mlsanityData to 7 Oct 2026

A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning

arXiv 2101.06778 ↗First posted 17 Jan 2021cs.RO cs.AI cs.SYcited by 18

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

Abstract (arXiv)

Autonomous vehicles need to handle various traffic conditions and make safe and efficient decisions and maneuvers. However, on the one hand, a single optimization/sampling-based motion planner cannot efficiently generate safe trajectories in real time, particularly when there are many interactive vehicles near by. On the other hand, end-to-end learning methods cannot assure the safety of the outcomes. To address this challenge, we propose a hierarchical behavior planning framework with a set of low-level safe controllers and a high-level reinforcement learning algorithm (H-CtRL) as a coordinator for the low-level controllers. Safety is guaranteed by the low-level optimization/sampling-based controllers, while the high-level reinforcement learning algorithm makes H-CtRL an adaptive and efficient behavior planner. To train and test our proposed algorithm, we built a simulator that can reproduce traffic scenes using real-world datasets. The proposed H-CtRL is proved to be effective in various realistic simulation scenarios, with satisfying performance in terms of both safety and efficiency.

Key facts. Cited by 18 papers 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 18 of its 28 references that are in the map. First posted on arXiv 17 Jan 2021.

Builds on

18 of 28 references.

References · 18

  1. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  2. 2016End to End Learning for Self-Driving Carscited by 1,000
  3. 2016A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehiclescited by 251
  4. 2019INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Mapscited by 231
  5. 2017Deep Reinforcement Learning framework for Autonomous Drivingcited by 224
  6. 2016End-to-end Learning of Driving Models from Large-scale Video Datasetscited by 147
  7. 2020Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learningcited by 99
  8. 2017Virtual to Real Reinforcement Learning for Autonomous Drivingcited by 79
  9. 2019Conditional Generative Neural System for Probabilistic Trajectory Predictioncited by 76
  10. 2019Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Drivingcited by 52
  11. 2019Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safetycited by 48
  12. 2019Social Attention for Autonomous Decision-Making in Dense Trafficcited by 39
6 more
  1. 2020Reinforcement Learning based Control of Imitative Policies for Near-Accident Drivingcited by 23
  2. 2017A Fast Integrated Planning and Control Framework for Autonomous Driving via Imitation Learningcited by 20
  3. 2020Learning hierarchical behavior and motion planning for autonomous drivingcited by 15
  4. 2019Hierarchical Reinforcement Learning Method for Autonomous Vehicle Behavior Planningcited by 6
  5. 2018Bayesian Persuasive Drivingcited by 5
  6. 2019A Deep Reinforcement Learning Driving Policy for Autonomous Road Vehiclescited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 6; 2024: 3; 2025: 3; 2026: 3.

18 papers.

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  1. 2023Motion Planning for Autonomous Driving: The State of the Art and Future Perspectivescited by 112
  2. 2022Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learningcited by 48
  3. 2023Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstrationcited by 14
  4. 2024CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Modelcited by 12
  5. 2025VLN-Zero: Rapid Exploration and Cache-Enabled Neurosymbolic Vision-Language Planning for Zero-Shot Transfer in Robot Navigationcited by 8
  6. 2023EnsembleFollower: A Hybrid Car-Following Framework Based On Reinforcement Learning and Hierarchical Planningcited by 6
  7. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  8. 2025SafePath: Conformal Prediction for Safe LLM-Based Autonomous Navigationcited by 4
  9. 2023Imagination-Augmented Hierarchical Reinforcement Learning for Safe and Interactive Autonomous Driving in Urban Environmentscited by 3
  10. 2022Bi-Level Optimization Augmented with Conditional Variational Autoencoder for Autonomous Driving in Dense Trafficcited by 2
  11. 2023End-to-End Learning of Behavioural Inputs for Autonomous Driving in Dense Trafficcited by 2
  12. 2025A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspectivecited by 2
6 more
  1. 2022Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discoverycited by 1
  2. 2024Act Better by Timing: A timing-Aware Reinforcement Learning for Autonomous Drivingcited by 1
  3. 2024Let Hybrid A* Path Planner Obey Traffic Rules: A Deep Reinforcement Learning-Based Planning Frameworkcited by 1
  4. 2026Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Drivingcited by 1
  5. 2026Constraint-Enhanced Reinforcement Learning Based on Dynamic Decoupled Spherical Radial Squashingcited by 0
  6. 2026LUNA-AD: Lightweight Uncertainty-Aware Language Model with Lifelong Learning for Autonomous Drivingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Goal-conditioned Hierarchical Reinforcement Learning for Sample-efficient and Safe Autonomous Driving at Intersections
  2. 2025Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving
  3. 2021Spatially and Seamlessly Hierarchical Reinforcement Learning for State Space and Policy space in Autonomous Driving
  4. 2020Trajectory Planning for Autonomous Vehicles Using Hierarchical Reinforcement Learning
  5. 2023Developing Driving Strategies Efficiently: A Skill-Based Hierarchical Reinforcement Learning Approach
  6. 2020Safe Trajectory Planning Using Reinforcement Learning for Self Driving
  7. 2023Action and Trajectory Planning for Urban Autonomous Driving with Hierarchical Reinforcement Learning
  8. 2023Integration of Reinforcement Learning Based Behavior Planning With Sampling Based Motion Planning for Automated Driving