Data-Centric Middleware support for ASIL assessment and de- composition in open automotive systems

Current automotive electrics and electronics (E/E) architectures are very complex and face the challenge to provide easy integration of additional and even more complex functionality such as automated driving. Furthermore, the end-customer is used to the possibility of easy personalization, adaptivity or extensibility of the electronic systems with new hardware or software. Since this possibility already exists in the infotainment domain, it significantly drives a similar expectation also within the automotive domain. Due to the fact that cars are safetycritical systems, automotive middlewares (MW) must provide framework and methods for safe integration of new hardware or software. This implies whenever a new functionality or component is integrated in the system, violation of different qualitative and quantitative safety requirements needs to be evaluated. This paper presents our recent work on runtime qualitative safety-assessment that considers Automotive Safety Integrity Level (ASIL) compatibility of signals and the possibility of their decomposition in such open automotive systems. We introduce our approach and present a case study where the approach is applied not only during the design of the automotive system but also in Plug&Play scenario, so during refurbishment or via the endcustomer.