Human performance moderator functions for human-robot peer-based teams
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Modeling multiple human operators in the supervisory control of heterogeneous unmanned vehicles
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
Modeling workload impact in multiple unmanned vehicle supervisory control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Adaptive automation and cue invocation: the effect of cue timing on operator error
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A qualitative path planner for robot navigation using human-provided maps
International Journal of Robotics Research
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In the future vision of allowing a single operator to remotely control multiple unmanned vehicles, it is not well understood what cognitive constraints limit the number of vehicles and related tasks that a single operator can manage. This paper illustrates that, when predicting the number of unmanned aerial vehicles (UAVs) that a single operator can control, it is important to model the sources of wait times (WTs) caused by human-vehicle interaction, particularly since these times could potentially lead to a system failure. Specifically, these sources of vehicle WTs include cognitive reorientation and interaction WT (WTI), queues for multiple-vehicle interactions, and loss of situation awareness (SA) WTs. When WTs were included, predictions using a multiple homogeneous and independent UAV simulation dropped by up to 67%, with a loss of SA as the primary source of WT delays. Moreover, this paper demonstrated that even in a highly automated management-by-exception system, which should alleviate queuing and WTIs, operator capacity is still affected by the SA WT, causing a 36% decrease over the capacity model with no WT included.