/Awesome-Vehicle-Planning

This repo collects interesting papers related to Autonomous Vehicle Planning (along with some personal notes).

Awesome-Vehicle-Planning

This repo collects interesting papers related to Autonomous Vehicle Planning. It is worth noting that these papers are broadly related to the topic in my point of view: papers not directly study about vehicle motion planning (e.g. pure RL, IL) may also be collected in the list. You can also refer to more details of these papers in Notes.md, which records my summarization for the papers. Welcome pull requests for interesting papers!

Planning

Subcategory Paper Conference Links
RL Related Hierarchical Planning Through Goal-Conditioned Offline Reinforcement Learning arXiv'22 Paper
Driving by Dreaming: Offline Model-Based Reinforcement Learning for Autonomous Vehicles Master's Thesis'22 Paper
Rethinking Closed-loop Training for Autonomous Driving ECCV'22 Paper
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning ICML'22 Paper | Code
UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning NeurIPS'21 Workshop (Best paper) Paper
Offline Reinforcement Learning for Autonomous Driving with Safety and Exploration Enhancement NeurIPS'21 Workshop Paper
Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning IROS'21 Paper
Marrying Motion Forecasting and Offline Model-Based Reinforcement Learning for Self-Driving Cars Github'20 Paper
Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning arXiv'20 Paper | Code
Model-free Deep Reinforcement Learning for Urban Autonomous Driving arXiv'19 Paper | Code
Learning to Drive in a Day arXiv'18 Paper
IL Related Guided Conditional Diffsuion for Controllable Traffic Simulation arXiv'22 Paper
Model-Based Imitation Learning for Urban Driving NeurIPS'22 Paper | Code
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving arXiv'22 Paper
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning ECCV'22 Paper | Code
PlanT: Explainable Planning Transformers via Object-Level Representations CoRL'22 Paper | Code
End-to-End Urban Driving by Imitating a Reinforcement Learning Coach CVPR'21 Paper | Code
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations ECCV'20 Paper
DSDNet: Deep Structured self-Driving Network ECCV'20 Paper
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles IROS'19 Paper
End-to-end Interpretable Neural Motion Planner CVPR'19 (Oral) Paper
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst RSS'19 Paper
End-to-end Driving via Conditional Imitation Learning ICRA'18 Paper
Tree Search Related LEADER: Learning Attention over Driving Behaviors for Planning under Uncertainty CoRL'22 (Oral) Paper
Closing the Planning-Learning Loop with Application to Autonomous Driving T-RP'22 Paper | Code
KB-Tree: Learnable and Continuous Monte-Carlo Tree Search for Autonomous Driving Planning IROS'21 Paper
Driving Maneuvers Prediction Based Autonomous Driving Control by Deep Monte Carlo Tree T-VT'20 Paper | Code
Interaction Modeling M2I: From Factored Marginal Trajectory Prediction to Interactive Prediction CVPR'22 Paper | Code
InterSim: Interactive Traffic Simulation via Explicit Relation Modeling IROS'22 Paper | Code
Optimization Related Comprehensive Reactive Safety: No Need for a Trajectory if You Have a Strategy IROS'22 Paper
Autonomous Driving Motion Planning With Constrained Iterative LQR T-IT'19 Paper
Tunable and Stable Real-Time Trajectory Planning for Urban Autonomous Driving IROS'15 Paper
Traditional Planning Algorithms Path Planning using Neural A* Search ICML'21 Paper | Code
Sampling-based Algorithms for Optimal Motion Planning IJRR'10 Paper
Practical Search Techniques in Path Planning for Autonomous Driving AAAI'08 Paper

Reinforcement Learning

Subcategory Paper Conference Link
Model-based RL Mismatched No More: Joint Model-Policy Optimization for Model-Based RL NeurIPS'22 Paper
Planning with Diffusion for Flexible Behavior Synthesis ICML'22 Paper
Offline RL Hierarchical Decision Transformer arXiv'22 Paper
The In-Sample Softmax for Offline Reinforcement Learning ICLR'23 (submitted) Paper
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning arXiv'22 Paper
Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL arXiv'22 Paper
Mildly Conservative Q-Learning for Offline Reinforcement Learning NeurIPS'22 Paper | Code
Bootstrapped Transformer for Offline Reinforcement Learning NeurIPS'22 Paper | Code
A Unified Framework for Alternating Offline Model Training and Policy Learning NeurIPS'22 Paper |Code
A Policy-Guided Imitation Approach for Offline Reinforcement Learning NeurIPS'22 Paper | Code
MOReL: Model-Based Offline Reinforcement Learning arXiv'21 Paper | Code
Offline Reinforcement Learning with Implicit Q-Learning arXiv'21 Paper | Code
Offline Reinforcement Learning from Images with Latent Space Models PRML'21 Paper | Code
Online and Offline Reinforcement Learning by Planning with a Learned Model NeurIPS'21 (Spotlight) Paper
Offline Reinforcement Learning as One Big Sequence Modeling Problem NeurIPS'21 Paper | Code
Decision Transformer: Reinforcement Learning via Sequence Modeling NeurIPS'21 Paper | Code
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble NeurIPS'21 Paper | Code
Conservative Q-Learning for Offline Reinforcement Learning NeurIPS'20 Paper | Code
Model-Based Offline Planning ICLR'21 Paper
Off-Policy Deep Reinforcement Learning without Exploration ICML'19 Paper | Code

Imitation Learning

Paper Conference Link
Planning for Sample Efficient Imitation Learning NeurIPS'22 Paper | Code
Generative Adversarial Imitation Learning arXiv'16 Paper