Abstract

Future automotive systems, with Advanced Driving Assistance Systems and Autonomous Driving functionalities, will require fail-operational electronic systems. To achieve that, redundancy is a necessary technique, like in many other fields such as aviation. Moreover the applications have different safety requirements, from safety-critical related applications, for example for the driver replacement domain, to QoS-oriented applications, for example for the infotainment domain. Redundancy in mixed-criticality systems can be solved by physically separating system resources or by using isolated virtualized environments with e.g. hypervisors. There are costs associated to both solutions. In this work we describe a novel model we use to characterize a mixed-criticality automotive system and the analysis steps to obtain quantified metrics. The quantified metrics include cost, failure probability, total functional and communication loads, and total cable length, to compare the different solutions from a system-level perspective. We analyse the same set of mixed-criticality applications that represent a simplified automotive system in four scenarios. The architecture topology is either domain-based or zone-based, and we use either physical separation or virtualization to provide isolation. The obtained results show how the model and the analysis allows us to understand the trade-offs between the different solutions in specific applications scenarios, and how to vary the metrics used in the analysis to adapt to a different applications scenario.

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