Connected and Automated Vehicles (CAVs) represent a rapidly growing technology in the automotive domain sector, offering promising solutions to address challenges such as traffic …
A Taik, Z Mlika, S Cherkaoui - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Federated Learning (FL) is expected to play a prominent role for privacy-preserving machine learning (ML) in autonomous vehicles. FL involves the collaborative training of a single ML …
Federated Learning (FL) is a promising technique to enhance the safety and efficiency of intelligent transportation systems. While FL has been extensively studied, the …
B Li, Y Jiang, Q Pei, T Li, L Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent studies have demonstrated the potentials of federated learning (FL) in achieving cooperative and privacy-preserving data analytics. It would also be promising if FL can be …
H Zhou, Y Zheng, H Huang, J Shu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The rapid growth of the Internet of Vehicles (IoV) paradigm sparks the generation of large volumes of distributed data at vehicles, which can be harnessed to build models for …
SS Shinde, D Tarchi - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Supported by some of the major revolutionary technologies, such as Internet of Vehicles (IoVs), Edge Computing, and Machine Learning (ML), the traditional Vehicular Networks …
Advancements in Vehicular ad-hoc Network (VANET) technology have led to a growing network of interconnected devices, including edge devices, resulting in substantial data …
Machine learning (ML) has recently been adopted in vehicular networks for applications such as autonomous driving, road safety prediction and vehicular object detection, due to its …
In the current era of the Internet of Vehicles (IoV), vehicle to vehicle data sharing can provide customized applications for Connected and Autonomous Vehicles (CAVs). The …