mlsanityData to 7 Oct 2026

Exploring applications of deep reinforcement learning for real-world autonomous driving systems

arXiv 1901.01536 ↗First posted 6 Jan 2019cs.LG cs.RO stat.MLcited by 18

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Abstract (arXiv)

Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind's AlphaGo. It has been successfully deployed in commercial vehicles like Mobileye's path planning system. However, a vast majority of work on DRL is focused on toy examples in controlled synthetic car simulator environments such as TORCS and CARLA. In general, DRL is still at its infancy in terms of usability in real-world applications. Our goal in this paper is to encourage real-world deployment of DRL in various autonomous driving (AD) applications. We first provide an overview of the tasks in autonomous driving systems, reinforcement learning algorithms and applications of DRL to AD systems. We then discuss the challenges which must be addressed to enable further progress towards real-world deployment.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Jan 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 0; 2023: 2; 2024: 2; 2025: 3; 2026: 4.

18 papers.

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  1. 2021Memory-based Deep Reinforcement Learning for POMDPscited by 53
  2. 2025DiWA: Diffusion Policy Adaptation with World Modelscited by 28
  3. 2021Recurrent Neural Network Controllers Synthesis with Stability Guarantees for Partially Observed Systemscited by 15
  4. 2021Reinforcement Learning Under Algorithmic Triagecited by 15
  5. 2024Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificatescited by 15
  6. 2021A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehiclescited by 10
  7. 2025OpenApps: Simulating Environment Variations to Measure UI-Agent Reliabilitycited by 10
  8. 2026The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMscited by 10
  9. 2021Development and testing of an image transformer for explainable autonomous driving systemscited by 9
  10. 2026KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Taskscited by 7
  11. 2024Safe and Reliable Training of Learning-Based Aerospace Controllerscited by 4
  12. 2025Mutual Information Tracks Policy Coherence in Reinforcement Learningcited by 3
6 more
  1. 2021Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific researchcited by 1
  2. 2023Review of Deep Reinforcement Learning for Autonomous Drivingcited by 1
  3. 2021Advances in Electron Microscopy with Deep Learningcited by 0
  4. 2023Trip Planning for Autonomous Vehicles with Wireless Data Transfer Needs Using Reinforcement Learningcited by 0
  5. 2026Uncertainty-aware reinforcement learning for chemical language modelscited by 0
  6. 2026Learning from the Test: Self-Referential Differential Testing for Deep RL Agentscited by 0