AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning
Connected and autonomous driving is developing rapidly in recent years. However, current
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
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 …
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 …
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 …
[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 …
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 …
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 …
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences
Recent advancements in foundation models (FMs) have unlocked new prospects in
autonomous driving, yet the experimental settings of these studies are preliminary, over …
autonomous driving, yet the experimental settings of these studies are preliminary, over …
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 …
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 …