SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving
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
- 2025VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion25 Feb
- 2024VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision19 Dec
- 2024SimpleLLM4AD: An End-to-End Vision-Language Model with Graph Visual Question Answering for Autonomous Driving31 Jul
- 2024VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes9 May
- 2023DriveLM: Driving with Graph Visual Question Answering21 Dec
- 2023VAD: Vectorized Scene Representation for Efficient Autonomous Driving21 Mar
Other references · 31
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
- 2023Visual Instruction Tuningcited by 7,792
- 2025Qwen2.5-VL Technical Reportcited by 5,418
- 2023Improved Baselines with Visual Instruction Tuningcited by 4,362
- 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
- 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
- 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
- 2022Planning-oriented Autonomous Drivingcited by 1,068
- 2023CogVLM: Visual Expert for Pretrained Language Modelscited by 704
- 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
- 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 477
19 more
- 2025Kimi-VL Technical Reportcited by 381
- 2023EVA-02: A Visual Representation for Neon Genesiscited by 377
- 2019A Survey of Autonomous Driving: Common Practices and Emerging Technologiescited by 373
- 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
- 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
- 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 287
- 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 239
- 2024CogVLM2: Visual Language Models for Image and Video Understandingcited by 214
- 2019An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detectioncited by 163
- 2024Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Drivingcited by 156
- 2025Pseudo-Simulation for Autonomous Drivingcited by 141
- 2025DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Drivingcited by 125
- 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
- 2025Generalized Trajectory Scoring for End-to-end Multimodal Planningcited by 63
- 2023Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Modelscited by 59
- 2024VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Drivingcited by 49
- 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
- 2025Centaur: Robust End-to-End Autonomous Driving with Test-Time Trainingcited by 41
- 2024QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Drivingcited by 11
Built on by
Citing papers per year: 2025: 1; 2026: 1.
2 papers.
Similar, not cited
Close in wording, no citation either way
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- 2026NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving
- 2025VERDI: VLM-Embedded Reasoning for Autonomous Driving
- 2025RoboDriveVLM: A Novel Benchmark and Baseline towards Robust Vision-Language Models for Autonomous Driving
- 2025Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving
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