The Impact of Heterogeneity on Operator Performance in Future Unmanned Vehicle Systems

Recent studies have shown that with appropriate operator decision support and with sufficient automation, inverting the multiple operators to single-unmanned 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 discrete event simulation (DES) model as a means to model a single operator supervising multiple heterogeneous unmanned vehicles. The DES model can be used to understand the impact of varying both vehicle team design variables (such as team composition) and operator design variables (including attention allocation strategies). The model also highlights the sub-components of operator attention allocation schemes that can impact overall performance when supervising heterogeneous unmanned vehicle teams. Results from an experimental case study are then used to validate the model, and make predictions about operator performance for various heterogeneous team configurations.The research was supported by Charles River Analytics, the Office of Naval Research (ONR), and MIT Lincoln Laboratory