Using Heart Rate Variability to Assess Operator Mental Workload in a Command and Control Simulation of Multiple Unmanned Aerial Vehicles

Abstract

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.

References

Bernston

G. G.

Cacioppo

J. T.

Quigley

K. S.

(1991) Autonomics determinism: The modes of autonomic space, and the laws of autonomic constraint. Psychological Review, 98, 459-487

Bernston

G. G.

Cacioppo

J. T.

Quigley

K. S.

Fabro

V. T.

(1994) Autonomic space and psychophysiological response. Psychophysiology, 31, 44-61.

Cummings

M. L.

Mitchell

P. J.

(2008) Predicting controller capacity in supervisory control of multiple UAVs. IEEE Systems, Man, and Cybernetics, 38(2).

Cummings

M. L.

Nehme

C.E.

Crandall

(2007). Predicting operator capacity for supervisory control of multiple UAVs. Innovations in Intelligent UAVs: Theory and Application, vol 70.

Dixon

S. R.

Wickens

C. D.

Chang

(2005). Mission control of multiple unmanned aerial vehicles: a workload analysis. Human factors, 47(3), 479-487

Franke

J. L.

Zaychik

Spura

T. M.

Alves

E. E.

(2005) Inverting the operator/vehicle ratio: approaches to next generation UAV command and control. Proceedings of AUVSI.

Mekdeci

Cummings

M. L.

(2009). Modeling multiple human operators in the supervisory control of heterogeneous unmanned vehicles. 9th Conference on Performance Metrics for Intelligent Systems. Gaithersburg MD, September, 2009.

Nehme

C. E.

Mekdeci

Crandall

J. W.

Cummings

M. L.

(2009). The impact of heterogeneity on operatory performance in futuristic unmanned vehicle systems. Defense Technical Information Center. 3 (1-17).

Office of Naval Research (2011) Naval S&T Strategic Plan. Arlington, VA.

10.

Ollero

Maza

(2007) Multiple Heterogeneous Unmanned Aerial Vehicles, Berlin, Springer.

11.

Saus

E. R.

Johnsen

B. H.

Eid

Thayer

J. F.

(2001). Who benefits from simulator training: Personality and heart rate variability in relation to situation awareness during navigation training? Computers in Human Behavior, 28(4), 1262-1268.

12.

Stern

R. M.

Ray

W. J.

Quigley

K. S.

(2001) Psychophysiological recording. New York. Oxford University Press

13.

Tattersall

E. J.

Hockey

G. R. L.

(1995). Level of operator control and changes in heart rate variability during simulated flight maintenance. Human factors. 37(4), pp 682.

14.

Veltman

J. A.

Gaillard

A. W. K.

(1996) Physiological indices of workload in a simulated flight task. Biological Psychology, 42, 323-342.