Two experiments were carried out to clarify the characteristics of manual driving when the task of vehicle control is transferred from an autonomous driving system at SAE levels 3 and 5 to manual driv....
Automated driving is currently one of the most active areas of research worldwide. While the general progress in developing specific algorithms for perception, planning and control tasks is very advan....
The foundation of both advanced driving assistance system(ADAS) and automated driving (AD) is an accurate environment perception system(EPS). However, evaluation and test method of EPS are seldom stud....
We present an approach in which an open-source software infrastructure is used for testing the behavior of autonomous vehicles through computer simulation. This software infrastructure is called CAVE,....
This work presents current methods to analyze and improve the architecture of Simulink models. The methods follow the “principles for architectural design” of part 6 on software development of the ISO....
ISO 26262 describes a safety engineering approach in which the safety of a system is considered from the early stages of design through a process of elicitation and allocation of system safety require....
Machine learning (ML) plays an ever-increasing role in advanced automotive functionality for driver assistance and autonomous operation; however, its adequacy from the perspective of safety certificat....
In early design activities (typically before the hardware is built), a reliability prediction is often required for the electronic components and systems in order to assess their future reliability an....
FTA (Fault Tree Analysis) is one of prominent safety analysis techniques in the automotive industry partly because of its graphical representation and partly because of cut-set analysis. Especially be....
In recent automotive systems, more and more applications are classified as safety related and hence are assigned an automotive safety integrity level (ASIL) according to ISO26262. Especially in the co....
Validating the safety of Highly Automated Vehicles (HAVs) is a significant autonomy challenge. HAV safety validation strategies based solely on brute force on-road testing campaigns are unlikely to be....
Increasing automation in the automotive systems has re-focused the industry’s attention on verification and validation methods and especially on the development of test scenarios. The complex nature o....
In recent years the automotive companies are developing their self-driving technology very rapidly. Most of them want to launch their self-driving vehicles with SAE level 4 at the beginning of 2020. T....
Lane departure prevention systems are able to detect imminent departure from the road, allowing the driver to apply control to prevent lane departure. These systems possess enormous potential to reduc....
The automotive world is getting ready to embrace the automated driving (AD). It is necessary to guarantee system safety of the AD application, which includes both “classic” functional safety according....
One of the major challenges for the automotive industry will be the release and validation of cooperative and automated vehicles. The immense driving distance that needs to be covered for a convention....
