Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …

The perception of the surrounding environment is a key requirement for autonomous driving
systems, yet the computation of an accurate semantic representation of the scene starting …

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …

Deep learning-based intelligent vehicle perception has been developing prominently in
recent years to provide a reliable source for motion planning and decision making in …

A reliable perception has to be robust against challenging environmental conditions.
Therefore, recent efforts focused on the use of radar sensors in addition to camera and lidar …

Metaverses have caused significant changes in the industry and their academic foundation
can be traced back to the term cyber–physical–social systems (CPSS), which was proposed …

Autonomous vehicles (AV) are rapidly becoming integrated into everyday life, with several
countries anticipating their inclusion in public transport networks in the coming years. Safety …

Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce
costs in practice low-cost multi-view cameras for 3D object detection are proposed to …

Radar has stronger adaptability in adverse scenarios for autonomous driving environmental
perception compared to widely adopted cameras and LiDARs. Compared with commonly …