mlsanityData to 14 Oct 2026

GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving

arXiv 2503.05689 ↗First posted 7 Mar 2025cs.CVcited by 120

On the map: Diffusion models → Diffusion and flow policies for robotics

also in 1 more
Abstract (arXiv)

We propose GoalFlow, an end-to-end autonomous driving method for generating high-quality multimodal trajectories. In autonomous driving scenarios, there is rarely a single suitable trajectory. Recent methods have increasingly focused on modeling multimodal trajectory distributions. However, they suffer from trajectory selection complexity and reduced trajectory quality due to high trajectory divergence and inconsistencies between guidance and scene information. To address these issues, we introduce GoalFlow, a novel method that effectively constrains the generative process to produce high-quality, multimodal trajectories. To resolve the trajectory divergence problem inherent in diffusion-based methods, GoalFlow constrains the generated trajectories by introducing a goal point. GoalFlow establishes a novel scoring mechanism that selects the most appropriate goal point from the candidate points based on scene information. Furthermore, GoalFlow employs an efficient generative method, Flow Matching, to generate multimodal trajectories, and incorporates a refined scoring mechanism to select the optimal trajectory from the candidates. Our experimental results, validated on the NavsimciteDauner2024navsim, demonstrate that GoalFlow achieves state-of-the-art performance, delivering robust multimodal trajectories for autonomous driving. GoalFlow achieved PDMS of 90.3, significantly surpassing other methods. Compared with other diffusion-policy-based methods, our approach requires only a single denoising step to obtain excellent performance. The code is available at https://github.com/YvanYin/GoalFlow.

Key facts. Cited by 120 papers in the map (data through 14 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 27 of its 38 references that are in the map. First posted on arXiv 7 Mar 2025.

Builds on

27 of 38 references.

Closest ancestors · 4

Same direction, newest first

  1. 2024DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model14 Oct
  2. 2024Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning8 Oct
  3. 2024Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following9 Feb
  4. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar

Other references · 23

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2020Denoising Diffusion Implicit Modelscited by 9,781
  3. 2022Classifier-Free Diffusion Guidancecited by 5,847
  4. 2022Flow Matching for Generative Modelingcited by 5,702
  5. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  6. 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,700
  7. 2022Planning-oriented Autonomous Drivingcited by 1,087
  8. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 622
  9. 2017End-to-end Driving via Conditional Imitation Learningcited by 485
  10. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 485
  11. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 354
  12. 2020TNT: Target-driveN Trajectory Predictioncited by 347
11 more
  1. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 346
  2. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 295
  3. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 289
  4. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 249
  5. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 241
  6. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  7. 2023MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusioncited by 213
  8. 2023ADAPT: Action-aware Driving Caption Transformercited by 78
  9. 2023FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Drivingcited by 67
  10. 2020Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimationcited by 57
  11. 2024TOD3Cap: Towards 3D Dense Captioning in Outdoor Scenescited by 40

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 44; 2026: 76.

120 papers.

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  1. 2025ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Drivingcited by 198
  2. 2025Epona: Autoregressive Diffusion World Model for Autonomous Drivingcited by 117
  3. 2025World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Modelcited by 95
  4. 2025ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Drivingcited by 67
  5. 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 67
  6. 2025AdaThinkDrive: Adaptive Thinking via Reinforcement Learning for Autonomous Drivingcited by 58
  7. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Drivingcited by 56
  8. 2025DriveLaW:Unifying Planning and Video Generation in a Latent Driving Worldcited by 47
  9. 2026Driving on Registerscited by 44
  10. 2025DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Drivingcited by 39
  11. 2025SimScale: Learning to Drive via Real-World Simulation at Scalecited by 36
  12. 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 33
38 more
  1. 2026Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Drivingcited by 30
  2. 2026SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Drivingcited by 26
  3. 2025Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Drivingcited by 24
  4. 2025ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Drivingcited by 22
  5. 2025Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modelingcited by 22
  6. 2025GuideFlow: Constraint-Guided Flow Matching for Planning in End-to-End Autonomous Drivingcited by 22
  7. 2025Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Drivingcited by 19
  8. 2026DriveFine: Refining-Augmented Masked Diffusion VLA for Precise and Robust Drivingcited by 19
  9. 2026Unleashing VLA Potentials in Autonomous Driving via Explicit Learning from Failurescited by 19
  10. 2025BridgeDrive: Diffusion Bridge Policy for Closed-Loop Trajectory Planning in Autonomous Drivingcited by 18
  11. 2025Learning Personalized Driving Styles via Reinforcement Learning from Human Feedbackcited by 17
  12. 2025DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Drivingcited by 17
  13. 2026DriveFuture: Future-Aware Latent World Models for Autonomous Drivingcited by 17
  14. 2025GaussianFusion: Gaussian-Based Multi-Sensor Fusion for End-to-End Autonomous Drivingcited by 16
  15. 2025PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Drivingcited by 16
  16. 2026EponaV2: Driving World Model with Comprehensive Future Reasoningcited by 15
  17. 2025ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Drivingcited by 14
  18. 2025AD-R1: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving with Impartial World Modelscited by 14
  19. 2026DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scalecited by 13
  20. 2025SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functionscited by 12
  21. 2025MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Drivingcited by 12
  22. 2026Unleashing the Potential of Diffusion Models for End-to-End Autonomous Drivingcited by 11
  23. 2026DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Drivingcited by 11
  24. 2026CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planningcited by 11
  25. 2026Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation Systemcited by 11
  26. 2026MindDriver: Introducing Progressive Multimodal Reasoning for Autonomous Drivingcited by 10
  27. 2025DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policycited by 9
  28. 2026Unifying Language-Action Understanding and Generation for Autonomous Drivingcited by 9
  29. 2025TrajDiff: End-to-end Autonomous Driving without Perception Annotationcited by 8
  30. 2026SafeDrive: Fine-Grained Safety Reasoning for End-to-End Driving in a Sparse Worldcited by 8
  31. 2025Generative AI for Autonomous Driving: Frontiers and Opportunitiescited by 7
  32. 2026Test-Time Trajectory Optimization for Autonomous Drivingcited by 7
  33. 2025FocalAD: Local Motion Planning for End-to-End Autonomous Drivingcited by 6
  34. 2025VR-Drive: Viewpoint-Robust End-to-End Driving with Feed-Forward 3D Gaussian Splattingcited by 6
  35. 2026Generative Scenario Rollouts for End-to-End Autonomous Drivingcited by 6
  36. 2026Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drivecited by 6
  37. 2026GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Drivingcited by 6
  38. 2026Senna-2: Aligning VLM and End-to-End Driving Policy for Consistent Decision Making and Planningcited by 5

50 most cited of 120 All 120 (JSON)

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  1. 2025TrajFlow: Multi-modal Motion Prediction via Flow Matching
  2. 2026MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving
  3. 2026ManeuverFlow: Maneuver Hypothesis Generation with Future Evidence for Trajectory Evaluation and Refinement in End-to-End Autonomous Driving
  4. 2026K-Gen: A Multimodal Language-Conditioned Approach for Interpretable Keypoint-Guided Trajectory Generation
  5. 2024LeGo-Drive: Language-enhanced Goal-oriented Closed-Loop End-to-End Autonomous Driving
  6. 2025UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planning
  7. 2026ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
  8. 2025Future-Aware End-to-End Driving: Bidirectional Modeling of Trajectory Planning and Scene Evolution