In the Systems Engineering (SE) domain there has been a paradigm shift from document-
based to model-based system development artefacts; in fact, new methodologies are …

In modern vehicles, system complexity and technical capabilities are constantly growing. As
a result, manufacturers and regulators are both increasingly challenged to ensure the …

Software metrics such as coverage or mutation scores have been investigated for the
automated quality assessment of test suites. While traditional tools rely on software metrics …

Previous literature on policy diversity in reinforcement learning (RL) either focuses on the
online setting or ignores the policy performance. In contrast, offline RL, which aims to learn …

This technical report presents research results achieved in the field of verification of trained
Convolutional Neural Network (CNN) used for image classification in safety-critical …

Robotics systems are complex, safety-critical systems that can consist of hundreds of
software components that interact with each other dynamically during run time. Software …

We propose a quantitative risk assessment approach for the design of an obstacle detection
function for low-speed freight trains with grade of automation 4. In this five-step approach …

Numerous fields, such as the military, agriculture, energy, welding, and automation of
surveillance, have benefited greatly from autonomous robots' contributions. Since mobile …

Unmanned robotics and autonomous systems (URAS) are integral components of
contemporary Cyber-Physical Systems (CPS), allowing vast applications across many …

Simulation is a vital method to test autonomous vehicle software. It provides a low-cost and
convenient virtual environment to verify the control program of autonomous vehicles …