With recent efforts to make vehicles intelligent, solutions based on machine learning have
been accepted to the ecosystem. These systems in the automotive domain are growing fast …

Perception is a safety-critical function of autonomous vehicles and machine learning (ML)
plays a key role in its implementation. This position paper identifies (1) perceptual …

This open access book brings together the latest developments from industry and research
on automated driving and artificial intelligence. Environment perception for highly automated …

Machine learning (ML) plays an ever-increasing role in advanced automotive functionality
for driver assistance and autonomous operation; however, its adequacy from the perspective …

Enabled by recent advances in the field of machine learning, the automotive industry pushes
towards automated driving. The development of traditional safety-critical automotive …

Machine learning (ML) applications generate a continuous stream of success stories from
various domains. ML enables many novel applications, also in safety-critical contexts …

Methods for safety assurance suggested by the ISO 26262 automotive functional safety
standard are not sufficient for applications based on machine learning (ML). We provide a …

A rise in popularity of Deep Neural Networks (DNNs), attributed to more powerful GPUs and
widely available datasets, has seen them being increasingly used within safety-critical …

This paper describes the challenges involved in arguing the safety of highly automated
driving functions which make use of machine learning techniques. An assurance case …

Autonomous vehicles are considered to be the next big thing. Several companies are racing
to put self-driving vehicles on the road by 2020. Regulations and standards are not ready for …