In recent years, with the rapid development of deep learning technology, great progress has
been made in computer vision, image recognition, pattern recognition, and speech signal …

Images captured through the glass often consist of undesirable specular reflections. These
reflections detected in front of the glass remarkably reduce the quality and visibility of the …

Autonomous driving has become an important research area for road traffic, whereas testing
of autonomous driving systems to ensure a safe and reliable operation remains an open …

The class of Trustworthy Autonomous Systems (TAS) includes cyber-physical systems
leveraging on self-x technologies that make them capable to learn, adapt to changes, and …

The progressive adoption of artificial intelligence and advanced communication
technologies within railway control and automation has brought up a huge potential in terms …

The objective of this research is to present the state of the art of the safety assurance of
Artificial Intelligence (AI)-based systems and guidelines on future correlated work. For this …

For robust object detection on LiDAR data, neural networks have to be trained on diverse
datasets that contain many different environmental influences like rain, snow, or fog. To this …

Light detection and ranging (LiDAR) technology plays an important role in achieving higher
levels of autonomous driving. These sensors, although robust in clear weather conditions …

This study reviews the research works published in the last five years on Digital Twin (DT)
technology for intelligent transportation systems, focusing on the use of DT in electromobility …

The advancement of automation in safety-critical systems has opened the door to newer
opportunities in several fields. However, the increasing complexity has led to more risks and …