Automotive perception involves understanding the external driving environment and the
internal state of the vehicle cabin and occupants using sensor data. It is critical to achieving …

Perception systems play a crucial role in autonomous driving by reading the sensory data
and providing meaningful interpretation of the operating environment for decision-making …

As the complexity of autonomous vehicles (AVs) continues to increase and artificial
intelligence algorithms are becoming increasingly ubiquitous, a novel safety concern known …

Vehicle-to-everything (V2X) communication is seen as one of the main enabling
technologies for automated vehicles. Collective perception is especially promising, as it …

To enable safe autonomous vehicle (AV) operations, it is critical that an AV's obstacle
detection module can reliably detect obstacles that pose a safety threat (ie, are safety …

For robust object detection on LiDAR data, neural networks have to be trained on diverse
datasets that contain many different environmental influences like rain, snow, or fog. To this …

The article presents a review of recent literature on the performance metrics of Automated
Driving Systems (ADS). More specifically, performance indicators of environment perception …

Whenever a visual perception system is employed in safety-critical applications such as
automated driving, a thorough, task-oriented experimental evaluation is necessary to …

The latest generation of safety standards applicable to automated driving systems require
both qualitative and quantitative safety acceptance criteria to be defined and argued. At the …

Due to poor local range of the perception and object recognition mechanisms used by
autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully …