Cover Image

Natural Language Instructions for Scene-Responsive Human-in-the-Loop Motion Planning in Autonomous Driving using Vision-Language-Action Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Martinez-Sanchez, Angel, Roy, Parthib, Greer, Ross
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Vision and Language: Novel Representations and Artificial intelligence for Driving Scene Safety Assessment and Autonomous Vehicle Planning
by: Greer, Ross, et al.
Published: (2026)

doScenes: An Autonomous Driving Dataset with Natural Language Instruction for Human Interaction and Vision-Language Navigation
by: Roy, Parthib, et al.
Published: (2024)

Perception Without Vision for Trajectory Prediction: Ego Vehicle Dynamics as Scene Representation for Efficient Active Learning in Autonomous Driving
by: Greer, Ross, et al.
Published: (2024)

Automated Data Curation Using GPS & NLP to Generate Instruction-Action Pairs for Autonomous Vehicle Vision-Language Navigation Datasets
by: Roque, Guillermo, et al.
Published: (2025)

DepthVision: Enabling Robust Vision-Language Models with GAN-Based LiDAR-to-RGB Synthesis for Autonomous Driving
by: Kirchner, Sven, et al.
Published: (2025)

SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment
by: Renz, Katrin, et al.
Published: (2025)

A Survey on Vision-Language-Action Models for Autonomous Driving
by: Jiang, Sicong, et al.
Published: (2025)

MindDrive: A Vision-Language-Action Model for Autonomous Driving via Online Reinforcement Learning
by: Fu, Haoyu, et al.
Published: (2025)

DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving
by: jia, Feiyang, et al.
Published: (2026)

Reasoning-VLA: A Fast and General Vision-Language-Action Reasoning Model for Autonomous Driving
by: Zhang, Dapeng, et al.
Published: (2025)

SIMPACT: Simulation-Enabled Action Planning using Vision-Language Models
by: Liu, Haowen, et al.
Published: (2025)

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving
by: Yang, Zhenjie, et al.
Published: (2025)

Explanation for Trajectory Planning using Multi-modal Large Language Model for Autonomous Driving
by: Yamazaki, Shota, et al.
Published: (2024)

Unifying Language-Action Understanding and Generation for Autonomous Driving
by: Wang, Xinyang, et al.
Published: (2026)

Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
by: Gao, Haoxiang, et al.
Published: (2025)

DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving
by: Jiang, Anqing, et al.
Published: (2025)

AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving
by: Huang, Wenhui, et al.
Published: (2026)

DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models
by: Song, Jingyu, et al.
Published: (2025)

LaMP: Learning Vision-Language-Action Policies with 3D Scene Flow as Latent Motion Prior
by: Wang, Xinkai, et al.
Published: (2026)

Vega: Learning to Drive with Natural Language Instructions
by: Zuo, Sicheng, et al.
Published: (2026)

UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving
by: Li, Yongkang, et al.
Published: (2026)

OccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving
by: Wei, Julong, et al.
Published: (2024)

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
by: Jiang, Bo, et al.
Published: (2024)

Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving
by: Gopalkrishnan, Akshay, et al.
Published: (2024)

QueryAdapter: Rapid Adaptation of Vision-Language Models in Response to Natural Language Queries
by: Chapman, Nicolas Harvey, et al.
Published: (2025)

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving
by: Tian, Kefei, et al.
Published: (2026)

Large Language Models Powered Context-aware Motion Prediction in Autonomous Driving
by: Zheng, Xiaoji, et al.
Published: (2024)

LoopVLA: Learning Sufficiency in Recurrent Refinement for Vision-Language-Action Models
by: Shen, Boyang, et al.
Published: (2026)

HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving
by: Wang, Yiru, et al.
Published: (2026)

Unified Vision-Language-Action Model
by: Wang, Yuqi, et al.
Published: (2025)

InstructVLA: Vision-Language-Action Instruction Tuning from Understanding to Manipulation
by: Yang, Shuai, et al.
Published: (2025)

DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale
by: Zuo, Sicheng, et al.
Published: (2026)

GeneralVLA: Generalizable Vision-Language-Action Models with Knowledge-Guided Trajectory Planning
by: Ma, Guoqing, et al.
Published: (2026)

DeeAD: Dynamic Early Exit of Vision-Language Action for Efficient Autonomous Driving
by: HU, Haibo, et al.
Published: (2025)

CLAP: Contrastive Latent Action Pretraining for Learning Vision-Language-Action Models from Human Videos
by: Zhang, Chubin, et al.
Published: (2026)

AutoDrive-QA: A Multiple-Choice Benchmark for Vision-Language Evaluation in Urban Autonomous Driving
by: Khalili, Boshra, et al.
Published: (2025)

CogVLA: Cognition-Aligned Vision-Language-Action Model via Instruction-Driven Routing & Sparsification
by: Li, Wei, et al.
Published: (2025)

A Unified Perception-Language-Action Framework for Adaptive Autonomous Driving
by: Zhang, Yi, et al.
Published: (2025)

AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
by: Xing, Shuo, et al.
Published: (2024)

Less is More: Lean yet Powerful Vision-Language Model for Autonomous Driving
by: Yang, Sheng, et al.
Published: (2025)