27 citations · 52 across the 23 of their papers we have counts for
6 papers · 1 filter
Personalized Autonomous Driving with Large Language Models: Field Experiments
Can Cui, Zichong Yang, Yupeng Zhou +6
Integrating large language models (LLMs) in autonomous vehicles enables conversation with AI systems to drive the vehicle. However, it also emphasizes the requirement for such syst…
LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs
Yunsheng Ma, Can Cui, Xu Cao +9
Autonomous driving (AD) has made significant strides in recent years. However, existing frameworks struggle to interpret and execute spontaneous user instructions, such as "overtak…
A Survey on Multimodal Large Language Models for Autonomous Driving
Can Cui, Yunsheng Ma, Xu Cao +18
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 perceive th…
MACP: Efficient Model Adaptation for Cooperative Perception
Yunsheng Ma, Juanwu Lu, Can Cui +4
Vehicle-to-vehicle (V2V) communications have greatly enhanced the perception capabilities of connected and automated vehicles (CAVs) by enabling information sharing to "see through…
Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles
Can Cui, Yunsheng Ma, Xu Cao +2
The fusion of human-centric design and artificial intelligence (AI) capabilities has opened up new possibilities for next-generation autonomous vehicles that go beyond transportati…
Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles
Can Cui, Yunsheng Ma, Xu Cao +2
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 passengers…