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 |