High quality perception is essential for autonomous driving (AD) systems. To reach the
accuracy and robustness thatare required by such systems, several types of sensors must …

Understanding the scene around the ego-vehicle is key to assisted and autonomous driving.
Nowadays, this is mostly conducted using cameras and laser scanners, despite their …

Datasets for autonomous cars are essential for the development and benchmarking of
perception systems. However, most existing datasets are captured with camera and LiDAR …

Scene understanding for automated driving requires accurate detection and classification of
objects and other traffic participants. Automotive radar has shown great potential as a sensor …

Radar has long been a common sensor on autonomous vehicles for obstacle ranging and
speed estimation. However, as a robust sensor to all-weather conditions, radar's capability …

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

Autonomous radar has been an integral part of advanced driver assistance systems due to
its robustness to adverse weather and various lighting conditions. Conventional automotive …

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 …

Due to the small number of raw data automotive radar datasets and the low resolution of
such radar sensors, automotive radar object detection has been little explored with deep …

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 …