Method to Characterize Potential UAS Encounters Using Open Source Data

TL;DR

This paper presents a methodology that uses open source geospatial data and parallel processing to analytically characterize potential encounters between UASs in the US airspace, aiding safety technology development.

Contribution

It introduces a novel approach combining open source data and high-performance computing to estimate all potential UAS encounter geometries during inspection missions.

Findings

Performed trillions of calculations across sixteen locations.

Estimated relative horizontal distances between UASs.

Demonstrated scalability of the method using open source data.

Abstract

As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.