Search papers, labs, and topics across Lattice.
This paper analyzes the impact of Safety Integrity Level (SIL) constraints, AUTOSAR basic software (BSW), and memory requirements on task allocation within a real-world automotive ECU application. It highlights how improper task sharing across different SILs can compromise critical functions. The study uses the Driverator configuration framework to characterize the application and analyze the interplay between SIL, BSW, and memory.
Mixing tasks with different safety levels in automotive ECUs can compromise critical functions, highlighting the need for careful task allocation strategies.
Automotive electronic control units (ECUs) are intricate systems with hundreds of individual functions, numerous software components, and multiple interdependent tasks. A prevalent structural pattern in these systems are so-called cause-effect chains. While significant research efforts have been dedicated to the temporal analysis and optimization of these chains, particularly minimizing data age and function response times, other crucial non-functional properties remain relatively underexplored. In particular, the safety integrity level (SIL) classification substantially influences the system design by determining task colocation strategies. Improper sharing of functions or interweaving tasks with different safety levels can compromise the integrity of critical functions. Additionally, AUTOSAR basic software (BSW) (e.g. OS, runtime environment, communication stacks, or diagnostics) introduces complexity that varies based on task characteristics and SIL categories. Furthermore, memory requirements present another critical challenge, given the diversity of memory architectures and SIL-specific dependencies that strongly constrain task allocations. This paper thoroughly characterizes a real-world automotive application, describing an automotive application based on SIL constraints, the impact of basic software, and memory requirements. In this context, the Driverator configuration framework is introduced for scalable system analysis.
