Lmdrive: Closed-loop end-to-end driving with large language models
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 …
struggle and can incur serious accidents when encountering long-tail unforeseen events …
Lampilot: An open benchmark dataset for autonomous driving with language model programs
Autonomous driving (AD) has made significant strides in recent years. However existing
frameworks struggle to interpret and execute spontaneous user instructions such as" …
frameworks struggle to interpret and execute spontaneous user instructions such as" …
[PDF][PDF] Drive like a human: Rethinking autonomous driving with large language models
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 …
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
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 …
advanced AI capabilities. Autonomous vehicles of the future will not only transport …
Drivellm: Charting the path toward full autonomous driving with large language models
Human drivers instinctively reason with commonsense knowledge to predict hazards in
unfamiliar scenarios and to understand the intentions of other road users. However, this …
unfamiliar scenarios and to understand the intentions of other road users. However, this …
Drivegpt4: Interpretable end-to-end autonomous driving via large language model
In the past decade, autonomous driving has experienced rapid development in both
academia and industry. However, its limited interpretability remains a significant unsolved …
academia and industry. However, its limited interpretability remains a significant unsolved …
Languagempc: Large language models as decision makers for autonomous driving
Existing learning-based autonomous driving (AD) systems face challenges in
comprehending high-level information, generalizing to rare events, and providing …
comprehending high-level information, generalizing to rare events, and providing …
A survey of large language models for autonomous driving
Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …
mobility, has the tend to transition from rule-based systems to data-driven strategies …
Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving
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 …
endowing them with human-like thinking and cognitive abilities. In this work, we delve into …
Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models
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 …
based driving tasks. However existing research typically focuses on limited tasks and often …