Sampling-based capacity estimation for unmanned traffic management

Abstract

The plenary talk at DASC 2016 by Dr. Parimal Kopardekar, the Principal Investigator of NASA UTM program, highlighted understanding the role of volume, noise and spectrum considerations in airspace demand-capacity modeling as the three requests from UTM developers to the avionics research community [1]. This paper proposes initial answers to all three requests, for the case of unmanned aerial vehicles (UAVs) operating in low-altitude uncontrolled airspace above populated areas: we estimate airspace capacity under several metrics centered on traffic volume manageability, drones noise pollution and spectrum demand. Our work aids in bridging regulators and the industry, by providing policy makers with decision support tools which help to quantify technological requirements which the manufacturers must follow in order to ensure seamless operation of small unmanned aerial systems (sUAS) in an urban airspace.