Time-triggered implementations of mixed-criticality automotive software - Embedded.com

Time-triggered implementations of mixed-criticality automotive software


Mixed critical systems such as automotive software consists of a mix of safety-critical control applications with performance and stability constraints and time-critical applications with only deadline constraints. The constraints associated with the control applications (e.g., engine control, brake-by wire, vehicle dynamics control) are crucial for ensuring the safety of the vehicle.

Timing constraints associated with the real-time, e.g., driver-assistance applications) help improve usability and driving comfort. Both classes of applications co-exist, interact and share commonresources like electronic control units (ECUs), and buses.

Scheduling and platform design to ensure such a mix of timing, control performance and stability constraints is a challenging problem, especially for architectures with multiple ECUs and buses with complex protocols like FlexRay .

Real-time applications only have deadline constraints and predefined sampling rates. However, both stability and performance of control applications depend on the choice of sampling periods, which in turn determinethe deadlines imposed by them.

In this work, we consider the problem of implementing such a mix of applications on a time-triggered platform with eCos-based ECUsconnected via FlexRay based buses. We proposed a co-design scheme that finds schedules for both the ECUs and the buses such that all the above-mentioned constraintsare satisfied.

We present an automatic schedule synthesis framework for applications that are mapped onto distributed time triggered automotive platforms where multiple Electronic ControlUnits (ECUs) are synchronized over a FlexRay bus.

We classify applications into two categories (i) safety-critical control applications with stability and performance constraints,and (ii) time-critical applications with only deadline constraints. Ourproposed framework can handle such mixed constraints arising from timing, control stability, and performance requirements. In particular, we synthesize schedules that optimize control performance and respects the timing requirements of the real-time applications.

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