Mirko Conrad, Frank Langner, Benjamin Axmann, Karlheinz Blankenbach, Jan Bauer, Matthäus Vogelmann, Manfred Wittmeir, Sascha Xu
In Press, Uncorrected Proof, Available Online: 22 February 2021
As of today, automotive video data transmission and processing systems are already being developed according to ISO 26262, but safety mechanisms and safety architectures for such systems are individually derived on a case-by-case basis. This approach, i.e., reinventing the wheel, over and over again,...
In Press, Corrected Proof, Available Online: 16 February 2021
Analyzing runtime behavior as part of debugging complex component-based systems used in the vehicle industry is an important aspect of the integration process. It is a laborious task that involves many manual steps. One reason for this is that, as of today, the analysis is usually not performed on the...
Alessio Di Sandro, Sahar Kokaly, Rick Salay, Marsha Chechik
Volume 1, Issue 1, 2020, Pages 34-50
The automotive domain has recently increased its reliance on model-based software development. Automotive models are often heterogeneous, large and interconnected through traceability links. When introducing safety-related artifacts, such as Hazard Analysis, fault tree analysis (FTA), failure modes and...
Betty H. C. Cheng, Bradley Doherty, Nicholas Polanco, Matthew Pasco
Volume 1, Issue 1, 2020, Pages 51-77
As automotive systems become increasingly sophisticated with numerous onboard features that support extensive inward and outward-facing communication, cybersecurity vulnerabilities are exposed. The relatively recent acknowledgement of automotive cybersecurity challenges has prompted numerous research...
The development of self-driving vehicles is often regarded as adding a layer of intelligence on top of classic vehicle platforms. However, the amount of software needed to reach autonomy will exceed the software deployed for operation of normal vehicles. As complexity increases, the demand for proper...
Markus Borg, Cristofer Englund, Krzysztof Wnuk, Boris Duran, Christoffer Levandowski, Shenjian Gao, Yanwen Tan, Henrik Kaijser, Henrik Lönn, Jonas Törnqvist
Volume 1, Issue 1, 2020, Pages 1-19
Deep neural networks (DNNs) will emerge as a cornerstone in automotive software engineering. However, developing systems with DNNs introduces novel challenges for safety assessments. This paper reviews the state-of-the-art in verification and validation of safety-critical systems that rely on machine...