OSU-Wing PIC Phase I Evaluation: Baseline Workload and Situation Awareness Results

TL;DR

This study investigates whether increasing the number of autonomous delivery UAS and nests degrades pilot performance. Using Wing's UAS delivery simulator and a two-session, three-condition design, the Phase I evaluation collects objective workload, SA, eye-tracking, and interaction data under nominal, DAA, and adverse weather scenarios; an IMPRINT Pro-based workload model is also developed for 1:N UAS. The results show pilots maintain high situation awareness and exhibit workload within normal ranges across nest and UAS variations, with attention focused largely on ADS-B and Wing interfaces, and only modest effects from unexpected events. These findings challenge the conventional view that higher UAS counts inherently degrade pilot performance and provide baseline data to guide Phase II investigations into mitigation strategies for safe, scalable UAS operations.

Abstract

The common theory is that human pilot's performance degrades when responsible for an increased number of uncrewed aircraft systems (UAS). This theory was developed in the early 2010's for ground robots and not highly autonomous UAS. It has been shown that increasing autonomy can mitigate some performance impacts associated with increasing the number of UAS. Overall, the Oregon State University-Wing collaboration seeks to understand what factors negatively impact a pilot's ability to maintain responsibility and control over an assigned set of active UAS. The Phase I evaluation establishes baseline data focused on the number of UAS and the number of nests increase. This evaluation focuses on nominal operations as well as crewed aircraft encounters and adverse weather changes. The results demonstrate that the pilots were actively engaged and had very good situation awareness. Manipulation of the conditions did not result in any significant differences in overall workload. The overall results debunk the theory that increasing the number of UAS is detrimental to pilot's performance.

Figures (10)

• Figure 1: The monitors with the respective open windows for each trial session. The eye tracking analysis AprilTags were aligned on the outsides and the center of the monitors.
• Figure 2: An overview of the three trial conditions by session.
• Figure 3: The task order and timing for each trial within all tasks.
• Figure 4: The X:Low weather METARs.
• Figure 5: The ADS-B display with the AOI numbered $(X,Y)$ cells of the 4 x 4 grid.