Towards Enabling Level 3A AI in Avionic Platforms

Abstract

The role of AI evolves from human assistance over human/machine collaboration towards fully autonomous systems. As the push towards more autonomy subsequently removes the reliance on a human overseeing the system, means of self supervision must be provided to enable safe operations. This work explores dynamic reconfiguration to provide resilience to unforeseen environmental conditions that exceed the systems capabilities, but also against normal faults. We focus on providing the means for this in an ARINC 653 compliant environment, since we target avionics platforms. Scheduling and communication are two major aspects of dynamic reconfiguration. Hence, we discuss multiple respective implementation approaches. The third pillar of reconfiguration, the process of deciding when to reconfigure is also investigated. Combining these yields the building blocks for a self-supervising system.