Automated driving is a promising tool for reducing traffic accidents. While some companies
claim that many cutting-edge automated driving functions have been developed, how to …

Variational quantum machine learning is an extensively studied application of near-term
quantum computers. The success of variational quantum learning models crucially depends …

The advancement of autonomous driving technology has had a significant impact on both
transportation networks and people's lives. Connected and automated vehicles as well as …

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

There is consensus across the automotive industry that Automated Driving Systems and
automated vehicles challenge the way how quality assurance and, particularly, testing must …

Ensuring the quality of automated driving systems is a major challenge the automotive
industry faces. In this context, quality defines the degree to which an object meets …

To successfully launch automated vehicles into the consumer market, there must be credible
proof that the vehicles will operate safely. However, finding a method to validate the …

Although traffic accidents are expected to decrease with the development of autonomous
vehicles, safety and reliability issues are emerging as traffic accidents with autonomous …

Scenario-based testing is envisioned as a key approach for the safety assurance of
autonomous vehicles. In scenario-based testing, relevant (driving) scenarios are the basis of …

Autonomous driving holds great potential for reducing traffic accidents. Despite many
advancements in autonomous vehicle functions, challenges persist in assessing their safety …