In this work, we introduce a novel approach to model the rain and fog effect on the light
detection and ranging (LiDAR) sensor performance for the simulation-based testing of …

Autonomous driving on water surfaces plays an essential role in executing hazardous and
time-consuming missions, such as maritime surveillance, survivor rescue, environmental …

In the context of autonomous driving environment perception, multi-modal fusion plays a
pivotal role in enhancing robustness, completeness, and accuracy, thereby extending the …

In recent years, the development of Advanced Driver-Assistance Systems (ADASs) is driving
the need for more reliable and precise on-vehicle sensing. Radar and lidar are crucial in this …

Human activity recognition plays a crucial role in Advanced Driver-Assisted Systems
(ADAS). A significant challenge in achieving automotive autonomy lies in the difficulty faced …

This paper provides an in-depth review of deep learning techniques to address the
challenges of odometry and global ego-localization using frequency modulated continuous …

In the field of autonomous driving, highly accurate representations of the environment are
essential for trajectory planning as well as for estimating the vehicle's location. Today, this …

Measurement performance evaluation of real and virtual automotive light detection and
ranging (LiDAR) sensors is an active area of research. However, no commonly accepted …

Automotive radars operating in dense urban environments experience a multipath
propagation phenomenon, degrading radar performance, and challenging conventional …

Monocular visual odometry (VO) has extensive applications in mobile robots and computer
vision. However, current applications of monocular VO systems in complex environments …