Integrating Runtime Verification into an Automated UAS Traffic Management System

Cauwels, Matthew
Hammer, Abigail
Hertz, Benjamin
Jones, Phillip
Rozier, Kristin Yvonne
Rozier, Kristin Yvonne
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Aerospace Engineering
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Aerospace EngineeringComputer ScienceVirtual Reality Applications CenterElectrical and Computer EngineeringMathematics

Unmanned Aerial Systems (UAS) are quickly integrating into the National Air Space (NAS). With the number of registered small (under 55 pounds) UAS in the USA alone at over 1.5 million, and projected to expand rapidly, according to the Federal Aviation Administration (FAA), safety is a pressing consideration. Safe UAS integration into the NAS requires an intelligent, automated system for UAS Traffic Management (UTM). Even more than for manned aircraft, UTM must integrate runtime checks to ensure system safety, at the very least to make up for the lack of humans on board to employ the common-sense safety checks ingrained into the culture of human aviation.

We overview a candidate automated, intelligent UTM system and propose multiple integration points for runtime verification (RV) to ensure that each part of the UTM adheres to safety requirements during operation. We write, validate, and present patterns for formal requirements across multiple subsystems of this UTM framework. After encoding our requirements as flight-certifiable runtime observers in the R2U2 RV engine, we execute them in simulation across multiple real-life test flights supplemented with simulated data to cover additional cases that did not occur in flight. Lessons learned accompany an analysis of the efficacy and performance of RV integration into the UTM framework.


This is a post-peer-review, pre-copyedit version of a book chapter published as Cauwels, Matthew, Abigail Hammer, Benjamin Hertz, Phillip H. Jones, and Kristin Y. Rozier. "Integrating Runtime Verification into an Automated UAS Traffic Management System." In: Muccini H. et al. (eds) Software Architecture. ECSA 2020. Communications in Computer and Information Science 1269 (2020): 340-357. DOI: 10.1007/978-3-030-59155-7_26. Posted with permission.