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 …

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

Most intelligent transportation systems use a combination of radar sensors and cameras for
robust vehicle perception. The calibration of these heterogeneous sensor types in an …

Reliable operation in inclement weather is essential to the deployment of safe autonomous
vehicles (AVs). Robustness and reliability can be achieved by fusing data from the standard …

Radar is among the most popular sensors in modern Intelligent Transportation Systems
(ITSs), enabling weather-robust perception. The orientation and position of the traffic radar …

Camera-radar fusion has been applied in obstacle detection or moving object tracking for
autonomous vehicles and advanced driver assistance systems. When utilizing multiple …

Autonomous vehicles (AVs) fuse data from multiple sensors and sensing modalities to
impart a measure of robustness when operating in adverse conditions. Radars and cameras …

While much effort has been devoted to deep learning object detection, relatively limited
attention has been paid to object detection in bad weather, eg rain, snow or haze. In heavy …

Integrated sensing and communications (ISAC) has been deemed as a key technology for
the sixth generation (6G) wireless communications systems. In this paper, we explore the …

The fusion of sensors is a task to improve the recognition performance of obstacles in an
autonomous vehicle system. For the fusion of sensors, extrinsic parameter calibration with 6 …