mlsanityData to 7 Oct 2026

Robust AI Driving Strategy for Autonomous Vehicles

arXiv 2207.07829 ↗First posted 16 Jul 2022cs.RO cs.SY eess.SYcited by 1

On the map: End-to-end autonomous driving → Reinforcement learning for driving

Abstract (arXiv)

There has been significant progress in sensing, perception, and localization for automated driving, However, due to the wide spectrum of traffic/road structure scenarios and the long tail distribution of human driver behavior, it has remained an open challenge for an intelligent vehicle to always know how to make and execute the best decision on road given available sensing / perception / localization information. In this chapter, we talk about how artificial intelligence and more specifically, reinforcement learning, can take advantage of operational knowledge and safety reflex to make strategical and tactical decisions. We discuss some challenging problems related to the robustness of reinforcement learning solutions and their implications to the practical design of driving strategies for autonomous vehicles. We focus on automated driving on highway and the integration of reinforcement learning, vehicle motion control, and control barrier function, leading to a robust AI driving strategy that can learn and adapt safely.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Reinforcement learning for driving, one of 9 directions in End-to-end autonomous driving. Builds on 17 of its 52 references that are in the map. First posted on arXiv 16 Jul 2022.

Builds on

17 of 52 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehicles29 May

Other references · 16

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2016Asynchronous Methods for Deep Reinforcement Learningcited by 2,218
  3. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  4. 2017Curiosity-driven Exploration by Self-supervised Predictioncited by 1,173
  5. 2016Control Barrier Function Based Quadratic Programs for Safety Critical Systemscited by 261
  6. 2015DeepDriving: Learning Affordance for Direct Perception in Autonomous Drivingcited by 229
  7. 2016End-to-end Learning of Driving Models from Large-scale Video Datasetscited by 147
  8. 2020Survey of Deep Reinforcement Learning for Motion Planning of Autonomous Vehiclescited by 101
  9. 2014Safe Exploration of State and Action Spaces in Reinforcement Learningcited by 37
  10. 2019Control Barrier Functions for Systems with High Relative Degreecited by 30
  11. 2018End-to-End Learning of Driving Models with Surround-View Cameras and Route Plannerscited by 27
  12. 2016Game-Theoretic Modeling of Driver and Vehicle Interactions for Verification and Validation of Autonomous Vehicle Control Systemscited by 24
4 more
  1. 2019Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learningcited by 23
  2. 2019Autonomous Highway Driving using Deep Reinforcement Learningcited by 22
  3. 2019Learning latent state representation for speeding up explorationcited by 8
  4. 2020Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehiclescited by 3

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2

Similar, not cited

Close in wording, no citation either way

  1. 2025Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach
  2. 2025A Comprehensive Review of Reinforcement Learning for Autonomous Driving in the CARLA Simulator
  3. 2022Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios
  4. 2020A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning
  5. 2024Optimizing Low-Speed Autonomous Driving: A Reinforcement Learning Approach to Route Stability and Maximum Speed
  6. 2025Balancing Progress and Safety: A Novel Risk-Aware Objective for RL in Autonomous Driving
  7. 2021Reinforcement Learning Based Safe Decision Making for Highway Autonomous Driving
  8. 2022Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning