Cover Image

Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Haohong, Zhang, Yunzhi, Ding, Wenhao, Wu, Jiajun, Zhao, Ding
Format:	Preprint
Published:	2025
Subjects:	Robotics Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving
by: Lin, Haohong, et al.
Published: (2023)

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
by: Hua, Zhihua, et al.
Published: (2026)

CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning
by: Ang, Sining, et al.
Published: (2026)

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving
by: Oh, Haesung, et al.
Published: (2026)

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

A Knowledge-Driven Diffusion Policy for End-to-End Autonomous Driving Based on Expert Routing
by: Xu, Chengkai, et al.
Published: (2025)

SimpleVSF: VLM-Scoring Fusion for Trajectory Prediction of End-to-End Autonomous Driving
by: Zheng, Peiru, et al.
Published: (2025)

LightEMMA: Lightweight End-to-End Multimodal Model for Autonomous Driving
by: Qiao, Zhijie, et al.
Published: (2025)

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving
by: Zheng, Yinan, et al.
Published: (2026)

FocalAD: Local Motion Planning for End-to-End Autonomous Driving
by: Sun, Bin, et al.
Published: (2025)

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving
by: Zhao, Seth Z., et al.
Published: (2026)

Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving
by: Atakishiyev, Shahin, et al.
Published: (2024)

End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023
by: Lan, Gongjin, et al.
Published: (2023)

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning
by: Li, Miao, et al.
Published: (2025)

AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
by: Chai, Jinhao, et al.
Published: (2025)

Integrating End-to-End and Modular Driving Approaches for Online Corner Case Detection in Autonomous Driving
by: Kaljavesi, Gemb, et al.
Published: (2024)

Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
by: Moon, Seokha, et al.
Published: (2026)

Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs
by: Duan, Yiqun, et al.
Published: (2024)

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

SynAD: Enhancing Real-World End-to-End Autonomous Driving Models through Synthetic Data Integration
by: Kim, Jongsuk, et al.
Published: (2025)

Enhanced Safety in Autonomous Driving: Integrating Latent State Diffusion Model for End-to-End Navigation
by: Chu, Detian, et al.
Published: (2024)

An Open-Source Modular Benchmark for Diffusion-Based Motion Planning in Closed-Loop Autonomous Driving
by: Li, Yun, et al.
Published: (2026)

EMMA: End-to-End Multimodal Model for Autonomous Driving
by: Hwang, Jyh-Jing, et al.
Published: (2024)

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

ME$^3$-BEV: Mamba-Enhanced Deep Reinforcement Learning for End-to-End Autonomous Driving with BEV-Perception
by: Lu, Siyi, et al.
Published: (2025)

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
by: Zhao, Rui, et al.
Published: (2026)

DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planning
by: Yao, Wenhao, et al.
Published: (2025)

HERMES: A Holistic End-to-End Risk-Aware Multimodal Embodied System with Vision-Language Models for Long-Tail Autonomous Driving
by: Tang, Weizhe, et al.
Published: (2026)

SENTINEL: A Fully End-to-End Language-Action Model for Humanoid Whole Body Control
by: Wang, Yuxuan, 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)

Efficient Fusion and Task Guided Embedding for End-to-end Autonomous Driving
by: Guo, Yipin, et al.
Published: (2024)

Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving
by: Wu, Sihao, et al.
Published: (2024)

AppleVLM: End-to-end Autonomous Driving with Advanced Perception and Planning-Enhanced Vision-Language Models
by: Han, Yuxuan, et al.
Published: (2026)

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

From Imitation to Exploration: End-to-end Autonomous Driving based on World Model
by: Li, Yueyuan, et al.
Published: (2024)

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
by: Zhang, Yuhang, et al.
Published: (2025)

Interpretable Decision-Making for End-to-End Autonomous Driving
by: Mirzaie, Mona, et al.
Published: (2025)

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

SEAL: Vision-Language Model-Based Safe End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling
by: You, Junwei, et al.
Published: (2025)

Autonomous Vehicle Controllers From End-to-End Differentiable Simulation
by: Nachkov, Asen, et al.
Published: (2024)