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Various algorithms such as emergency brake or crash warning using V2X communication have been published recently. For such systems hard real-time constraints have to be satisfied. Therefore latency needs to be minimized to keep the message processing delay below a certain threshold. Existing V2X systems based on the IEEE 1609 and SAE J2735 standards implement most message processing in software. This means the latency of these systems strongly depends on the CPU load as well as the number of incoming messages per time. According to safety constraints all messages of nearby vehicles have to be processed, whereby no prediction of the message importance can be given without analyzing the message content. Regarding the aforementioned requirements we propose a novel architecture that optimizes latency to satisfy the hard real-time constraints for V2X messages.

Due to the continuously increasing complexity of automotive electric/electronic architectures (EEAs), model-based systems engineering principles became state-of-the-art for designing such heterogeneous systems. However, current Architecture Description Languages (ADLs) as well as their system-design and analysis tools and frameworks for simulation-based analysis of EEA models often are not fully integrated in a single design process. They usually require error-prone import/export processes, especially when considering distributed collaboration, from EEA data models to external analysis frameworks and vice versa. Particularly, this limits the efficient assessment and comparison of distinct architecture variants regarding certain non-functional properties. Moreover, simulation-based analysis of the latter intended for EEA assessments in early concept phases demands backtracking capabilities to allow iterative model adaptations.