Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

Platooning technologies enable trucks to drive cooperatively and automatically, providing
benefits including less fuel consumption, greater road capacity, and safety. To establish trust …

The development of Intelligent Transportation System (ITS) has brought about
comprehensive urban traffic information that not only provides convenience to urban …

Since its debut in 2016, Federated Learning (FL) has been tied to the inner workings of
Deep Neural Networks (DNNs); this allowed its development as DNNs proliferated but …

Federated Learning (FL) is a privacy-preserving machine learning (ML) technology that
enables collaborative training and learning of a global ML model based on aggregating …

Traffic flow prediction (TFP) plays a key role in optimizing intelligent transportation systems
and reducing congestion in smart cities. However, current centralized TFP systems suffer …

Federated Learning represents among the most important techniques used in recent years.
It enables the training of Machine Learning-related models without sharing sensitive data …

Managing urban traffic dynamics is critical in Intelligent Transportation Systems (ITS), where
short-term traffic prediction is vital for effective congestion management and vehicle routing …

In the realm of machine learning (ML) systems featuring client-host connections, the
enhancement of privacy security can be effectively achieved through federated learning (FL) …

Federated learning is an enabling technology for the services in Internet of vehicles because
it can effectively alleviate privacy issues in data circulation and diversified intelligent …