AIAA Design Challenge: Austere Field Light Attack Aircraft; How the Psychological and Social Aspects of Fully Autonomous Commercial Flight will affect its Rate of Adoption

Author:
Hanafin, Catherine, School of Engineering and Applied Science, University of Virginia
Advisors:
Foley, Rider, EN-Engineering and Society, University of Virginia
Quinlan, Jesse, EN-Mech/Aero Engr Dept, University of Virginia
Abstract:

The problem my research solves is the need for new light attack aircraft in the United States military. The technical advantage of these aircraft is that they can land and takeoff on unsophisticated runaways, require less maintenance, and can be acquired at lower costs. The technology developed by my team in my Capstone project solves this problem as we are implementing an iterative design approach to create a new light attack aircraft that is able to carry a specified payload, takeoff on austere fields, and meet several other requirements.
For the human and social dimensions of technology, the rate of adoption of fully autonomous commercial aircraft will be explored. Specifically, this research will be in relation to the psychological and social aspects of the potential adopters of the technology. The theory used to analyze this research will be Everett Roger’s Diffusion of Innovations framework, specifically the chapter on rate of adoption of technology. The relative advantage, compatibility, complexity, trialability, and observability of the psychological and social aspects of fully autonomous commercial flight will be explored. In order to accomplish this, a thematic analysis of counting the instances that published studies, agency reports, and media accounts mention positive or negative themes related to these five attributes will be conducted.

Degree:
BS (Bachelor of Science)
Keywords:
flight, autonomous flight, attack aircraft, rate of adoption, diffusion of innovations
Notes:

School of Engineering and Applied Science
Bachelor of Science in Aerospace Engineering
Technical Advisor: Jesse Quinlan
STS Advisor: Rider Foley
Technical Team Members: Will Ayscue, David Gibbs, Lauren Hancock, Blake Mager, Brendan Schneider, Hope Wheeler

Language:
English
Issued Date:
2021/05/11