The availability of computational power in the domain of Prognostics and Health
Management (PHM) with deep learning (DL) applications has attracted researchers …

Over the last few decades, automotive embedded Information and Communication
Technology (ICT) systems have been used to enhance vehicle performance and enrich …

With increasing customer demand, industry 4.0 gained a lot of interest, which is based on
smart factories. In smart factories, robotic components are vulnerable to failure due to …

Despite the recent advancements that Autonomous Vehicles have shown in their potential to
improve safety and operation, considering differences between Autonomous Vehicles and …

This paper considers the main challenges for all components engaged in the driving task
suggested by the automation of road vehicles or autonomous cars. Numerous autonomous …

Reconstructing large-scale 3D scenes is essential for autonomous vehicles, especially
when partial sensor data is lost. Although the recently developed neural radiance fields …

Driver distraction is one of the significant causes of traffic accidents. To improve the accuracy
of accident occurrence prediction under driver distraction and to provide graded warnings, it …

Autonomous driving technology heavily depends on accurate and smooth path tracking.
Facing complex urban driving scenarios, developing a suite of high-performance and robust …

The rapid influx of data-driven models into the industrial sector has been facilitated by the
proliferation of sensor technology, enabling the collection of vast quantities of data …

Vehicular networks have become a critical component of modern transportation systems by
facilitating communication between vehicles and infrastructure. Nonetheless, the security of …