# End-to-End Race Driving with Deep Reinforcement Learning

arXiv: https://arxiv.org/abs/1807.02371 · HTML: https://mlsanity.com/paper/1807.02371/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2018.

## Built on by (most cited first, 30 of 40)

- [Reward (Mis)design for Autonomous Driving](https://mlsanity.com/paper/2104.13906/) (2021)
- [Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing](https://mlsanity.com/paper/2202.07008/) (2022)
- [Autonomous Drone Racing with Deep Reinforcement Learning](https://mlsanity.com/paper/2103.08624/) (2021)
- [Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning](https://mlsanity.com/paper/2103.14666/) (2021)
- [Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing](https://mlsanity.com/paper/2103.04909/) (2021)
- [A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo](https://mlsanity.com/paper/2406.12563/) (2024)
- [Formula RL: Deep Reinforcement Learning for Autonomous Racing using Telemetry Data](https://mlsanity.com/paper/2104.11106/) (2021)
- [A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles](https://mlsanity.com/paper/2105.14218/) (2021)
- [Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehicles](https://mlsanity.com/paper/2109.13446/) (2021)
- [Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-lane Scenarios](https://mlsanity.com/paper/2109.05540/) (2021)
- [Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions](https://mlsanity.com/paper/2402.04168/) (2024)
- [A Champion-level Vision-based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7](https://mlsanity.com/paper/2504.09021/) (2025)
- [Steadily Learn to Drive with Virtual Memory](https://mlsanity.com/paper/2102.08072/) (2021)
- [Goal-constrained Sparse Reinforcement Learning for End-to-End Driving](https://mlsanity.com/paper/2103.09189/) (2021)
- [Expert Human-Level Driving in Gran Turismo Sport Using Deep Reinforcement Learning with Image-based Representation](https://mlsanity.com/paper/2111.06449/) (2021)
- [End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing](https://mlsanity.com/paper/2309.00296/) (2023)
- [V-Max: A Reinforcement Learning Framework for Autonomous Driving](https://mlsanity.com/paper/2503.08388/) (2025)
- [Predictive Uncertainty for Runtime Assurance of a Real-Time Computer Vision-Based Landing System](https://mlsanity.com/paper/2508.09732/) (2025)
- [Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment](https://mlsanity.com/paper/2112.11947/) (2021)
- [Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Cars](https://mlsanity.com/paper/2206.10249/) (2022)
- [Development and Assessment of Autonomous Vehicles in Both Fully Automated and Mixed Traffic Conditions](https://mlsanity.com/paper/2312.04805/) (2023)
- [Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios](https://mlsanity.com/paper/2404.10658/) (2024)
- [AARK: An Open Toolkit for Autonomous Racing Research](https://mlsanity.com/paper/2410.00358/) (2024)
- [OctoPath: An OcTree Based Self-Supervised Learning Approach to Local Trajectory Planning for Mobile Robots](https://mlsanity.com/paper/2106.00988/) (2021)
- [Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecture](https://mlsanity.com/paper/2110.05437/) (2021)
- [Towards Optimal Head-to-head Autonomous Racing with Curriculum Reinforcement Learning](https://mlsanity.com/paper/2308.13491/) (2023)
- [Partial End-to-end Reinforcement Learning for Robustness Against Modelling Error in Autonomous Racing](https://mlsanity.com/paper/2312.06406/) (2023)
- [Scalable Decentralized Cooperative Platoon using Multi-Agent Deep Reinforcement Learning](https://mlsanity.com/paper/2312.06858/) (2023)
- [Deep Reinforcement Learning for Local Path Following of an Autonomous Formula SAE Vehicle](https://mlsanity.com/paper/2401.02903/) (2024)
- [Learning Autonomous Race Driving with Action Mapping Reinforcement Learning](https://mlsanity.com/paper/2406.14934/) (2024)

## 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.