With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

In the last few years, due to the continuous advancement of technology, human behavior
detection and recognition have become important scientific research in the field of computer …

Nowadays, there are outstanding strides towards a future with autonomous vehicles on our
roads. While the perception of autonomous vehicles performs well under closed-set …

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Contemporary deep-learning object detection methods for autonomous driving usually
presume fixed categories of common traffic participants, such as pedestrians and cars. Most …

Bird's-Eye View (BEV) Perception has received increasing attention in recent years as it
provides a concise and unified spatial representation across views and benefits a diverse …

The core obstacle towards a large-scale deployment of autonomous vehicles currently lies
in the long tail of rare events. These are extremely challenging since they do not occur often …

Systems and functions that rely on machine learning (ML) are the basis of highly automated
driving. An essential task of such ML models is to reliably detect and interpret unusual, new …

Autonomous driving perception has made significant strides in recent years, but accurately
sensing the environment using a single sensor remains a daunting task. This review offers a …

In safety-critical applications such as automated driving, perception errors may create an
imminent risk to vulnerable road users (VRU). To mitigate the occurrence of unexpected and …