Journal of Automotive Software Engineering
Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry
Markus Borg, Cristofer Englund, Krzysztof Wnuk, Boris Duran, Christoffer Levandowski, Shenjian Gao, Yanwen Tan, Henrik Kaijser, Henrik Lönn, Jonas Törnqvist
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...
Using Architectural Runtime Verification for Offline Data Analysis
Lars Stockmann, Sven Laux, Eric Bodden
Pages: 1 - 14
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...
Improving Functional Safety of Automotive Video Data Transmission and Processing Systems
Mirko Conrad, Frank Langner, Benjamin Axmann, Karlheinz Blankenbach, Jan Bauer, Matthäus Vogelmann, Manfred Wittmeir, Sascha Xu
Pages: 15 - 26
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,...
A Standard Driven Software Architecture for Fully Autonomous Vehicles
Alex Serban, Erik Poll, Joost Visser
Pages: 20 - 33
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...
Multi-Level Message Sequence Charts to Validate the Collaborative Automotive Cyber-Physical Systems
Marian Daun, Bastian Tenbergen, Jennifer Brings, Patricia Aluko Obe
Pages: 27 - 45
Autonomous driving and e-mobility are swiftly becoming not only the work of science fiction or popular science, but a reality. A key focus of manufacturers and suppliers in the automotive domain is of course to specify systems that implement this reality. Often, scenarios at type-level are used throughout...
Querying Automotive System Models and Safety Artifacts: Tool Support and Case Study
Alessio Di Sandro, Sahar Kokaly, Rick Salay, Marsha Chechik
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...
Security Patterns for Connected and Automated Automotive Systems†
Betty H. C. Cheng, Bradley Doherty, Nicholas Polanco, Matthew Pasco
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...