An Analysis of Heterogeneity in Futuristic Unmanned Vehicle Systems

Abstract

Recent studies have shown that with appropriate operator decision support and with enough automation aboard unmanned vehicles, inverting the multiple operators to single-vehicle control paradigm is possible. These studies, however, have generally focused on homogeneous teams of vehicles, and have not completely addressed either the manifestation of heterogeneity in vehicle teams, or the effects of heterogeneity on operator capacity. An important implication of heterogeneity in unmanned vehicle teams is an increase in the diversity of possible team configurations available for each operator, as well as an increase in the diversity of possible attention allocation schemes that can be utilized by operators. To this end, this paper introduces a resource allocation framework that defines the strategies and processes that lead to alternate team configurations. The framework also highlights the sub-components of operator attention allocation schemes that can impact overall performance when supervising heterogeneous unmanned vehicle teams. A subsequent discrete event simulation model of a single operator supervising multiple heterogeneous vehicles and tasks explores operator performance under different heterogeneous team compositions and varying attention allocation strategies. Results from the discrete event simulation model show that the change in performance when switching from a homogeneous team to a heterogeneous one is highly dependent on the change in operator utilization. Heterogeneous teams that result in lower operator utilization can lead to improved performance under certain operator strategies.