Task-Allocation Decisions of Human-UAS Collaboration: Effects of Workload, Trust, and Self-confidence

Abstract

Uncrewed Aerial Systems (UAS) show promise in urban air transport, package delivery, and emergency services. UAS efficiency can be significantly improved by having multiple operators ( m) managing a greater number of vehicles ( N), or the m:N architecture of operation. The current study investigates how workload affects operators’ task-allocation decision-making and the potential mediating effects of two crucial human factors, trust and self-confidence. In the context of a simulated UAS package-delivery task under the m:N architecture, two groups of participants with different levels of expertise in UAS operation will be recruited: UAS pilots and university students. Each participant will watch two sets of videos with different work-load manipulations and report their preferred task-allocation strategy for various subtasks. Measures of perceived workload, trust, and self-confidence will be conducted after each video session. Findings will inform optimizing task-allocation designs for UAS missions, considering operators’ decision-making needs and expertise disparities.