Large language models (LLMs) have exploded a new heatwave of AI for their ability to
engage end-users in human-level conversations with detailed and articulate answers across …

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

Autonomous vehicles (AVs) have promised to drastically improve the convenience of driving
by releasing the burden of drivers and reducing traffic accidents with more precise control …

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 …

Due to the impressive performance of deep neural networks (DNNs) for visual perception,
there is an increased demand for their use in automated systems. However, to use deep …

This paper investigates runtime monitoring of perception systems. Perception is a critical
component of high-integrity applications of robotics and autonomous systems, such as self …

Safety and performance are key enablers for autonomous driving: on the one hand we want
our autonomous vehicles (AVs) to be safe, while at the same time their performance (eg …

Perception is a critical component of high-integrity applications of robotics and autonomous
systems, such as self-driving vehicles. In these applications, failure of perception systems …

Formal methods and machine learning are two research fields with drastically different
foundations and philosophies. Formal methods utilise mathematically rigorous techniques …

Recently, many applications have begun to employ deep neural networks (DNN), such as
image recognition and safety-critical applications, for more accurate results. One of the most …