Autonomous Driving with RL Reading List

Curated by Mouhssine Rifaki | Stanford Electrical Engineering | Last updated August 2026

RL-based approaches to autonomous driving, from simulation to deployment.

Autonomous Driving with RL: 10 key papers

1. Flow: A Modular Learning Framework for Mixed Autonomy Traffic
   Wu et al. arXiv 2017.
2. CARLA: An Open Urban Driving Simulator
   Dosovitskiy et al. arXiv 2017.
3. Learning by Cheating
   Chen et al. arXiv 2019.
4. End to End Learning for Self-Driving Cars
   Bojarski et al. arXiv 2016.
5. Deep Reinforcement Learning for Autonomous Driving: A Survey
   Kiran et al. arXiv 2020.
6. Learning to Drive in a Day
   Kendall et al. arXiv 2018.
7. ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
   Bansal et al. arXiv 2018.
8. Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
   Vinitsky et al. arXiv 2022.
9. GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS
   Kazemkhani et al. arXiv 2024.
10. Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
    Gulino et al. arXiv 2023.

Related reading lists

• Sim-to-Real Transfer
• Uncertainty Quantification & Conformal Prediction
• Offline Imitation Learning
• Adaptive Sensing and Active Learning
• Multi-Agent Reinforcement Learning
• Curiosity-Driven Exploration
• Offline Reinforcement Learning
• Optimal Transport for Machine Learning