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