Global vs. local decision support for multiple independent UAV schedule management

Abstract

As unmanned aerial vehicles (UAVs) become increasingly autonomous, time-critical and complex single-operator systems will require advance prediction and mitigation of schedule conflicts. However, actions that mitigate a current schedule conflict may create future schedule problems. Decision support is needed allowing an operator to evaluate different mission schedule management options in real-time. This paper describes two decision support visualisations for single-operator supervisory control of four independent UAVs performing a time-critical targeting mission. A configural display common to both visualisations, called StarVis, graphically depicts current schedule problems, as well as projections of potential local and global schedule problems. Results from an experiment showed that subjects using the locally optimal StarVis implementation had better performance, higher situational awareness, and no significant increase in workload over a more globally optimal implementation of StarVis. This research effort highlights how the same decision support design applied at different abstraction levels can produce different performance results.