Buchumschlag

World Models for Autonomous Driving: An Initial Survey

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Guan, Yanchen, Liao, Haicheng, Li, Zhenning, Hu, Jia, Yuan, Runze, Li, Yunjian, Zhang, Guohui, Xu, Chengzhong
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Machine Learning Artificial Intelligence Robotics
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Towards Human-Like Trajectory Prediction for Autonomous Driving: A Behavior-Centric Approach
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

NEST: A Neuromodulated Small-world Hypergraph Trajectory Prediction Model for Autonomous Driving
von: Wang, Chengyue, et al.
Veröffentlicht: (2024)

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

A Cognitive-Based Trajectory Prediction Approach for Autonomous Driving
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

Minds on the Move: Decoding Trajectory Prediction in Autonomous Driving with Cognitive Insights
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

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

ROAR: Robust Accident Recognition and Anticipation for Autonomous Driving
von: Liu, Xingcheng, et al.
Veröffentlicht: (2025)

Addressing Corner Cases in Autonomous Driving: A World Model-based Approach with Mixture of Experts and LLMs
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

Human Observation-Inspired Trajectory Prediction for Autonomous Driving in Mixed-Autonomy Traffic Environments
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

SafeCast: Risk-Responsive Motion Forecasting for Autonomous Vehicles
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

Large Foundation Models for Trajectory Prediction in Autonomous Driving: A Comprehensive Survey
von: Dai, Wei, et al.
Veröffentlicht: (2025)

Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

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

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

DEMO: A Dynamics-Enhanced Learning Model for Multi-Horizon Trajectory Prediction in Autonomous Vehicles
von: Wang, Chengyue, et al.
Veröffentlicht: (2024)

Real-time Accident Anticipation for Autonomous Driving Through Monocular Depth-Enhanced 3D Modeling
von: Liao, Haicheng, et al.
Veröffentlicht: (2024)

GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language Models
von: Liao, Haicheng, et al.
Veröffentlicht: (2023)

Vehicle Dynamics Embedded World Models for Autonomous Driving
von: Li, Huiqian, et al.
Veröffentlicht: (2025)

A Survey on Large Language Model-empowered Autonomous Driving
von: Zhu, Yuxuan, et al.
Veröffentlicht: (2024)

BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
von: Zhou, Zikang, et al.
Veröffentlicht: (2024)

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles
von: Liao, Haicheng, et al.
Veröffentlicht: (2025)

Map-World: Masked Action planning and Path-Integral World Model for Autonomous Driving
von: Hu, Bin, et al.
Veröffentlicht: (2025)

Driving Through Uncertainty: Risk-Averse Control with LLM Commonsense for Autonomous Driving under Perception Deficits
von: Hu, Yuting, et al.
Veröffentlicht: (2025)

A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services
von: Katare, Dewant, et al.
Veröffentlicht: (2023)

Large Language Models for Human-like Autonomous Driving: A Survey
von: Li, Yun, et al.
Veröffentlicht: (2024)

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

Kinematics-Aware Latent World Models for Data-Efficient Autonomous Driving
von: Li, Jiazhuo, et al.
Veröffentlicht: (2026)

Diffusion-Based Planning for Autonomous Driving with Flexible Guidance
von: Zheng, Yinan, et al.
Veröffentlicht: (2025)

Ego-centric Learning of Communicative World Models for Autonomous Driving
von: Wang, Hang, et al.
Veröffentlicht: (2025)

Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion
von: Zhang, Lunjun, et al.
Veröffentlicht: (2023)

Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving
von: Su, Wensheng, et al.
Veröffentlicht: (2024)

Distributional Soft Actor-Critic with Harmonic Gradient for Safe and Efficient Autonomous Driving in Multi-lane Scenarios
von: Zhang, Feihong, et al.
Veröffentlicht: (2025)

Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis
von: Gao, Yuan, et al.
Veröffentlicht: (2025)

Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving
von: Xiao, Lingyu, et al.
Veröffentlicht: (2024)

SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
von: Zhang, Jiawei, et al.
Veröffentlicht: (2025)

Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving
von: Hu, Xuemin, et al.
Veröffentlicht: (2024)

Autonomous Driving Small-Scale Cars: A Survey of Recent Development
von: Li, Dianzhao, et al.
Veröffentlicht: (2024)