Machine learning (ML) algorithms are essential components in autonomous driving. In most
existing connected and autonomous vehicles (CAVs), a large amount of driving data …

Federated learning (FL), as a distributed machine learning technology, allows large-scale
nodes to utilize local datasets for model training and sharing without revealing privacy …

Internet of Vehicles (IoVs) is highly characterized by collaborative environment data sensing,
computing and processing. Emerging Big Data and Artificial Intelligence (AI) technologies …

Abstract Internet of Vehicles (IoVs) consists of smart vehicles, Autonomous Vehicles (AVs)
as well as roadside units (RSUs) that communicate wirelessly to provide enhanced …

Autonomous Vehicles (s) take advantage of Machine Learning (ML) for yielding improved
experiences of self-driving. However, large-scale collection of s' data for training will …

The application of artificial intelligence technology in Internet of Vehicles (IoV) has attracted
great research interests with the goal of enabling smart transportation and traffic …

Internet of Vehicles (IoV) has been sought as a solution to realize an Intelligent
Transportation System (ITS) for efficient traffic management. Data driven ITS requires …

While the convergence of Artificial Intelligence (AI) techniques with improved information
technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it …

As an emerging distributed machine learning (ML) method, federated learning (FL) can
protect data privacy through collaborative learning of artificial intelligence (AI) models across …

Blockchain-based Federated Learning (FL) technology enables vehicles to make smart
decisions, improving vehicular services and enhancing the driving experience through a …