Date of Award

3-2020

Document Type

Thesis

Degree Name

Master of Science in Systems Engineering

Department

Department of Systems Engineering and Management

First Advisor

Christina F. Rusnock, PhD

Abstract

Due to the advent of autonomous technology coupled with the extreme expense of manned aircraft, the Department of Defense (DoD) has increased interest in developing affordable, expendable Unmanned Aerial Vehicles (UAVs) to become autonomous wingmen for jet fighters in mosaic warfare. Like a mosaic that forms a whole picture out of smaller pieces, battlefield commanders can utilize disaggregated capabilities, such as Manned-Unmanned Teaming (MUM-T), to operate in contested environments. With a single pilot controlling both the UAVs and manned aircraft, it may be challenging for pilots to manage all systems should the system design not be conducive to a steady state level of workload. To understand the potential effects of MUM-T on the pilot’s cognitive workload, an Improved Performance Research Integration Tool (IMPRINT) Pro pilot workload model was developed. The model predicts the cognitive workload of the pilot in a simulated environment when interacting with both the cockpit and multiple UAVs to provide insight into the effect of Human-Agent Interactions (HAI) and increasing autonomous control abstraction on the pilot’s cognitive workload and mission performance. This research concluded that peaks in workload occur for the pilot during periods of high communications load and this communication may be degraded or delayed during air-to-air engagements. Nonetheless, autonomous control of the UAVs through a combination of Vector Steering, Pilot Directed Engagements, and Tactical Battle Management would enable pilots to successfully command up to 3 UAVs as well as their own aircraft against 4 enemy targets, while maintaining acceptable pilot cognitive workload in an air-to-air mission scenario.

AFIT Designator

AFIT-ENV-MS-20-M-185

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