Unmanned aircraft system demand generation and airspace performance impact prediction

Modeling and simulations of three future unmanned aircraft system (UAS) missions are described in this paper: air quality monitoring, wildfire monitoring, and on-demand air taxi. These missions are expected to have high benefit-to-cost ratio, and hence, a high potential for early adoption and integration into the national airspace system (NAS). Due to lack of historical data, input from subject matter experts involved in the air quality and wildfire monitoring domains was obtained to understand the challenges involved in modeling these two missions. On the other hand, the on-demand air taxi mission involved a strong socio-economic component, wherein the general public is directly involved in influencing the characteristics of the mission. Consequently, an activity-based modeling approach was adopted to model this mission. Demand data for the three missions were compiled into standard flight data sets (FDSs) that can be distributed to researchers across academia and the industry to conduct various impact studies on the integration of UAS into NAS. Since this research is part of an ongoing project, details of initial simulations and analyses conducted using these FDSs will also be described. NAS performance in the simulations was measured in terms of number of blind-encounter events and flight delays, before and after the introduction of UAS flights. Blind-encounters are separation violations that occur in a hypothetical uncontrolled airspace.