mlsanityData to 7 Oct 2026

VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

arXiv 2402.13243 ↗First posted 20 Feb 2024cs.CV cs.ROcited by 287

On the map: End-to-end autonomous driving → Imitation-learning end-to-end planners

Abstract (arXiv)

Learning a human-like driving policy from large-scale driving demonstrations is promising, but the uncertainty and non-deterministic nature of planning make it challenging. Existing learning-based planning methods follow a deterministic paradigm to directly regress the action, failing to cope with the uncertainty problem. In this work, we propose a probabilistic planning model for end-to-end autonomous driving, termed VADv2. We resort to a probabilistic field function to model the mapping from the action space to the probabilistic distribution. Since the planning action space is a high-dimensional continuous spatiotemporal space and hard to tackle, we first discretize the planning action space to a large planning vocabulary and then tokenize the planning vocabulary into planning tokens. Planning tokens interact with scene tokens and output the probabilistic distribution of action. Mass driving demonstrations are leveraged to supervise the distribution. VADv2 achieves state-of-the-art closed-loop performance on the CARLA Town05 benchmark, significantly outperforming existing methods, and also leads the recent Bench2Drive benchmark. We further provide comprehensive evaluations on NAVSIM and a large-scale 3DGS-based benchmark, demonstrating its effectiveness in real-world applications. Code is available at https://github.com/hustvl/VAD.

Key facts. Cited by 287 papers in the map (data through 7 Oct 2026). Placed in Imitation-learning end-to-end planners, one of 9 directions in End-to-end autonomous driving. Builds on 52 of its 71 references that are in the map. First posted on arXiv 20 Feb 2024.

Builds on

52 of 71 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022Model-Based Imitation Learning for Urban Driving14 Oct
  2. 2021End-to-End Urban Driving by Imitating a Reinforcement Learning Coach18 Aug

Other references · 50

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  4. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  5. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  6. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  7. 2022Planning-oriented Autonomous Drivingcited by 1,068
  8. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  9. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 613
  10. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  11. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 528
  12. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 527
38 more
  1. 2023DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Modelcited by 455
  2. 2019MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncited by 417
  3. 2020Learning Lane Graph Representations for Motion Forecastingcited by 380
  4. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  5. 2022ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learningcited by 365
  6. 2019Learning by Cheatingcited by 361
  7. 2023GPT-Driver: Learning to Drive with GPTcited by 344
  8. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 343
  9. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 313
  10. 2022MapTR: Structured Modeling and Learning for Online Vectorized HD Map Constructioncited by 311
  11. 2022BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervisioncited by 302
  12. 2021HDMapNet: An Online HD Map Construction and Evaluation Frameworkcited by 280
  13. 2019CoverNet: Multimodal Behavior Prediction using Trajectory Setscited by 259
  14. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  15. 2021FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Camerascited by 239
  16. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  17. 2023Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Drivingcited by 231
  18. 2021MP3: A Unified Model to Map, Perceive, Predict and Plancited by 211
  19. 2022Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformercited by 211
  20. 2021Multimodal Motion Prediction with Stacked Transformerscited by 207
  21. 2023DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Modelscited by 204
  22. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
  23. 2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
  24. 2023LanguageMPC: Large Language Models as Decision Makers for Autonomous Drivingcited by 188
  25. 2023Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Drivingcited by 168
  26. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectoriescited by 165
  27. 2023Drive Like a Human: Rethinking Autonomous Driving with Large Language Modelscited by 158
  28. 2023MotionLM: Multi-Agent Motion Forecasting as Language Modelingcited by 154
  29. 2019End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordancescited by 147
  30. 2023DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Drivingcited by 142
  31. 2022ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queriescited by 116
  32. 2021Learning to drive from a world on railscited by 114
  33. 2021GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Drivingcited by 59
  34. 2023Trajeglish: Traffic Modeling as Next-Token Predictioncited by 59
  35. 2023Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Constructioncited by 50
  36. 2023HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Drivingcited by 48
  37. 2023MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersectionscited by 38
  38. 2022Perceive, Interact, Predict: Learning Dynamic and Static Clues for End-to-End Motion Predictioncited by 28

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 23; 2025: 139; 2026: 125.

287 papers.

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  1. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  2. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
  3. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  4. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 226
  5. 2025ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Drivingcited by 190
  6. 2025ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generationcited by 177
  7. 2025FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Drivingcited by 165
  8. 2024Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Drivingcited by 156
  9. 2024Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Taskscited by 146
  10. 2025End-to-End Driving with Online Trajectory Evaluation via BEV World Modelcited by 145
  11. 2025OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoningcited by 142
  12. 2025Unified Vision-Language-Action Modelcited by 128
38 more
  1. 2025GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Drivingcited by 117
  2. 2025Epona: Autoregressive Diffusion World Model for Autonomous Drivingcited by 115
  3. 2025AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoningcited by 108
  4. 2024DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformerscited by 96
  5. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  6. 2025DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planningcited by 91
  7. 2025World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Modelcited by 91
  8. 2024VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervisioncited by 85
  9. 2025Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Drivingcited by 84
  10. 2025RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learningcited by 76
  11. 2025A Survey on Vision-Language-Action Models for Autonomous Drivingcited by 72
  12. 2025ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Drivingcited by 66
  13. 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 63
  14. 2025Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Modelscited by 60
  15. 2024Unleashing Generalization of End-to-End Autonomous Driving with Controllable Long Video Generationcited by 54
  16. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Drivingcited by 52
  17. 2024Making Large Language Models Better Planners with Reasoning-Decision Alignmentcited by 51
  18. 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
  19. 2024SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Drivingcited by 46
  20. 2025DriveLaW:Unifying Planning and Video Generation in a Latent Driving Worldcited by 43
  21. 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 41
  22. 2025iPad: Iterative Proposal-centric End-to-End Autonomous Drivingcited by 41
  23. 2025Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Trainingcited by 39
  24. 2025DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Drivingcited by 39
  25. 2026Driving on Registerscited by 38
  26. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  27. 2024DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulationcited by 34
  28. 2025SimScale: Learning to Drive via Real-World Simulation at Scalecited by 34
  29. 2026SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Drivingcited by 34
  30. 2025AutoDrive-R2: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Drivingcited by 32
  31. 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 32
  32. 2025From Forecasting to Planning: Policy World Model for Collaborative State-Action Predictioncited by 29
  33. 2025SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Drivingcited by 28
  34. 2024End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotationcited by 27
  35. 2025Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environmentscited by 27
  36. 2025ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstructioncited by 27
  37. 2026Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Drivingcited by 27
  38. 2024OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoningcited by 26

50 most cited of 287 All 287 (JSON)

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  1. 2026Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms
  2. 2022Distribution-aware Goal Prediction and Conformant Model-based Planning for Safe Autonomous Driving
  3. 2025LAP: Fast LAtent Diffusion Planner for Autonomous Driving
  4. 2024PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Driving
  5. 2025VDRive: Leveraging Reinforced VLA and Diffusion Policy for End-to-end Autonomous Driving
  6. 2021Closing the Planning-Learning Loop with Application to Autonomous Driving
  7. 2026PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning
  8. 2026TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations