9 citations · 23 across the 16 of their papers we have counts for
16 papers
STAMP: Scalable Task And Model-agnostic Collaborative Perception
Xiangbo Gao, Runsheng Xu, Jiachen Li +3
Perception is crucial for autonomous driving, but single-agent perception is often constrained by sensors' physical limitations, leading to degraded performance under severe occlus…
Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
Juanwu Lu, Can Cui, Yunsheng Ma +2
Safety and robustness are crucial factors in developing trustworthy autonomous vehicles. One essential aspect of addressing these factors is to equip vehicles with the capability t…
A Review of Full-Sized Autonomous Racing Vehicle Sensor Architecture
Manuel Mar, Vishnu Chellapandi, Liangqi Yuan +2
In the landscape of technological innovation, autonomous racing is a dynamic and challenging domain that not only pushes the limits of technology, but also plays a crucial role in…
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…
Digital Ethics in Federated Learning
Liangqi Yuan, Ziran Wang, Christopher G. Brinton
The Internet of Things (IoT) consistently generates vast amounts of data, sparking increasing concern over the protection of data privacy and the limitation of data misuse. Federat…
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…