# DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning

arXiv: https://arxiv.org/abs/1911.01562 · HTML: https://mlsanity.com/paper/1911.01562/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Nov 2019.

## Built on by (most cited first, 13 of 13)

- [Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing](https://mlsanity.com/paper/2202.07008/) (2022)
- [Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems](https://mlsanity.com/paper/2112.11255/) (2021)
- [Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty](https://mlsanity.com/paper/2404.18909/) (2024)
- [Transferring Multi-Agent Reinforcement Learning Policies for Autonomous Driving using Sim-to-Real](https://mlsanity.com/paper/2203.11653/) (2022)
- [Minimax-Optimal Multi-Agent Robust Reinforcement Learning](https://mlsanity.com/paper/2412.19873/) (2024)
- [PlayBest: Professional Basketball Player Behavior Synthesis via Planning with Diffusion](https://mlsanity.com/paper/2306.04090/) (2023)
- [A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systems](https://mlsanity.com/paper/2509.22379/) (2025)
- [MicroRacer: a didactic environment for Deep Reinforcement Learning](https://mlsanity.com/paper/2203.10494/) (2022)
- [Memory based neural networks for end-to-end autonomous driving](https://mlsanity.com/paper/2205.12124/) (2022)
- [Hearts Gym: Learning Reinforcement Learning as a Team Event](https://mlsanity.com/paper/2209.05466/) (2022)
- [A Multifidelity Sim-to-Real Pipeline for Verifiable and Compositional Reinforcement Learning](https://mlsanity.com/paper/2312.01249/) (2023)
- [Distributionally Robust Cooperative Multi-Agent Reinforcement Learning via Robust Value Factorization](https://mlsanity.com/paper/2602.11437/) (2026)
- [Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation](https://mlsanity.com/paper/2605.03125/) (2026)

## Abstract (arXiv)

DeepRacer is a platform for end-to-end experimentation with RL and can be used to systematically investigate the key challenges in developing intelligent control systems. Using the platform, we demonstrate how a 1/18th scale car can learn to drive autonomously using RL with a monocular camera. It is trained in simulation with no additional tuning in physical world and demonstrates: 1) formulation and solution of a robust reinforcement learning algorithm, 2) narrowing the reality gap through joint perception and dynamics, 3) distributed on-demand compute architecture for training optimal policies, and 4) a robust evaluation method to identify when to stop training. It is the first successful large-scale deployment of deep reinforcement learning on a robotic control agent that uses only raw camera images as observations and a model-free learning method to perform robust path planning. We open source our code and video demo on GitHub: https://git.io/fjxoJ.