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Automated Speed and Lane Change Decision Making using Deep Reinforcement Learning

arXiv 1803.10056 ↗First posted 14 Mar 2018cs.RO cs.AI cs.LGcited by 36

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Abstract (arXiv)

This paper introduces a method, based on deep reinforcement learning, for automatically generating a general purpose decision making function. A Deep Q-Network agent was trained in a simulated environment to handle speed and lane change decisions for a truck-trailer combination. In a highway driving case, it is shown that the method produced an agent that matched or surpassed the performance of a commonly used reference model. To demonstrate the generality of the method, the exact same algorithm was also tested by training it for an overtaking case on a road with oncoming traffic. Furthermore, a novel way of applying a convolutional neural network to high level input that represents interchangeable objects is also introduced.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Mar 2018.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 14; 2022: 6; 2023: 3; 2024: 8; 2025: 3; 2026: 1.

36 papers.

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  1. 2021A Survey of Deep RL and IL for Autonomous Driving Policy Learningcited by 59
  2. 2021Multi-agent Reinforcement Learning for Cooperative Lane Changing of Connected and Autonomous Vehicles in Mixed Trafficcited by 20
  3. 2023Machine Learning for Large-Scale Optimization in 6G Wireless Networkscited by 18
  4. 2024Optimizing Autonomous Driving for Safety: A Human-Centric Approach with LLM-Enhanced RLHFcited by 18
  5. 2021Ensemble Quantile Networks: Uncertainty-Aware Reinforcement Learning with Applications in Autonomous Drivingcited by 17
  6. 2024A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Drivingcited by 17
  7. 2021Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPScited by 10
  8. 2021A Survey of Deep Reinforcement Learning Algorithms for Motion Planning and Control of Autonomous Vehiclescited by 10
  9. 2019Randomized Adversarial Imitation Learning for Autonomous Drivingcited by 6
  10. 2021SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learningcited by 6
  11. 2021End-to-End Intersection Handling using Multi-Agent Deep Reinforcement Learningcited by 6
  12. 2021Reinforcement Learning Based Safe Decision Making for Highway Autonomous Drivingcited by 5
24 more
  1. 2022Tackling Real-World Autonomous Driving using Deep Reinforcement Learningcited by 5
  2. 2022How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategiescited by 4
  3. 2023Deep Q-Network Based Decision Making for Autonomous Drivingcited by 4
  4. 2024Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptionscited by 4
  5. 2022Optimizing Trajectories for Highway Driving with Offline Reinforcement Learningcited by 3
  6. 2025AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learningcited by 3
  7. 2021Adversarial Imitation Learning via Random Search in Lane Change Decision-Makingcited by 2
  8. 2021Decentralized Cooperative Lane Changing at Freeway Weaving Areas Using Multi-Agent Deep Reinforcement Learningcited by 2
  9. 2021Personalized Lane Change Decision Algorithm Using Deep Reinforcement Learning Approachcited by 2
  10. 2022Bi-Level Optimization Augmented with Conditional Variational Autoencoder for Autonomous Driving in Dense Trafficcited by 2
  11. 2023DRNet: A Decision-Making Method for Autonomous Lane Changingwith Deep Reinforcement Learningcited by 2
  12. 2021Flocking and Collision Avoidance for a Dynamic Squad of Fixed-Wing UAVs Using Deep Reinforcement Learningcited by 1
  13. 2021Lane Change Decision-Making through Deep Reinforcement Learningcited by 1
  14. 2021Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehiclescited by 1
  15. 2022Deep Q-learning: a robust control approachcited by 1
  16. 2024Autonomous Navigation of Tractor-Trailer Vehicles through Roundabout Intersectionscited by 1
  17. 2024Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Frameworkcited by 1
  18. 2022Estimating Link Flows in Road Networks with Synthetic Trajectory Data Generation: Reinforcement Learning-based Approachescited by 0
  19. 2024Safe Hybrid-Action Reinforcement Learning-Based Decision and Control for Discretionary Lane Changecited by 0
  20. 2024Autonomous vehicle decision and control through reinforcement learning with traffic flow randomizationcited by 0
  21. 2024Multi-Task Lane-Free Driving Strategy for Connected and Automated Vehicles: A Multi-Agent Deep Reinforcement Learning Approachcited by 0
  22. 2025Socially-Aware Autonomous Driving: Inferring Yielding Intentions for Safer Interactionscited by 0
  23. 2025A Hybrid Input based Deep Reinforcement Learning for Lane Change Decision-Making of Autonomous Vehiclecited by 0
  24. 2026End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systemscited by 0