As vehicle complexity and road congestion increase, combined with the emergence of
electric vehicles, the need for intelligent transportation systems to improve on-road safety …

Autonomous driving solutions stretch over different disciplines and technologies eg,
sensors, communication, computation, machine learning, data analytic, etc., that need to be …

The last two decades have seen a clear trend toward crafting intelligent vehicles based on
the significant advances in communication and computing paradigms, which provide a safer …

Federated learning (FL) is a promising decentralized deep learning technology, which
allows users to update models cooperatively without sharing their data. FL is reshaping …

Federated learning (FL) has received a great deal of research attention in the context of
privacy protection restrictions. By jointly training deep learning models, a variety of training …

For vehicle-to-network communications, handover (HO) management enables vehicles to
maintain the connection with the network while transiting through coverage areas of different …

Federated learning holds great promise in learning from fragmented sensitive data and has
revolutionized how machine learning models are trained. This article provides a systematic …

Federated Learning is gaining significant prominence in the Telecommunication Industry as
Communication Service Providers (CSPs) look at harnessing their data assets, while …

The data analysis in the process of vehicle collaboration for the Internet of Vehicles (IoV)
environment improves the driving experience and service quality. However, the privacy …

Federated learning (FL) is a promising framework for distributed machine learning that trains
models without sharing local data while protecting privacy. FL exploits the concept of …