A Runtime Safety Monitoring Approach for Adaptable Autonomous Systems

Abstract

Adaptable Autonomous Systems are advanced autonomous systems which not only interact with their environment, but are aware of it and are capable of adapting their behavior and structure accordingly. Since these systems operate in an unknown, dynamic and unstructured safety-critical environment, traditional safety assurance techniques are not sufficient anymore. In order to guarantee safe behavior, possibly at all times in all possible situations, they require methodologies that can observe the system status at runtime and ensure safety accordingly. To this end, we introduce a runtime safety monitoring approach that uses a rule-based safety monitor to observe the system for safety-critical deviations. The approach behaves like a fault tolerance mechanism where, the system continuously monitors itself and activates corrective measures in the event of safety-critical failures, thereby aiding the system to sustain a safe behavior at runtime. We illustrate the presented approach by employing an example from autonomous agricultural domain and discuss the case study with initial findings.