When will automated vehicles come onto the market? This question has puzzled the
automotive industry and society for years. The technology and its implementation have …

Symbolic regression (SR) is a machine learning-based regression method based on genetic
programming principles that integrates techniques and processes from heterogeneous …

Nowadays, there are outstanding strides towards a future with autonomous vehicles on our
roads. While the perception of autonomous vehicles performs well under closed-set …

The rapid developments in Artificial Intelligence (AI) and the intensification in the adoption of
AI in domains such as autonomous vehicles, lethal weapon systems, robotics and alike pose …

AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …

Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …

Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …

Scenario-based approaches have been receiving a huge amount of attention in research
and engineering of automated driving systems. Due to the complexity and uncertainty of the …

Deep Neural Networks (DNNs) are the core component of modern autonomous driving
systems. To date, it is still unrealistic that a DNN will generalize correctly to all driving …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …