The human challenges of command and control with multiple unmanned aerial vehicles

Author(s):  
Bruce P. Hunn
Author(s):  
Phillip Jasper ◽  
Ciara Sibley ◽  
Joseph Coyne

Unmanned systems will play an increased role in the future beyond military application including but not limited to: search and rescue, border patrol, homeland security, and natural disaster relief operations. Current models of unmanned system operations, such as those used for unmanned aerial vehicles, require multiple operators to control a single vehicle. This multioperator-single vehicle ratio will soon shift to a multioperator-multivehicle model as the number of unmanned systems increase and work in unison to complete a mission. The purpose of this study was to determine the utility of a physiological measure i.e. heart rate variability (HRV), to assess operator workload in a single operator-multivehicle command and control simulation. An internally developed command and control simulator is described and observed effects of mental workload on HRV are reported. Results suggest that HRV can be used to assess operator workload during a command and control simulation of multiple unmanned aerial vehicles.


2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Man Zhu ◽  
Yuan-Qiao Wen

With the increasing application of unmanned surface vehicle-unmanned aerial vehicles (USV-UAVs) in maritime supervision, research on their deployment and control is becoming vitally important. We investigate the application of USV-UAVs for synergistic cruising and evaluate the effectiveness of the proposed collaborative model. First, we build a collaborative model consisting of the cruise vehicles and communication, detection, and command-and-control networks for the USV-UAV. Second, based on an analysis of the problems faced by collaborative USV-UAV systems, we establish a model to evaluate the effectiveness of such synergistic cruises. Third, we propose a weighting method for each evaluation factor. Finally, a model consisting of one UAV and four USVs is employed to validate our synergistic cruise model.


Author(s):  
Bruce P. Hunn

The unmanned aerial vehicle represents a significant challenge to its operators since they are literally out of touch with the system they control. Operating from remote sites miles from the vehicle they control, they are isolated by space and time from a direct connection to the machine they operate. While the pilot of a manned aircraft can always receive some type of direct feedback from the machine they operate, even if they lose all their control and display systems, they can still perceive many qualities of that machine's system state merely from their senses. However, in contrast, the unmanned system is based solely on an electronic link connecting the operator to their vehicle. This paper will review the historical trends in remote vehicle operation and discuss state-of-the-art in remote control systems as they apply to single or multiple unmanned aerial vehicles.


Author(s):  
Yuval Zak ◽  
Tal Oron-Gilad ◽  
Yisrael Parmet

Command and control (C2) maps in military unmanned aerial vehicles (UAVs) are often cluttered beyond the needs of operators. Unfortunately, information overload increases the operators’ mental effort and mission performance suffers. To make C2 maps more useful and improve operator performance, this study proposes a triangular approach to highlighting mission-critical information. First, the underlying value of map information and its relevance to mission success are examined. Second, algorithms based on machine learning are developed to facilitate information integration and generate visualization items, via tagging in time and space, where the appropriate area of relevance for each item is defined. Third, the algorithms are improved to dynamically update the visualizations. The proposed approach and developed algorithms are being evaluated based on four experiments with professional operators in simulated UAV and C2 environments. Hopefully, it would be possible to generalize the algorithms developed in this research-in-progress to other spatial and temporal domains where workload must be reduced.


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