Online latency monitoring of time-sensitive event chains in safety-critical applications
Jonas Peeck, Johannes Schlatow, Rolf Ernst · 2021
Highly-automated driving involves chains of perception, decision, and control functions. These functions involve data-intensive algorithms that motivate the use of a data-centric middleware and a service-oriented architecture. As an example we use the open-source project Autoware.Auto. The function chains define a safety-critical automated control task with weakly-hard real-time constraints. However, providing the required assurance by formal analysis is challenged by the complex hardware/software structure of these systems and their dynamics. We propose an approach that combines measurement, suitable distribution of deadline segments, and application-level online monitoring that serves to supervise the execution of service-oriented software systems with multiple function chains and weakly-hard real-time constraints. We use DDS as middleware and apply it to an Autoware.Auto use case.