mlsanityData to 7 Oct 2026

A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers

arXiv 1804.07871 ↗First posted 21 Apr 2018cs.ROcited by 44

Not on the map. Why?

Cited by 28 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Lane change is a crucial vehicle maneuver which needs coordination with surrounding vehicles. Automated lane changing functions built on rule-based models may perform well under pre-defined operating conditions, but they may be prone to failure when unexpected situations are encountered. In our study, we proposed a Reinforcement Learning based approach to train the vehicle agent to learn an automated lane change behavior such that it can intelligently make a lane change under diverse and even unforeseen scenarios. Particularly, we treated both state space and action space as continuous, and designed a Q-function approximator that has a closed- form greedy policy, which contributes to the computation efficiency of our deep Q-learning algorithm. Extensive simulations are conducted for training the algorithm, and the results illustrate that the Reinforcement Learning based vehicle agent is capable of learning a smooth and efficient driving policy for lane change maneuvers.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Apr 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2019: 2; 2020: 0; 2021: 14; 2022: 9; 2023: 12; 2024: 4; 2025: 2; 2026: 1.

44 papers.

Sort:

By area:

  1. 2023Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Researchcited by 158
  2. 2022Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarioscited by 124
  3. 2021A Survey of Deep RL and IL for Autonomous Driving Policy Learningcited by 59
  4. 2021ROAD: The ROad event Awareness Dataset for Autonomous Drivingcited by 54
  5. 2023Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challengescited by 39
  6. 2021Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligencecited by 25
  7. 2023Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviorscited by 25
  8. 2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
  9. 2021Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Drivingcited by 16
  10. 2021Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigationcited by 13
  11. 2025DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Modelcited by 13
  12. 2022Self-Adaptive Driving in Nonstationary Environments through Conjectural Online Lookahead Adaptationcited by 12
32 more
  1. 2021Modified DDPG car-following model with a real-world human driving experience with CARLA simulatorcited by 9
  2. 2021Runtime Safety Assurance for Learning-enabled Control of Autonomous Driving Vehiclescited by 8
  3. 2021Learning Interaction-aware Guidance Policies for Motion Planning in Dense Traffic Scenarioscited by 7
  4. 2023A Platform-Agnostic Deep Reinforcement Learning Framework for Effective Sim2Real Transfer towards Autonomous Drivingcited by 7
  5. 2021Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-lane Scenarioscited by 5
  6. 2022Tackling Real-World Autonomous Driving using Deep Reinforcement Learningcited by 5
  7. 2021Formulation and validation of a car-following model based on deep reinforcement learningcited by 4
  8. 2021An Intelligent Self-driving Truck System For Highway Transportationcited by 3
  9. 2022Bilateral Deep Reinforcement Learning Approach for Better-than-human Car Following Modelcited by 3
  10. 2022Optimizing Trajectories for Highway Driving with Offline Reinforcement Learningcited by 3
  11. 2022Residual Policy Learning for Powertrain Controlcited by 3
  12. 2023Developing Driving Strategies Efficiently: A Skill-Based Hierarchical Reinforcement Learning Approachcited by 3
  13. 2023Safe, Efficient, Comfort, and Energy-saving Automated Driving through Roundabout Based on Deep Reinforcement Learningcited by 3
  14. 2023Risk-anticipatory autonomous driving strategies considering vehicles' weights, based on hierarchical deep reinforcement learningcited by 3
  15. 2025Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learningcited by 3
  16. 2019Efficient Motion Planning for Automated Lane Change based on Imitation Learning and Mixed-Integer Optimizationcited by 2
  17. 2022Improve Generalization of Driving Policy at Signalized Intersections with Adversarial Learningcited by 2
  18. 2022Driver Assistance Eco-driving and Transmission Control with Deep Reinforcement Learningcited by 2
  19. 2023Comprehensive Training and Evaluation on Deep Reinforcement Learning for Automated Driving in Various Simulated Driving Maneuverscited by 2
  20. 2023DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learningcited by 2
  21. 2024Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learningcited by 2
  22. 2021Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programmingcited by 1
  23. 2023Review of Deep Reinforcement Learning for Autonomous Drivingcited by 1
  24. 2023Interpretable and Flexible Target-Conditioned Neural Planners For Autonomous Vehiclescited by 1
  25. 2024Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Frameworkcited by 1
  26. 2019Decision Making for Autonomous Driving via Augmented Adversarial Inverse Reinforcement Learningcited by 0
  27. 2021WAD: A Deep Reinforcement Learning Agent for Urban Autonomous Drivingcited by 0
  28. 2021Spatially and Seamlessly Hierarchical Reinforcement Learning for State Space and Policy space in Autonomous Drivingcited by 0
  29. 2022Integrated Decision and Control for High-Level Automated Vehicles by Mixed Policy Gradient and Its Experiment Verificationcited by 0
  30. 2024Safe Hybrid-Action Reinforcement Learning-Based Decision and Control for Discretionary Lane Changecited by 0
  31. 2024SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Drivingcited by 0
  32. 2026PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learningcited by 0