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 …

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

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

Predicting traffic flow is vital for optimizing intelligent transportation systems (ITS) and
reducing congestion by forecasting traffic patterns accurately. However, current centralized …

In the field of vehicular communication, the Internet of Vehicles (IoV) serves as a new era
that guarantees increased connectivity, efficiency, and safety. The modern area and new …

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 …

Truck platooning uses networking technology and automated driving support systems to join
multiple trucks in a group. When these vehicles interact for particular journey stages, such as …

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 involves training statistical models over edge devices such as mobile
phones such that the training data are kept local. Federated Learning (FL) can serve as an …

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 …