mlsanityData to 7 Oct 2026

SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving

arXiv 2510.17191 ↗First posted 20 Oct 2025cs.RO cs.AIcited by 2

On the map: End-to-end autonomous driving → VLMs for autonomous driving

Abstract (arXiv)

End-to-end autonomous driving has emerged as a promising paradigm for achieving robust and intelligent driving policies. However, existing end-to-end methods still face significant challenges, such as suboptimal decision-making in complex scenarios. In this paper,we propose SimpleVSF (Simple VLM-Scoring Fusion), a novel framework that enhances end-to-end planning by leveraging the cognitive capabilities of Vision-Language Models (VLMs) and advanced trajectory fusion techniques. We utilize the conventional scorers and the novel VLM-enhanced scorers. And we leverage a robust weight fusioner for quantitative aggregation and a powerful VLM-based fusioner for qualitative, context-aware decision-making. As the leading approach in the ICCV 2025 NAVSIM v2 End-to-End Driving Challenge, our SimpleVSF framework demonstrates state-of-the-art performance, achieving a superior balance between safety, comfort, and efficiency.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in VLMs for autonomous driving, one of 9 directions in End-to-end autonomous driving. Builds on 37 of its 38 references that are in the map. First posted on arXiv 20 Oct 2025.

Builds on

37 of 38 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion25 Feb
  2. 2024VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision19 Dec
  3. 2024SimpleLLM4AD: An End-to-End Vision-Language Model with Graph Visual Question Answering for Autonomous Driving31 Jul
  4. 2024VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes9 May
  5. 2023DriveLM: Driving with Graph Visual Question Answering21 Dec
  6. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Driving21 Mar

Other references · 31

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2023Visual Instruction Tuningcited by 7,792
  3. 2025Qwen2.5-VL Technical Reportcited by 5,418
  4. 2023Improved Baselines with Visual Instruction Tuningcited by 4,362
  5. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
  6. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
  7. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
  8. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  9. 2022Planning-oriented Autonomous Drivingcited by 1,068
  10. 2023CogVLM: Visual Expert for Pretrained Language Modelscited by 704
  11. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  12. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 477
19 more
  1. 2025Kimi-VL Technical Reportcited by 381
  2. 2023EVA-02: A Visual Representation for Neon Genesiscited by 377
  3. 2019A Survey of Autonomous Driving: Common Practices and Emerging Technologiescited by 373
  4. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  5. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
  6. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 287
  7. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 239
  8. 2024CogVLM2: Visual Language Models for Image and Video Understandingcited by 214
  9. 2019An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detectioncited by 163
  10. 2024Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Drivingcited by 156
  11. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  12. 2025DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Drivingcited by 125
  13. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  14. 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 63
  15. 2023Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Modelscited by 59
  16. 2024VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Drivingcited by 49
  17. 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
  18. 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 41
  19. 2024QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Drivingcited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
  2. 2025VLAD: A VLM-Augmented Autonomous Driving Framework with Hierarchical Planning and Interpretable Decision Process
  3. 2025SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving
  4. 2026NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving
  5. 2025VERDI: VLM-Embedded Reasoning for Autonomous Driving
  6. 2025RoboDriveVLM: A Novel Benchmark and Baseline towards Robust Vision-Language Models for Autonomous Driving
  7. 2025Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving
  8. 2026AppleVLM: End-to-end Autonomous Driving with Advanced Perception and Planning-Enhanced Vision-Language Models