Assurance Benefits of ISO 26262 compliant Microcontrollers for safety-critical Avionics

The usage of complex Microcontroller Units (MCUs) in avionic systems constitutes a challenge in assuring their safety. They are not developed according to the development requirements accepted by the aerospace industry. These Commercial off-the-shelf (COTS) hardware components usually target other domains like the telecommunication branch. In the last years MCUs developed in compliance to the ISO 26262 have been released on the market for safety-related automotive applications. The avionic assurance process could profit from these safety MCUs. In this paper we present evaluation results based on the current assurance practice that demonstrates expected assurance activities benefit from ISO 26262 compliant MCUs.Comment: Submitted to SafeComp 2018: http://www.es.mdh.se/safecomp2018

Supporting ISO 26262 with SysML, Benefits and Limits

International audienceThis article deals with the issue of deploying efficiently the ISO 26262: the new standard in automotive systems development. The directives enclosed in this norm demands the establishment of a product lifecycle fully integrating the safety assessment activities. To tackle this subject, this paper explores the way of setting up Model-Based Design methodology to express and organize the concepts manipulated during the ISO 26262 process. This attempt is founded on the use of SysML and on the creation of a profile dedicated to ISO 26262 development context. We provide an introduction to Model-Based Design paradigm and its appli-cation in a safety relevant context. An overview of ISO 26262 is given, followed by the description of an on-going project on the subject. Modeling propositions are formulated and the use of diverse SysML diagrams are mapped on the automotive safety lifecycle process

Automotive safety and machine learning: Initial results from a study on how to adapt the ISO 26262 safety standard

Machine learning (ML) applications generate a continuous stream of success stories from various domains. ML enables many novel applications, also in safety-critical contexts. However, the functional safety standards such as ISO 26262 did not evolve to cover ML. We conduct an exploratory study on which parts of ISO 26262 represent the most critical gaps between safety engineering and ML development. While this paper only reports the first steps toward a larger research endeavor, we report three adaptations that are critically needed to allow ISO 26262 compliant engineering, and related suggestions on how to evolve the standard

Overview of the Second Edition of ISO 26262: Functional Safety— Road Vehicles

Functional safety is of the utmost importance in the development of safety-critical automotive systems, especially with the introduction of driver assist and automated driving systems. ISO 26262: Functional Safety – Road Vehicles, has been the de facto standard for functional safety in the automotive electronics domain since the release of its first edition in 2011. It is currently available in its second edition, published in December 2018. In this paper, we present an overview of the standard, which applies to all activities during the safety lifecycle of system development. In the concept phase of ISO 26262, the hazard and risk assessment process focuses on identifying possible hazards caused by malfunctioning behavior of electrical/electronic (E/E) safety-related systems and mitigating them through the identification of safety goals. The design phase includes system, hardware, and software development, with requirements developed from the safety goals. ISO 26262 also prescribes the functional safety management activities to be performed during the safety lifecycle and provides requirements for the supporting processes. In addition to presenting an overview of the standard, this paper highlights some major changes introduced in the second edition of ISO 26262

Safety-related challenges and opportunities for GPUs in the automotive domain

GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.Authors would like to thank Guillem Bernat from Rapita Systems for his technical feedback on this work. The research leading to this work has received funding from the European Re-search Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773). This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernández is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN.Peer ReviewedPostprint (author's final draft