In this study, a new control approach is introduced for active/reactive power control in
modernized microgrids (MMGs). The dynamics of MMG are considered to be unknown and a …

In order to navigate through complex traffic scenarios safely and efficiently, the autonomous
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …

Road accidents are on the rise worldwide, causing 1.35 million deaths per year, thus
encouraging the search for solutions. The promising proposal of autonomous vehicles …

Driving behavior primitives play a crucial role in semantic explanation of driving behaviors.
Although much work has been done on exacting driving behavior primitives from naturalistic …

Multivariate Time Series (MTS) data capture temporal behaviors to provide invaluable
insights into various physical dynamic phenomena. In smart mobility, MTS plays a crucial …

The increasing demand for real-time time series classification, especially in high-stakes
industries, underscores the need for predictive explanations and energy-efficient …

Driver's behavior is expressed by the intentional and unintentional actions the driver
performs while driving a motor vehicle. This behavior could be influenced by several factors …

With increasing adoption of digital technologies to automotive industry, the revo-lution of the
vehicles opens new doors for many advanced applications to improve the driver safety and …

Driver behavior has recently emerged as a challenging topic in Traffic risk studies. Despite
the advances in this topic, the challenges still remain. In fact, the current contribution deals …

With the popularization of the smart city and the explosion of vehicles, the emergence of
large amounts of data has boosted research. Distributed machine learning (DML) is an …