41 citations · 77 across the 41 of their papers we have counts for
19 papers · 1 filter
CP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perception
Senkang Hu, Yihang Tao, Guowen Xu +4
Collaborative Perception (CP) has shown a promising technique for autonomous driving, where multiple connected and autonomous vehicles (CAVs) share their perception information to…
IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers
Zihan Fang, Zheng Lin, Senkang Hu +4
Recently, in-car monitoring has emerged as a promising technology for detecting early-stage abnormal status of the driver and providing timely alerts to prevent traffic accidents.…
Channel-Aware Throughput Maximization for Cooperative Data Fusion in CAV
Haonan An, Zhengru Fang, Yuang Zhang +4
Connected and autonomous vehicles (CAVs) have garnered significant attention due to their extended perception range and enhanced sensing coverage. To address challenges such as bli…
R-ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications
Zhengru Fang, Jingjing Wang, Yanan Ma +4
Collaborative perception enhances sensing in multirobot and vehicular networks by fusing information from multiple agents, improving perception accuracy and sensing range. However,…
Resources on the Move for Smart City: A Disruptive Perspective on the Grand Convergence of Sensing, Communications, Computing, Storage, and Intelligence
Yuguang Fang, Yiqin Deng, Xianhao Chen
The most commonly seen things on streets in any city are vehicles. However, most of them are used to transport people or goods. What if they also carry resources and capabilities f…
Secure Traffic Sign Recognition: An Attention-Enabled Universal Image Inpainting Mechanism against Light Patch Attacks
Hangcheng Cao, Longzhi Yuan, Guowen Xu +3
Traffic sign recognition systems play a crucial role in assisting drivers to make informed decisions while driving. However, due to the heavy reliance on deep learning technologies…
The Fluorescent Veil: A Stealthy and Effective Physical Adversarial Patch Against Traffic Sign Recognition
Shuai Yuan, Xingshuo Han, Hongwei Li +5
Recently, traffic sign recognition (TSR) systems have become a prominent target for physical adversarial attacks. These attacks typically rely on conspicuous stickers and projectio…
Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention
Yihang Tao, Senkang Hu, Zhengru Fang +1
Collaborative perception (CP) leverages visual data from connected and autonomous vehicles (CAV) to enhance an ego vehicle's field of view (FoV). Despite recent progress, current C…
Prioritized Information Bottleneck Theoretic Framework with Distributed Online Learning for Edge Video Analytics
Zhengru Fang, Senkang Hu, Jingjing Wang +3
Collaborative perception systems leverage multiple edge devices, such surveillance cameras or autonomous cars, to enhance sensing quality and eliminate blind spots. Despite their a…
PIB: Prioritized Information Bottleneck Framework for Collaborative Edge Video Analytics
Zhengru Fang, Senkang Hu, Liyan Yang +3
Collaborative edge sensing systems, particularly in collaborative perception systems in autonomous driving, can significantly enhance tracking accuracy and reduce blind spots with…
AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging
Senkang Hu, Zhengru Fang, Zihan Fang +4
Ramp merging is one of the bottlenecks in traffic systems, which commonly cause traffic congestion, accidents, and severe carbon emissions. In order to address this essential issue…
Multi-hop Multi-RIS Wireless Communication Systems: Multi-reflection Path Scheduling and Beamforming
Xiaoyan Ma, Haixia Zhang, Xianhao Chen +1
Reconfigurable intelligent surface (RIS) provides a promising way to proactively augment propagation environments for better transmission performance in wireless communications. Ex…
Security Analysis of WiFi-based Sensing Systems: Threats from Perturbation Attacks
Hangcheng Cao, Wenbin Huang, Guowen Xu +5
Deep learning technologies are pivotal in enhancing the performance of WiFi-based wireless sensing systems. However, they are inherently vulnerable to adversarial perturbation atta…
AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning
Senkang Hu, Zhengru Fang, Zihan Fang +3
Connected and autonomous driving is developing rapidly in recent years. However, current autonomous driving systems, which are primarily based on data-driven approaches, exhibit de…
PACP: Priority-Aware Collaborative Perception for Connected and Autonomous Vehicles
Zhengru Fang, Senkang Hu, Haonan An +5
Surrounding perceptions are quintessential for safe driving for connected and autonomous vehicles (CAVs), where the Bird's Eye View has been employed to accurately capture spatial…
Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models
Zihan Fang, Zheng Lin, Zhe Chen +3
Recently, there has been a surge in the development of advanced intelligent generative content (AIGC), especially large language models (LLMs). However, for many downstream tasks,…
SmartCooper: Vehicular Collaborative Perception with Adaptive Fusion and Judger Mechanism
Yuang Zhang, Haonan An, Zhengru Fang +4
In recent years, autonomous driving has garnered significant attention due to its potential for improving road safety through collaborative perception among connected and autonomou…
ESFL: Efficient Split Federated Learning over Resource-Constrained Heterogeneous Wireless Devices
Guangyu Zhu, Yiqin Deng, Xianhao Chen +3
Federated learning (FL) allows multiple parties (distributed devices) to train a machine learning model without sharing raw data. How to effectively and efficiently utilize the res…
Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities
Senkang Hu, Zhengru Fang, Yiqin Deng +2
Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current aut…