:sunglasses: Awesome VLA for Autonomous Driving

Autonomous driving has long relied on modular "Perception-Decision-Action" pipelines, whose hand-crafted interfaces and rule-based components often struggle in complex, dynamic, or long-tailed scenarios. Their cascaded structure also amplifies upstream perception errors, undermining downstream planning and control.

This survey reviews vision-action (VA) models and vision-language-action (VLA) models for autonomous driving. We trace the evolution from early VA approaches to modern VLA frameworks, and organize existing methods into two principal paradigms:

• End-to-End VLA, which integrates perception, reasoning, and planning within a single model.
• Dual-System VLA, which separates slow deliberation (via VLMs) from fast, safety-critical execution (via planners).

For more details, kindly refer to our :books: Paper, :globe_with_meridians: Project Page, and :hugs: HuggingFace Leaderboard.

:books: Citation

If you find this work helpful for your research, please kindly consider citing our paper:

@article{survey_vla4ad,
    title   = {Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future},
    author  = {Tianshuai Hu and Xiaolu Liu and Song Wang and Yiyao Zhu and Ao Liang and Lingdong Kong and Guoyang Zhao and Zeying Gong and Jun Cen and Zhiyu Huang and Xiaoshuai Hao and Linfeng Li and Hang Song and Xiangtai Li and Jun Ma and Shaojie Shen and Jianke Zhu and Dacheng Tao and Ziwei Liu and Junwei Liang},
    journal = {arXiv preprint arXiv:2512.16760},
    year    = {2025},
}

@article{survey_3d_4d_world_models,
    title   = {{3D} and {4D} World Modeling: A Survey},
    author  = {Lingdong Kong and Wesley Yang and Jianbiao Mei and Youquan Liu and Ao Liang and Dekai Zhu and Dongyue Lu and Wei Yin and Xiaotao Hu and Mingkai Jia and Junyuan Deng and Kaiwen Zhang and Yang Wu and Tianyi Yan and Shenyuan Gao and Song Wang and Linfeng Li and Liang Pan and Yong Liu and Jianke Zhu and Wei Tsang Ooi and Steven C. H. Hoi and Ziwei Liu},
    journal = {arXiv preprint arXiv:2509.07996},
    year    = {2025}
}

Table of Contents

• 1. Vision-Action Models
  • Action-Only Models
  • Perception-Action Models
  • Image-Based World Models
  • Occupancy-Based World Models
  • Latent-Based World Models
• 2. Vision-Language-Action Models
  • Textual Action Generator
  • Numerical Action Generator
  • Explicit Action Guidance
  • Implicit Representations Transfer
• 3. Datasets & Benchmarks
  • Vision-Action Datasets
  • Vision-Language-Action Datasets
• 4. Applications
• 5. Other Resources

1. Vision-Action Models

:one: Action-Only Models

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
LBC	Learning by Cheating	CoRL 2020	-
Latent-DRL	End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances	CVPR 2020	-	-
NEAT	NEAT: Neural Attention Fields for End-to-End Autonomous Driving	ICCV 2021	-
Roach	End-to-End Urban Driving by Imitating a Reinforcement Learning Coach	ICCV 2021
WoR	Learning to Drive from A World on Rails	ICCV 2021
TCP	Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline	NeurIPS 2022	-
Urban-Driver	Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients	CoRL 2022
LAV	Learning from All Vehicles	CVPR 2022
TransFuser	TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving	TPAMI 2023	-
GRI	GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving	Robotics 2023	-	-
BEVPlanner	Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?	CVPR 2024	-
Raw2Drive	Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)	NeurIPS 2025	-	-
RAD	RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning	NeurIPS 2025		-
TrajDiff	TrajDiff: End-to-End Autonomous Driving without Perception Annotation	arXiv 2025	-
SimScale	SimScale: Learning to Drive via Real-World Simulation at Scale	arXiv 2025
-	Addressing the Waypoint-Action Gap in End-to-End Autonomous Driving via Vehicle Motion Models	arXiv 2026	-	-

:two: Perception-Action Models

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
ST-P3	ST-P3: End-to-End Vision-Based Autonomous Driving via Spatial-Temporal Feature Learning	ECCV 2022	-
UniAD	Planning-Oriented Autonomous Driving	CVPR 2023	-
VAD	VAD: Vectorized Scene Representation for Efficient Autonomous Driving	ICCV 2023	-
OccNet	Scene as Occupancy	ICCV 2023	-
GenAD	GenAD: Generative End-to-End Autonomous Driving	ECCV 2024	-
PARA-Drive	PARA-Drive: Parallelized Architecture for Real-Time Autonomous Driving	CVPR 2024		-
Hydra-MDP	Hydra-MDP: End-to-End Multimodal Planning with Multi-Target Hydra-Distillation	CVPRW 2024
SparseAD	SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving	arXiv 2024	-	-
GaussianAD	GaussianAD: Gaussian-Centric End-to-End Autonomous Driving	arXiv 2024	-	-
DiFSD	DiFSD: Ego-Centric Fully Sparse Paradigm with Uncertainty Denoising and Iterative Refinement for Efficient End-to-End Self-Driving	arXiv 2024	-
DriveTransformer	DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving	ICLR 2025	-
SparseDrive	SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation	ICRA 2025	-
DiffusionDrive	DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving	CVPR 2025	-
GoalFlow	GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving	CVPR 2025
GuideFlow	GuideFlow: Constraint-Guided Flow Matching for Planning in End-to-End Autonomous Driving	arXiv 2025	-
ETA	ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models	arXiv 2025	-
Geo	Spatial Retrieval Augmented Autonomous Driving	arXiv 2025	-	-
DiffusionDriveV2	DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving	arXiv 2025	-
NaviHydra	NaviHydra: Controllable Navigation-Guided End-to-End Autonomous Driving with Hydra Distillation	arXiv 2025	-	-
Mimir	Mimir: Hierarchical Goal-Driven Diffusion with Uncertainty Propagation for End-to-End Autonomous Driving	arXiv 2025	-
FROST-Drive	FROST-Drive: Scalable and Efficient End-to-End Driving with a Frozen Vision Encoder	arXiv 2026	-	-
DrivoR	Driving on Registers	arXiv 2026
SPS	See Less, Drive Better: Generalizable End-to-End Autonomous Driving via Foundation Models Stochastic Patch Selection	arXiv 2026	-	-
BevAD	What Matters for Scalable and Robust Learning in End-to-End Driving Planners?	CVPR 2026

:three: Image-Based World Models

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
DriveDreamer	DriveDreamer: Towards Real-World-Driven World Models for Autonomous Driving	ECCV 2024
GenAD	GenAD: Generalized Predictive Model for Autonomous Driving	CVPR 2024	-
Drive-WM	Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving	CVPR 2024
DrivingWorld	DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT	arXiv 2024
Imagine-2-Drive	Imagine-2-Drive: Leveraging High-Fidelity World Models via Multi-Modal Diffusion Policies	IROS 2025		-
DrivingGPT	DrivingGPT: Unifying Driving World Modeling and Planning with Multi-Modal Autoregressive Transformers	ICCV 2025		-
Epona	Epona: Autoregressive Diffusion World Model for Autonomous Driving	ICCV 2025
VaViM	VaViM and VaVAM: Autonomous Driving through Video Generative Modeling	arXiv 2025
UniDrive-WM	UniDrive-WM: Unified Understanding, Planning and Generation World Model For Autonomous Driving	arXiv 2026		-
DwD	Driving with DINO: Vision Foundation Features as a Unified Bridge for Sim-to-Real Generation in Autonomous Driving	arXiv 2026	-	-
WorldDrive	Bridging Scene Generation and Planning: Driving with World Model via Unifying Vision and Motion Representation	arXiv 2026	-
OmniDreams	NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation	arXiv 2026	-	-
DriveDreamer-Policy	DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning	arXiv 2026	-	-
DriveVA	DriveVA: Video Action Models are Zero-Shot Drivers	arXiv 2026	-	-
Xiaomi EV World Model	Xiaomi Auto World Model: A Joint World Model Integrating Reconstruction and Generation for Autonomous Driving	arXiv 2026	-	-
HERMES++	HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation	arXiv 2026	-	-
LMGenDrive	LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving	arXiv 2026	-	-
X-World	X-World: Controllable Ego-Centric Multi-Camera World Models for Scalable End-to-End Driving	arXiv 2026	-	-

:four: Occupancy-Based World Models

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
OccWorld	OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving	ECCV 2024
NeMo	Neural Volumetric World Models for Autonomous Driving	ECCV 2024	-	-
OccVAR	OCCVAR: Scalable 4D Occupancy Prediction via Next-Scale Prediction	OpenReview 2024	-	-
RenderWorld	RenderWorld: World Model with Self-Supervised 3D Label	arXiv 2024	-	-
DFIT-OccWorld	An Efficient Occupancy World Model via Decoupled Dynamic Flow and Image-assisted Training	arXiv 2024	-	-
Drive-OccWorld	Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving	AAAI 2025
T³Former	Temporal Triplane Transformers as Occupancy World Models	arXiv 2025	-	-
OmniNWM	OmniNWM: Omniscient Driving Navigation World Models	arXiv 2025	-
AD-R1	AD-R1: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving with Impartial World Models	arXiv 2025	-	-
SparseOccVLA	SparseOccVLA: Bridging Occupancy and Vision-Language Models via Sparse Queries for Unified 4D Scene Understanding and Planning	arXiv 2026	-
GEM	GEM: Gaussian Evolution Model for Occupancy Forecasting and Motion Planning	arXiv 2026	-	-

:five: Latent-Based World Models

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
Covariate-Shift	Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models	arXiv 2024	-	-
World4Drive	World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model	ICCV 2025	-	-
WoTE	End-to-End Driving with Online Trajectory Evaluation via BEV World Model	ICCV 2025	-
LAW	Enhancing End-to-End Autonomous Driving with Latent World Model	ICLR 2025	-
SSR	Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Driving	ICLR 2025	-
Echo-Planning	Echo Planning for Autonomous Driving: From Current Observations to Future Trajectories and Back	arXiv 2025	-	-
SeerDrive	Future-Aware End-to-End Driving: Bidirectional Modeling of Trajectory Planning and Scene Evolution	NeurIPS 2025	-
Drive-JEPA	Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving	arXiv 2026	-
GraphWorld	GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Driving	arXiv 2026	-	-
Unified Driving Tokens	Unified Driving Tokens: Representation- and Geometry-Guided Discrete Tokenizer for Driving World Models and Planning	arXiv 2026	-	-
EponaV2	EponaV2: Driving World Model with Comprehensive Future Reasoning	arXiv 2026	-	-
IDOL	IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving	arXiv 2026	-	-
ExploreVLA	ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving	arXiv 2026	-	-
Kinematics-Aware LWM	Kinematics-Aware Latent World Models for Data-Efficient Autonomous Driving	arXiv 2026	-	-
SparseWorld	SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation	arXiv 2026	-	-
LWM Survey	Latent World Models for Automated Driving: A Unified Taxonomy, Evaluation Framework, and Open Challenges	arXiv 2026	-	-
World Models	World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications	arXiv 2026	-	-
DynVLA	DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving	arXiv 2026	-	-
DriveWorld-VLA	DriveWorld-VLA: Unified Latent-Space World Modeling with Vision-Language-Action for Autonomous Driving	arXiv 2026	-	-

2. Vision-Language-Action Models

:one: Textual Action Generator

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
DriveMLM	DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving	arXiv 2023	-
RAG-Driver	RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model	RSS 2024
RDA-Driver	Making Large Language Models Better Planners with Reasoning-Decision Alignment	ECCV 2024	-	-
DriveLM	DriveLM: Driving with Graph Visual Question Answering	ECCV 2024
DriveGPT4	DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model	RA-L 2024		-
DriVLMe	DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experience	IROS 2024
LLaDA	Driving Everywhere with Large Language Model Policy Adaptation	CVPR 2024
VLAAD	VLAAD: Vision and Language Assistant for Autonomous Driving	WACVW 2024	-
OccLLaMA	OccLLaMA: A Unified Occupancy-Language-Action World Model for Understanding and Generation Tasks in Autonomous Driving	arXiv 2024		-
Doe-1	Doe-1: Closed-Loop Autonomous Driving with Large World Model	arXiv 2024
LINGO-2	LINGO-2: Driving with Natural Language	-		-
SafeAuto	SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models	ICML 2025	-
OpenEMMA	OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving	WACV 2025	-
ReasonPlan	ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving	CoRL 2025	-
WKER	World Knowledge-Enhanced Reasoning Using Instruction-Guided Interactor in Autonomous Driving	AAAI 2025	-	-
OmniDrive	OmniDrive: A Holistic LLM-Agent Framework for Autonomous Driving with 3D Perception, Reasoning and Planning	CVPR 2025	-
S4-Driver	S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation	CVPR 2025		-
Occ-LLM	Occ-LLM: Enhancing Autonomous Driving with Occupancy-BasedLarge Language Models	ICRA 2025	-	-
DriveBench	Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives	ICCV 2025
FutureSightDrive	FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving	NeurIPS 2025
ImpromptuVLA	Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models	NeurIPS 2025
Sce2DriveX	Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning	RA-L 2025	-	-
EMMA	EMMA: End-to-End Multimodal Model for Autonomous Driving	TMLR 2025		-
DriveAgent-R1	DriveAgent-R1: Advancing VLM-Based Autonomous Driving with Hybrid Thinking and Active Perception	arXiv 2025	-	-
Drive-R1	Drive-R1: Bridging Reasoning and Planning in VLMs for Autonomous Driving with Reinforcement Learning	arXiv 2025	-	-
FastDriveVLA	FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-Based Token Pruning	arXiv 2025	-	-
WiseAD	WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model	arXiv 2025
AutoDrive-R²	AutoDrive-R²: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving	arXiv 2025	-	-
OmniReason	OmniReason: A Temporal-Guided Vision-Language-Action Framework for Autonomous Driving	arXiv 2025	-	-
OpenREAD	OpenREAD: Reinforced Open-Ended Reasoning for End-to-End Autonomous Driving with LLM-as-Critic	arXiv 2025	-
dVLM-AD	dVLM-AD: Enhance Diffusion Vision-Language-Model for Driving via Controllable Reasoning	arXiv 2025	-	-
PLA	A Unified Perception-Language-Action Framework for Adaptive Autonomous Driving	arXiv 2025	-	-
AlphaDrive	AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning	arXiv 2025	-
CoReVLA	CoReVLA: A Dual-Stage End-to-End Autonomous Driving Framework for Long-Tail Scenarios via Collect-and-Refine	arXiv 2025
WAM-Diff	WAM-Diff: A Masked Diffusion VLA Framework with MoE and Online Reinforcement Learning for Autonomous Driving	arXiv 2025	-
VLADriveBench	VLADriveBench: Evaluating CoT-Action Relationship in VLA for Autonomous Driving	arXiv 2026	-	-
BLUE	BLUE: Toward Better Language Use in Efficient Vision-Language-Action Models for Autonomous Driving	arXiv 2026	-	-
DriveMA	DriveMA: Rethinking Language Interfaces in Driving VLAs with One-Step Meta-Actions	arXiv 2026	-	-
C-CoT	C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving	arXiv 2026	-	-
MAGNIFIED	MAGNIFIED: RL Fine-tuning of Multimodal Large Language Models for Motion Planning	arXiv 2026	-	-
DriveReward	DriveReward: A Comprehensive Dataset and Generative Vision-Language Reward Model for Autonomous Driving	arXiv 2026	-	-
nuReasoning	nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving	arXiv 2026	-	-
Decision-Making	Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Driving	arXiv 2026	-	-
Is	Is VLA Reasoning Faithful? Probing Safety of Chain-of-Causation in Autonomous Driving Models	arXiv 2026	-	-
ReasonBreak	ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving	arXiv 2026	-	-
Intend,	Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving	arXiv 2026	-	-
Judge, Then Drive	Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving	arXiv 2026	-	-
EvoDrive	EvoDrive: Pareto Evolution for Safety-Critical Autonomous Driving via Self-Improving LLM Agents	arXiv 2026	-	-
Unifying	Unifying Language-Action Understanding and Generation for Autonomous Driving	arXiv 2026	-	-
MindDriver	MindDriver: Introducing Progressive Multimodal Reasoning for Autonomous Driving	arXiv 2026	-	-
HERMES	HERMES: A Holistic End-to-End Risk-Aware Multimodal Embodied System with Vision-Language Models for Long-Tail Autonomous Driving	arXiv 2026	-	-
Counterfactual VLA	Counterfactual VLA: Self-Reflective Vision-Language-Action Model with Adaptive Reasoning	arXiv 2025	-	-
OmniDrive-R1	OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving	arXiv 2025	-	-
BeLLA	BeLLA: End-to-End Birds Eye View Large Language Assistant for Autonomous Driving	arXiv 2025	-	-

:two: Numerical Action Generator

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
LMDrive	LMDrive: Closed-Loop End-to-End Driving with Large Language Models	CVPR 2024
BEVDriver	BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Driving	IROS 2025	-	-
CoVLA-Agent	CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving	WACV 2025		-
ORION	ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation	ICCV 2025
SimLingo	SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment	CVPR 2025
DriveGPT4-V2	DriveGPT4-V2: Harnessing Large Language Model Capabilities for Enhanced Closed-Loop Autonomous Driving	CVPR 2025	-	-
AutoVLA	AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning	NeurIPS 2025
DriveMoE	DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving	arXiv 2025
DSDrive	DSDrive: Distilling Large Language Model for Lightweight End-to-End Autonomous Driving with Unified Reasoning and Planning	arXiv 2025	-	-
OccVLA	OccVLA: Vision-Language-Action Model with Implicit 3D Occupancy Supervision.	arXiv 2025	-	-
VDRive	VDRive: Leveraging Reinforced VLA and Diffusion Policy for End-to-End Autonomous Driving	arXiv 2025	-	-
ReflectDrive	Discrete Diffusion for Reflective Vision-Language-Action Models in Autonomous Driving	arXiv 2025	-
E3AD	E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving	arXiv 2025	-	-
LCDrive	Latent Chain-of-Thought World Modeling for End-to-End Driving	arXiv 2025	-	-
Alpamayo-R1	Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail	arXiv 2025	-	-
UniUGP	UniUGP: Unifying understanding, generation, and planing for end-to-end autonomous driving.	arXiv 2025	-	-
MindDrive	MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Driving	arXiv 2025	-	-
AdaThinkDrive	AdaThinkDrive: Adaptive Thinking via Reinforcement Learning for Autonomous Driving	arXiv 2025	-	-
Percept-WAM	Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Driving	arXiv 2025	-	-
Reasoning-VLA	Reasoning-VLA: A Fast and General Vision-Language-Action Reasoning Model for Autonomous Driving	arXiv 2025	-	-
SpaceDrive	SpaceDrive: Infusing Spatial Awareness into VLM-Based Autonomous Driving	arXiv 2025	-	-
OpenDriveVLA	OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model	AAAI 2026
WAM-Flow	WAM-Flow: Parallel Coarse-to-Fine Motion Planning via Discrete Flow Matching for Autonomous Driving	CVPR 2026
ColaVLA	ColaVLA: Leveraging Cognitive Latent Reasoning for Hierarchical Parallel Trajectory Planning in Autonomous Driving	CVPR 2026
AutoMoT	AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving	arXiv 2026	-	-
OneDrive	OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models	arXiv 2026	-	-
UniDriveVLA	UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving	arXiv 2026	-	-
VLA-World	Learning Vision-Language-Action World Models for Autonomous Driving	arXiv 2026	-	-
Metis	Metis: A Generalizable and Efficient World-Action Model for Autonomous Driving and Urban Navigation	arXiv 2026	-	-
MindVLA-U1	MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving	arXiv 2026	-	-
DVGT-2	DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale	arXiv 2026	-	-
VLGA	VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving	arXiv 2026	-	-
VECTOR-Drive	VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving	arXiv 2026	-	-
ChainFlow-VLA	ChainFlow-VLA: Causal Flow Planning with Vision-Language Models	arXiv 2026	-	-
LVDrive	LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model	arXiv 2026	-	-
StyleVLA	StyleVLA: Driving Style-Aware Vision Language Action Model for Autonomous Driving	arXiv 2026	-	-
Masked-VLA-Diffusion	Efficient and Explainable End-to-End Autonomous Driving via Masked Vision-Language-Action Diffusion	arXiv 2026	-	-
Uni-World VLA	Uni-World VLA: Interleaved World Modeling and Planning for Autonomous Driving	arXiv 2026	-	-
Does	Does Visual Information Play a Decisive Role in Vision-Language-Action Model Driving Behavior?	arXiv 2026	-	-
Reasoning	Reasoning About Traversability: Language-Guided Off-Road 3D Trajectory Planning	arXiv 2026	-	-
SpanVLA	SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model	arXiv 2026	-	-
Sim2Real-AD	Sim2Real-AD: A Modular Sim-to-Real Framework for Deploying VLM-Guided Reinforcement Learning in Real-World Autonomous Driving	arXiv 2026	-	-
Drive My Way	Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving	arXiv 2026	-	-
DriveVLM-RL	DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving	arXiv 2026	-	-
Learning from Mistakes	Learning from Mistakes: Post-Training for Driving VLA with Takeover Data	arXiv 2026	-	-
SAMoE-VLA	SAMoE-VLA: A Scene Adaptive Mixture-of-Experts Vision-Language-Action Model for Autonomous Driving	arXiv 2026	-	-
LaST-VLA	LaST-VLA: Thinking in Latent Spatio-Temporal Space for Vision-Language-Action in Autonomous Driving	arXiv 2026	-	-

:three: Explicit Action Guidance

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
DriveVLM	DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models	CoRL 2024		-
LeapAD	Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving	NeurIPS 2024
FasionAD	FASIONAD: Fast and Slow Fusion Thinking Systems for Human-Like Autonomous Driving with Adaptive Feedback	arXiv 2024	-	-
Senna	Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving	arXiv 2024	-
DualAD	DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving	IROS 2025
DME-Driver	DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving	AAAI 2025	-	-
SOLVE	SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving	CVPR 2025	-	-
ReAL-AD	ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving	ICCV 2025		-
LeapVAD	LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking	TNNLS 2025	-	-
DiffVLA	DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving	arXiv 2025	-	-
FasionAD++	FASIONAD++: Integrating High-Level Instruction and Information Bottleneck in Fast-Slow fusion Systems for Enhanced Safety in Autonomous Driving with Adaptive Feedback	arXiv 2025	-	-
HiST-VLA	HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving	arXiv 2026	-	-
Senna-2	Senna-2: Aligning VLM and End-to-End Driving Policy for Consistent Decision Making and Planning	arXiv 2026	-	-
From	From Representational Complementarity to Dual Systems: Synergizing VLM and Vision-Only Backbones for End-to-End Driving	arXiv 2026	-	-
Fast-dDrive	Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving	arXiv 2026	-	-
DiffVLA++	DiffVLA++: Bridging Cognitive Reasoning and End-to-End Driving through Metric-Guided Alignment	arXiv 2025	-	-
RT-VLA	RT-VLA: Real-Time Vision-Language-Action Models via Knowledge Distillation	arXiv 2026	-	-
Slow	Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation	arXiv 2026	-	-
SimpleVSF	SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving	arXiv 2025	-	-
CoWorld-VLA	CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving	arXiv 2026	-	-
OneVL	Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation	arXiv 2026	-	-
WorldVLM	WorldVLM: Combining World Model Forecasting and Vision-Language Reasoning	arXiv 2026	-	-
NaviDriveVLM	NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving	arXiv 2026	-	-
PRAM-R	PRAM-R: A Perception-Reasoning-Action-Memory Framework with LLM-Guided Modality Routing for Adaptive Autonomous Driving	arXiv 2026	-	-
CorrectAD	CorrectAD: A Self-Correcting Agentic System to Improve End-to-end Planning in Autonomous Driving	arXiv 2025	-	-
MTRDrive	MTRDrive: Memory-Tool Synergistic Reasoning for Robust Autonomous Driving in Corner Cases	arXiv 2025	-	-

:four: Implicit Representations Transfer

:timer_clock: In chronological order, from the earliest to the latest.

Model	Paper	Venue	Website	GitHub
VLP	VLP: Vision Language Planning for Autonomous Driving	CVPR 2024	-	-
VLM-AD	VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision	CoRL 2025	-	-
DiMA	Distilling Multi-modal Large Language Models for Autonomous Driving	CVPR 2025	-	-
DINO-Foresight	DINO-Foresight: Looking into the Future with DINO	NeurIPS 2025
ALN-P3	ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving	arXiv 2025	-	-
VERDI	VERDI: VLM-Embedded Reasoning for Autonomous Driving	arXiv 2025	-	-
VLM-E2E	VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion	arXiv 2025	-	-
ReCogDrive	ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving	arXiv 2025
InsightDrive	InsightDrive: Insight Scene Representation for End-to-End Autonomous Driving	arXiv 2025	-
NetRoller	NetRoller: Interfacing General and Specialized Models for End-to-End Autonomous Driving	arXiv 2025	-
ViLaD	ViLaD: A Large Vision Language Diffusion Framework for End-to-End Autonomous Driving	arXiv 2025	-	-
OmniScene	OmniScene: Attention-Augmented Multimodal 4D Scene Understanding for Autonomous Driving	arXiv 2025	-	-
LMAD	LMAD: Integrated End-to-End VisionLanguage Model for Explainable Autonomous Driving	arXiv 2025	-	-
BEVLM	BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations	arXiv 2026	-	-

3. Datasets & Benchmarks

:timer_clock: In chronological order, from the earliest to the latest.

:one: Vision-Action Datasets

Dataset	Paper	Venue	Website	GitHub
BDD100K	BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning	CVPR 2020
nuScenes	nuScenes: A Multimodal Dataset for Autonomous Driving	CVPR 2020		-
Waymo	Scalability in Perception for Autonomous Driving: Waymo Open Dataset	CVPR 2020
nuPlan	nuPlan: A Closed-Loop ML-Based Planning Benchmark for Autonomous Vehicles	arXiv 2021
Argoverse 2	Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting	NeurIPS 2021
Bench2Drive	Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-to-End Autonomous Driving	NeurIPS 2024	-
RoboBEV	Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving	TPAMI 2025	-
WOD-E2E	WOD-E2E: Waymo Open Dataset for End-to-End Driving in Challenging Long-Tail Scenarios	arXiv 2025
navdream	The Constant Eye: Benchmarking and Bridging Appearance Robustness in Autonomous Driving	arXiv 2026	-	-

:two: Vision-Language-Action Datasets

Dataset	Paper	Venue	Website	GitHub
BDD-X	Textual Explanations for Self-Driving Vehicles	ECCV 2018	-
Talk2Car	Talk2Car: Predicting Physical Trajectories for Natural Language Commands	IEEE Access 2022	-
SDN	DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents	EMNLP 2022	-
DriveMLM	DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving	arXiv 2023	-
LMDrive	LMDrive: Closed-Loop End-to-End Driving with Large Language Models	CVPR 2024
DriveLM-nuScenes	DriveLM: Driving with Graph Visual Question Answering	ECCV 2024
HBD	DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving	AAAI 2025	-	-
VLAAD	VLAAD: Vision and Language Assistant for Autonomous Driving	WACVW 2024	-
SUP-AD	DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models	CoRL 2024		-
NuInstruct	Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models	CVPR 2024	-
WOMD-Reasoning	WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving	ICML 2025
DriveCoT	DriveCoT: Integrating Chain-of-Thought Reasoning with End-to-End Driving	arXiv 2024		-
Reason2Drive	Reason2Drive: Towards Interpretable and Chain-Based Reasoning for Autonomous Driving	ECCV 2024	-
DriveBench	Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives	ICCV 2025
MetaAD	AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning	arXiv 2025
OmniDrive	OmniDrive: A Holistic LLM-Agent Framework for Autonomous Driving with 3D Perception, Reasoning and Planning	CVPR 2025	-
NuInteract	Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous Driving	arXiv 2025	-	-
DriveAction	DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models	arXiv 2025	-	-
ImpromptuVLA	Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models	arXiv 2025
CoVLA	CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Driving	WACV 2025		-
OmniReason-nuScenes	OmniReason: A Temporal-Guided Vision-Language-Action Framework for Autonomous Driving	arXiv 2025	-	-
OmniReason-B2D	OmniReason: A Temporal-Guided Vision-Language-Action Framework for Autonomous Driving	arXiv 2025	-	-
Bench2Drive-VL	Bench2Drive-VL: Benchmarks for Closed-Loop Autonomous Driving with Vision-Language Models	arXiv 2026	-	-
V2X-QA	V2X-QA: A Comprehensive Reasoning Dataset and Benchmark for Multimodal Large Language Models in Autonomous Driving Across Ego, Infrastructure, and Cooperative Views	arXiv 2026	-	-
DriveSpatial	DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving	arXiv 2026	-	-
GeoDrive-Bench	GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving	arXiv 2026	-	-
Vega	Vega: Learning to Drive with Natural Language Instructions	arXiv 2026	-	-
doScenes/DVDrive	A DVDrive Approach for doScenes Instructed Driving Challenge	arXiv 2026	-	-
PedestrianQA	PEDESTRIANQA: A Benchmark for Vision-Language Models on Pedestrian Intention and Trajectory Prediction	arXiv 2026	-	-
Where	Where Does the Answer Come From? Benchmarking View-Level Visual Evidence Identification in Multi-View MLLMs for Autonomous Driving	arXiv 2026	-	-
EventDrive	EventDrive: Event Cameras for Vision-Language Driving Intelligence	arXiv 2026	-	-
CrashSight	CrashSight: A Phase-Aware, Infrastructure-Centric Video Benchmark for Traffic Crash Scene Understanding and Reasoning	arXiv 2026	-	-
Towards Safe Mobility	Towards Safe Mobility: A Unified Transportation Foundation Model enabled by Open-Ended Vision-Language Dataset	arXiv 2026	-	-
TRIP-Evaluate	TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation	arXiv 2026	-	-
DriveJudge	DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Models	arXiv 2026	-	-
ReactSim-Bench	ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving	arXiv 2026	-	-
AnchorDrive	AnchorDrive: LLM Scenario Rollout with Anchor-Guided Diffusion Regeneration for Safety-Critical Scenario Generation	arXiv 2026	-	-
ScenePilot-Bench	ScenePilot-4K: A Large-Scale First-Person Dataset and Benchmark for Vision-Language Models in Autonomous Driving	arXiv 2026	-	-
RoboDriveVLM	RoboDriveVLM: A Novel Benchmark and Baseline towards Robust Vision-Language Models for Autonomous Driving	arXiv 2025	-	-
Is	Is Your VLM for Autonomous Driving Safety-Ready? A Comprehensive Benchmark for Evaluating External and In-Cabin Risks	arXiv 2025	-	-
CARScenes	CARScenes: Semantic VLM Dataset for Safe Autonomous Driving	arXiv 2025	-	-

4. Applications

5. Other Resources