Dilu: A knowledge-driven approach to autonomous driving with large language models
Recent advancements in autonomous driving have relied on data-driven approaches, which
are widely adopted but face challenges including dataset bias, overfitting, and …
are widely adopted but face challenges including dataset bias, overfitting, and …
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 …
Towards knowledge-driven autonomous driving
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …
investigation highlights the limitations of current autonomous driving systems, in particular …
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 …
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 …
A language agent for autonomous driving
Human-level driving is an ultimate goal of autonomous driving. Conventional approaches
formulate autonomous driving as a perception-prediction-planning framework, yet their …
formulate autonomous driving as a perception-prediction-planning framework, yet their …
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 …
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" …
Receive, reason, and react: Drive as you say, with large language models in autonomous vehicles
The fusion of human-centric design and artificial intelligence capabilities has opened up
new possibilities for next-generation autonomous vehicles that go beyond traditional …
new possibilities for next-generation autonomous vehicles that go beyond traditional …
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 …