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 …

The increasing complexity of Advanced Driver Assistance Systems (ADAS) presents a
challenging task to validate safe and reliable performance of these systems under varied …

Perception sensor modeling is essential for the safety validation of automated driving
systems in virtual environments. Nevertheless, the community lacks a methodical approach …

Perception is a safety-critical function of autonomous vehicles and machine learning (ML)
plays a key role in its implementation. This position paper identifies (1) perceptual …

This article proposes a framework for evaluating and modeling perception systems,
motivated by the need to develop testing scenarios for verification and validation of …

Complete perception of the environment and its correct interpretation is crucial for
autonomous vehicles. Object perception is the main component of automotive surround …

Safety assurance of automated driving systems must consider uncertain environment
perception. This paper reviews literature addressing how perception testing is realized as …

Automated driving requires reliable perception of the environment to ensure the safety of the
driving task. One common perception task is 3D object detection, which aims at perceiving …

Recent advances in the field of deep learning and impressive performance of deep neural
networks (DNNs) for perception have resulted in an increased demand for their use in …

Self-evaluation and monitoring are critical components in autonomous driving applications,
especially for safety purposes, and yet there is no systematic framework to estimate the …