A survey on multimodal large language models for autonomous driving

C Cui, Y Ma, X Cao, W Ye, Y Zhou… - Proceedings of the …, 2024 - openaccess.thecvf.com
With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving

W Wang, J Xie, CY Hu, H Zou, J Fan, W Tong… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have opened up new possibilities for intelligent agents,
endowing them with human-like thinking and cognitive abilities. In this work, we delve into …

Hilm-d: Towards high-resolution understanding in multimodal large language models for autonomous driving

X Ding, J Han, H Xu, W Zhang, X Li - arXiv preprint arXiv:2309.05186, 2023 - arxiv.org
Autonomous driving systems generally employ separate models for different tasks resulting
in intricate designs. For the first time, we leverage singular multimodal large language …

Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models

X Ding, J Han, H Xu, X Liang… - Proceedings of the …, 2024 - openaccess.thecvf.com
The rise of multimodal large language models (MLLMs) has spurred interest in language-
based driving tasks. However existing research typically focuses on limited tasks and often …

Vision language models in autonomous driving and intelligent transportation systems

X Zhou, M Liu, BL Zagar, E Yurtsever… - arXiv preprint arXiv …, 2023 - arxiv.org
The applications of Vision-Language Models (VLMs) in the fields of Autonomous Driving
(AD) and Intelligent Transportation Systems (ITS) have attracted widespread attention due to …

Lmdrive: Closed-loop end-to-end driving with large language models

H Shao, Y Hu, L Wang, G Song… - Proceedings of the …, 2024 - openaccess.thecvf.com
Despite significant recent progress in the field of autonomous driving modern methods still
struggle and can incur serious accidents when encountering long-tail unforeseen events …

Drivegpt4: Interpretable end-to-end autonomous driving via large language model

Z Xu, Y Zhang, E Xie, Z Zhao, Y Guo, KKY Wong… - arXiv preprint arXiv …, 2023 - arxiv.org
In the past decade, autonomous driving has experienced rapid development in both
academia and industry. However, its limited interpretability remains a significant unsolved …

[PDF][PDF] Drive like a human: Rethinking autonomous driving with large language models

D Fu, X Li, L Wen, M Dou, P Cai… - Proceedings of the …, 2024 - openaccess.thecvf.com
In this paper, we explore the potential of using a large language model (LLM) to understand
the driving environment in a human-like manner and analyze its ability to reason, interpret …

Drive as you speak: Enabling human-like interaction with large language models in autonomous vehicles

C Cui, Y Ma, X Cao, W Ye… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
The future of autonomous vehicles lies in the convergence of human-centric design and
advanced AI capabilities. Autonomous vehicles of the future will not only transport …

A survey of large language models for autonomous driving

Z Yang, X Jia, H Li, J Yan - arXiv preprint arXiv:2311.01043, 2023 - arxiv.org
Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …