Towards Engineering Fair and Equitable Software Systems for Managing Low-Altitude Airspace Authorizations

TL;DR

The paper addresses the fairness and transparency challenges of automating low-altitude airspace authorizations for sUAS within the emerging UTM framework. It uses a vignette-based mixed-method study to elicit stakeholder perspectives on factors that should influence automated decisions and to identify concerns about AI-driven authorization. Key findings show that environmental conditions and mission characteristics are highly important, while pilot and drone history vary in influence across stakeholder groups, and distrust of AI plus a desire for human oversight are prevalent. The work informs the design of fair, equitable, and transparent UTM decision-making and highlights the need for inclusive, iterative stakeholder engagement as automation scales.

Abstract

Small Unmanned Aircraft Systems (sUAS) have gained widespread adoption across a diverse range of applications. This has introduced operational complexities within shared airspaces and an increase in reported incidents, raising safety concerns. In response, the U.S. Federal Aviation Administration (FAA) is developing a UAS Traffic Management (UTM) system to control access to airspace based on an sUAS's predicted ability to safely complete its mission. However, a fully automated system capable of swiftly approving or denying flight requests can be prone to bias and must consider safety, transparency, and fairness to diverse stakeholders. In this paper, we present an initial study that explores stakeholders' perspectives on factors that should be considered in an automated system. Results indicate flight characteristics and environmental conditions were perceived as most important but pilot and drone capabilities should also be considered. Further, several respondents indicated an aversion to any AI-supported automation, highlighting the need for full transparency in automated decision-making. Results provide a societal perspective on the challenges of automating UTM flight authorization decisions and help frame the ongoing design of a solution acceptable to the broader sUAS community.

Figures (8)

• Figure 1: Overview of an automated software system for managing low-altitude airspace authorizations. In Step 1, the operator submits a PAR. Step 2 analyzes various factors about the flight, pilot, mission, and environment and makes a decision. Step 3 grants or denies permission based on the analysis from Step 2.
• Figure 2: Flight replays of two physical sUAS flights.
• Figure 3: Study participants were asked to approve or reject a flight authorization request presented in the form of a vignette. Each vignette provided a high-level summary rather than a detailed authorization request, allowing respondents to assess the importance of pilot, drone, environmental, and mission concepts rather than focusing on low-level details.
• Figure 4: Participants rated factor importance for each vignette using a 5-point Likert scale.
• Figure 5: Overall mean ratings (0 - 100) on a slider scale for the general importance of each factor in the participants' decision-making. The error bars denote the standard deviation. The colors represent the ranked importance based on the Scott-Knott test 6235961. Dark, lighter, light and white represents the rank from first (most important) to fourth (least important).