Cover Image

Safety-aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Haohong, Ding, Wenhao, Liu, Zuxin, Niu, Yaru, Zhu, Jiacheng, Niu, Yuming, Zhao, Ding
Format:	Preprint
Published:	2023
Subjects:	Robotics Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving
by: Lin, Haohong, et al.
Published: (2025)

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
by: Lin, Haohong, et al.
Published: (2024)

Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization
by: Yang, Fan, et al.
Published: (2023)

HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
by: Zhang, Hao, et al.
Published: (2026)

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

Learning Multi-Agent Loco-Manipulation for Long-Horizon Quadrupedal Pushing
by: Feng, Yuming, et al.
Published: (2024)

Safety2Drive: Safety-Critical Scenario Benchmark for the Evaluation of Autonomous Driving
by: Li, Jingzheng, et al.
Published: (2025)

Enhancing Autonomous Driving Safety through World Model-Based Predictive Navigation and Adaptive Learning Algorithms for 5G Wireless Applications
by: Ding, Hong, et al.
Published: (2024)

Simulator Ensembles for Trustworthy Autonomous Driving Testing
by: Sorokin, Lev, et al.
Published: (2025)

CorrectionPlanner: Self-Correction Planner with Reinforcement Learning in Autonomous Driving
by: Guo, Yihong, et al.
Published: (2026)

Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning
by: Weiwei, Liu, et al.
Published: (2024)

Causal Flow Q-Learning for Robust Offline Reinforcement Learning
by: Li, Mingxuan, et al.
Published: (2026)

VLM-SAFE: Vision-Language Model-Guided Safety-Aware Reinforcement Learning with World Models for Autonomous Driving
by: Qu, Yansong, et al.
Published: (2025)

Prediction-aware and Reinforcement Learning based Altruistic Cooperative Driving
by: Valiente, Rodolfo, et al.
Published: (2022)

RealDrive: Retrieval-Augmented Driving with Diffusion Models
by: Ding, Wenhao, et al.
Published: (2025)

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning
by: Xu, Chengkai, et al.
Published: (2025)

Causal Composition Diffusion Model for Closed-loop Traffic Generation
by: Lin, Haohong, et al.
Published: (2024)

Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios
by: Li, Jingzheng, et al.
Published: (2025)

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
by: Yao, Yihang, et al.
Published: (2023)

Action Space Reduction Strategies for Reinforcement Learning in Autonomous Driving
by: Delavari, Elahe, et al.
Published: (2025)

Less is More: Efficient Brain-Inspired Learning for Autonomous Driving Trajectory Prediction
by: Liao, Haicheng, et al.
Published: (2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
by: Liu, Zuxin, et al.
Published: (2023)

Diffusion Models for Safety Validation of Autonomous Driving Systems
by: Wang, Juanran, et al.
Published: (2025)

Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining
by: Niu, Yaru, et al.
Published: (2025)

EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data
by: Zhang, Jesse, et al.
Published: (2024)

Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning
by: Lee, Dongsu, et al.
Published: (2025)

Diffusion Models for Offline Multi-agent Reinforcement Learning with Safety Constraints
by: Huang, Jianuo
Published: (2024)

Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving
by: Huang, Zilin, et al.
Published: (2024)

DriveMind: A Dual Visual Language Model-based Reinforcement Learning Framework for Autonomous Driving
by: Wasif, Dawood, et al.
Published: (2025)

CtRL-Sim: Reactive and Controllable Driving Agents with Offline Reinforcement Learning
by: Rowe, Luke, et al.
Published: (2024)

Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving
by: Jin, Guizhe, et al.
Published: (2025)

Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction
by: Wang, Bonan, et al.
Published: (2025)

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving
by: Lian, Zhexi, et al.
Published: (2026)

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

SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Driving
by: Huynh, Minh Tri, 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)

SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Driving
by: Luo, Xuewen, et al.
Published: (2025)

Is Your VLM for Autonomous Driving Safety-Ready? A Comprehensive Benchmark for Evaluating External and In-Cabin Risks
by: Meng, Xianhui, et al.
Published: (2025)

Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking Control
by: Wang, Yanran, et al.
Published: (2023)

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