Cover Image

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Yupeng, Yang, Pengxuan, Xing, Zebin, Zhang, Qichao, Zheng, Yuhang, Gao, Yinfeng, Li, Pengfei, Zhang, Teng, Xia, Zhongpu, Jia, Peng, Zhao, Dongbin
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mimir: Hierarchical Goal-Driven Diffusion with Uncertainty Propagation for End-to-End Autonomous Driving
by: Xing, Zebin, et al.
Published: (2025)

WorldRFT: Latent World Model Planning with Reinforcement Fine-Tuning for Autonomous Driving
by: Yang, Pengxuan, et al.
Published: (2025)

Data Scaling Laws for Imitation Learning-Based End-to-End Autonomous Driving
by: Zheng, Yupeng, et al.
Published: (2024)

Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
by: Wang, Linbo, et al.
Published: (2026)

DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving
by: Yang, Pengxuan, et al.
Published: (2026)

UncAD: Towards Safe End-to-end Autonomous Driving via Online Map Uncertainty
by: Yang, Pengxuan, et al.
Published: (2025)

TakeAD: Preference-based Post-optimization for End-to-end Autonomous Driving with Expert Takeover Data
by: Liu, Deqing, et al.
Published: (2025)

Dream to Drive with Predictive Individual World Model
by: Gao, Yinfeng, et al.
Published: (2025)

MeanFuser: Fast One-Step Multi-Modal Trajectory Generation and Adaptive Reconstruction via MeanFlow for End-to-End Autonomous Driving
by: Wang, Junli, et al.
Published: (2026)

PerlAD: Towards Enhanced Closed-loop End-to-end Autonomous Driving with Pseudo-simulation-based Reinforcement Learning
by: Gao, Yinfeng, et al.
Published: (2026)

Enhancing End-to-End Autonomous Driving with Latent World Model
by: Li, Yingyan, et al.
Published: (2024)

ComDrive: Comfort-Oriented End-to-End Autonomous Driving
by: Wang, Junming, et al.
Published: (2024)

PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning
by: Zheng, Yupeng, et al.
Published: (2024)

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
by: Wang, Junli, et al.
Published: (2026)

FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model
by: Lin, Hongbin, et al.
Published: (2025)

Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
by: Sun, Jiangxin, et al.
Published: (2026)

ResWorld: Temporal Residual World Model for End-to-End Autonomous Driving
by: Zhang, Jinqing, et al.
Published: (2026)

TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learning
by: Xing, Zebin, et al.
Published: (2025)

From Human Intention to Action Prediction: Intention-Driven End-to-End Autonomous Driving
by: Zheng, Huan, et al.
Published: (2025)

GaussianAD: Gaussian-Centric End-to-End Autonomous Driving
by: Zheng, Wenzhao, et al.
Published: (2024)

Latent Chain-of-Thought World Modeling for End-to-End Driving
by: Tan, Shuhan, et al.
Published: (2025)

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
by: Zhang, Lingjun, et al.
Published: (2026)

Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Driving
by: Han, Jianhua, et al.
Published: (2025)

DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
by: Jia, Xiaosong, et al.
Published: (2025)

GenAD: Generative End-to-End Autonomous Driving
by: Zheng, Wenzhao, et al.
Published: (2024)

SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
by: Sun, Wenchao, et al.
Published: (2024)

ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving
by: Liu, Xueyi, et al.
Published: (2025)

GoalFlow: Goal-Driven Flow Matching for Multimodal Trajectories Generation in End-to-End Autonomous Driving
by: Xing, Zebin, et al.
Published: (2025)

Learning from Mistakes: Post-Training for Driving VLA with Takeover Data
by: Gao, Yinfeng, et al.
Published: (2026)

World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving
by: Guan, Yanchen, et al.
Published: (2025)

Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)
by: Yang, Zhenjie, et al.
Published: (2025)

Cognitive-Hierarchy Guided End-to-End Planning for Autonomous Driving
by: Wang, Zhennan, et al.
Published: (2025)

Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
by: Geng, Jiaheng, et al.
Published: (2025)

MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Driving
by: Sun, Bin, et al.
Published: (2025)

ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving
by: Sheng, Zihao, et al.
Published: (2026)

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
by: Wu, Yanhao, et al.
Published: (2026)

Embodied Cognition Augmented End2End Autonomous Driving
by: Niu, Ling, et al.
Published: (2025)

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving
by: Jiang, Hao, et al.
Published: (2025)

TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
by: Wang, Jiawei, et al.
Published: (2025)

PokeVLA: Empowering Pocket-Sized Vision-Language-Action Model with Comprehensive World Knowledge Guidance
by: Zheng, Yupeng, et al.
Published: (2026)