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 …

Foundation models are used to train a broad system of general data to build adaptations to
new bottlenecks. Typically, they contain hundreds of billions of hyperparameters that have …

Development and safety validation of highly automated vehicles increasingly relies on data
and data-driven methods. In processing sensor datasets for environment perception, it is …

Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the
safety and reliability of these systems, extensive testings are being conducted before their …

Realizing human-like perception is a challenge in open driving scenarios due to corner
cases and visual occlusions. To gather knowledge of rare and occluded instances …

The integration of intelligent transportation systems (ITS) in urban infrastructure has
increased significantly, and one of the most notable examples is the development of …

Autonomous vehicles must operate safely in their dynamic and continuously-changing
environment. However, the operating environment of an autonomous vehicle is complicated …

This paper aims to contribute to the comprehensive and systematic safety assessment of
Automated Driving Systems (ADSs) by identifying unknown hazardous areas of operation …

Though automated vehicles (AVs) are believed to play a crucial role in future transport,
human driving vehicles will share the road with automated vehicles for a relatively long …

Virtual simulation‐based testing of autonomous vehicles (AVs) needs massive challenging
corner cases to reach high testing accuracy. Current methods achieve this goal by finding …