: Deep Reinforcement Learning for Autonomous Racing using Telemetry Datacited by 10
  8. 2021A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehiclescited by 10
  9. 2021Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehiclescited by 8
  10. 2021Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-lane Scenarioscited by 5
  11. 2024Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptionscited by 4
  12. 2025A Champion-level Vision-based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7cited by 4
26 more
  1. 2021Steadily Learn to Drive with Virtual Memorycited by 3
  2. 2021Goal-constrained Sparse Reinforcement Learning for End-to-End Drivingcited by 3
  3. 2021Expert Human-Level Driving in Gran Turismo Sport Using Deep Reinforcement Learning with Image-based Representationcited by 3
  4. 2025V-Max: A Reinforcement Learning Framework for Autonomous Drivingcited by 3
  5. 2025Predictive Uncertainty for Runtime Assurance of a Real-Time Computer Vision-Based Landing Systemcited by 3
  6. 2021Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environmentcited by 2
  7. 2022Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Carscited by 2
  8. 2023End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racingcited by 2
  9. 2023Development and Assessment of Autonomous Vehicles in Both Fully Automated and Mixed Traffic Conditionscited by 2
  10. 2024AARK: An Open Toolkit for Autonomous Racing Researchcited by 2
  11. 2021OctoPath: An OcTree Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robotscited by 1
  12. 2021Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecturecited by 1
  13. 2023Towards Optimal Head-to-head Autonomous Racing with Curriculum Reinforcement Learningcited by 1
  14. 2023Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racingcited by 1
  15. 2023Scalable Decentralized Cooperative Platoon using Multi-Agent Deep Reinforcement Learningcited by 1
  16. 2024Learning Autonomous Race Driving with Action Mapping Reinforcement Learningcited by 1
  17. 2021ObserveNet Control: A Vision-Dynamics Learning Approach to Predictive Control in Autonomous Vehiclescited by 0
  18. 2021Geo-Context Aware Study of Vision-Based Autonomous Driving Models and Spatial Video Datacited by 0
  19. 2022A New Approach to Training Multiple Cooperative Agents for Autonomous Drivingcited by 0
  20. 2022Integrated Decision and Control for High-Level Automated Vehicles by Mixed Policy Gradient and Its Experiment Verificationcited by 0
  21. 2023Automated Driving Without Ethics: Meaning, Design and Real-World Implementationcited by 0
  22. 2024Deep Reinforcement Learning for Local Path Following of an Autonomous Formula SAE Vehiclecited by 0
  23. 2024Bidirectional-Reachable Hierarchical Reinforcement Learning with Mutually Responsive Policiescited by 0
  24. 2024Performance Comparison of Deep RL Algorithms for Mixed Traffic Cooperative Lane-Changingcited by 0
  25. 2025Experimental investigation of pose informed reinforcement learning for skid-steered visual navigationcited by 0
  26. 2025Context-Aware Model-Based Reinforcement Learning for Autonomous Racingcited by 0