Operator Performance and Intelligent Aiding in Unmanned Aerial Vehicle Scheduling

Abstract

Interest is increasing in designing systems for controlling unmanned vehicles that will invert the current many-to-one ratio of operators to UVs. Instead of the lower-level tasks that today's UV teams perform, a single operator would focus on high-level supervisory control. A key challenge in designing such single-operator systems is to minimize periods of excessive workload that arise when critical tasks for several UVs occur simultaneously. So, we need decision support that helps the operator evaluate different action alternatives for managing a multiple-UV mission schedule in real time. Two decision support experiments have attempted to provide operators of unmanned aerial vehicles with multivariate scheduling assistance, with mixed results. Those automated decision support tools that provided more local, as opposed to global, visual recommendations performed better. This result suggests that meta-information displays could saturate operators and reduce performance. This article is part of a special issue on Interacting with Autonomy.