Date of Graduation

5-2026

Document Type

Thesis

Degree Name

Master of Science in Mechanical Engineering (MSME)

Degree Level

Graduate

Department

Mechanical Engineering

Advisor/Mentor

Majumdar, Neelakshi

Committee Member

Campbell, Jenn

Second Committee Member

Ham, Richard

Keywords

Advanced Air Mobility; Analytical Hierarchy Process; Community Acceptance; Route Modeling; Social Factors

Abstract

Advanced air mobility (AAM) is an emerging mode of transportation that integrates advanced aircraft technologies, such as manned air taxis or unmanned freight drones, to transport people and goods across urban and regional environments. While these technologies promise to transform mobility, successful implementation depends heavily on community acceptance, which is shaped by multiple social factors. This study presents a multi-criteria decision framework to evaluate and prioritize the key social factors influencing AAM adoption. A literature review identified six primary social factors: safety, noise, privacy and cybersecurity, automation, environmental impact, and price and economics. The Analytical Hierarchy Process (AHP) was used to perform pairwise comparisons among these factors and assign relative importance weights based on their prevalence and emphasis in the literature. The analysis showed that safety has the highest priority (41%), followed by noise (25%), with the remaining factors each below 15%. The weights were then used to develop a geospatial implementation model for Northwest Arkansas using ArcGIS Pro, incorporating the two highest-priority social factors (i.e., safety and noise) alongside demographic and operational variables. The resulting route network showed that incorporating the AHP-derived weights of safety and noise into the route design increases route length by 5.65% compared with direct flight and by 0.13% compared with equally weighted factors (safety and noise). These results indicate that community acceptance and social factors can be incorporated into AAM route design at minimal additional cost. This thesis demonstrates that socially informed route design is a feasible and low-cost approach to AAM implementation planning, offering a replicable framework for other urban and regional contexts and AAM use cases.

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