Modern cyber operations require operators to maintain supervisory control of remote computer agents. A current operational concern is the number of agents an operator can control at once. This type of task resonates with similar Human Supervisory Control (HSC) research that has been conducted in environments such as Unmanned Aerial Vehicle operations. Within the relevant literature, there has been limited discussion of cyber-HSC, and no available experimental research. In this paper, we present an initial exploration cyber-HSC. Using the BOARD 1.5 Simulation, we manipulated the number of autonomous assets accessible to a human operator. We expected that as the number of autonomous agents available increased, we would observe concomitant changes in human performance and cognition.However, our results indicated that participants’ overall span-of-control did not vary with additional agents. Our findings highlight the need for continued research on issues of supervisory control within cyber operations.
References
1.
BarnesM. J.MatzM. F. (1998, October). Crew simulations for unmanned aerial vehicle (UAV) applications: Sustained effects, shift factors, interface issues, and crew size. In Proceedings of the 42nd Annual Meeting of the Human Factors and Ergonomics Society, Chicago, IL5-9 October (pp. 143-147). HFES.
2.
CrandallJ. W.CummingsM. L. (2007). Identifying Predictive Metrics for Supervisory Control of Multiple Robots. IEEE Transactions on Robotics, 23(5), 942-951.
3.
CrandallJ. W.GoodrichM. A.NielsenC. W. (2005). Validating human-robot interaction schemes in multitasking environments. IEEE Transactions on Systems, Man, and Cybernetics, 35(4), 438-439.
4.
CummingsM. L.GuerlainS. (2004, September). An interactive decision support tool for real-time in-flight replanning of autonomous vehicles. AIAA 3rd Unmanned Unlimited Technical Conference, Workshop and Exhibit, Chicago, Il.
5.
CummingsM. L.GuerlainS. (2007). Developing operator capacity estimates for supervisory control of autonomous vehicles. Human Factors: The Journal of the Human Factors and Ergonomics Society, 49(1), 1-15.
6.
CummingsM. L.NehmeC. E.CrandallJ. W.MitchellP. (2007). Predicting Operator Capacity for Supervisory Control of Multiple UAVs. Innovations in Intelligent Machines: Studies in Computational Intelligence, 1(70), 11-37.
7.
DixonS. R.WickensC. D.ChangD. (2005). Mission Control of Multiple Unmanned Aerial Vehicles: A Workload Analysis. Human Factors, 47(3), 479-487.
8.
EndsleyM. R.RodgersM. D. (1994, October). Situation awareness information requirements analysis for en route air traffic control. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Nashville, TN24-28 October (pp. 71-75). HFES.
9.
Federation of American Scientists. (2009). United States Air Force unmanned aircraft systems flight plan 2009-2047. Retrieved from Headquarters, United States Air Force website: https://www.fas.org/irp/program/collect/uas_2009.pdf
10.
GalsterS. M.DuleyJ. A.MasalonisA. J.ParasuramanR. (2001). Air Traffic Controller Performance and Workload Under Mature Free Flight: Conflict Detection and Resolution of Aircraft Self-Separation. International Journal of Aviation Psychology, 11(1), 71-93.
11.
GiacobeN. A. (2013, September). A Picture is Worth a Thousand Alerts. In Proceedings of the 57th Annual Meeting of the Human Factors and Ergonomics Society, 30 September - 4 October (pp. 172-176). San Diego, CA, HFES.
12.
GosakanM. (2011). HSI Tool Enhancements to Better Represent Operator Workload When Controlling Unmanned Systems. Final Report submitted to Leonard Wood Institute.
13.
GrieveA. P. (1984). Tests of sphericity of normal distributions and the analysis of repeated measures designs. Psychometrika, 49(2), 257-267.
14.
JonesD. G.EndsleyM. R. (1996). Sources of situation awareness errors in aviation. Aviation, Space, and Environmental Medicine, 67(6), 507-512.
15.
LevinthalB. R.WickensC. D. (2006, October). Management of multiple UAVs with imperfect automation. In Proceedings of the 50th Annual Meeting of the Human Factors and Ergonomics Society Annual Meeting. San Francisco, CA, 16-20 October (pp. 1941-1944).
16.
MancusoV. F.McNeeseM. D. (2012, September). Effects of Integrated and Differentiated Team Knowledge Structures on Distributed Team Cognition. Proceedings of the 56th Annual Meeting of the Human Factors and Ergonomics Society, 22-26 October (pp. 388-392). Boston, MA. HFES
17.
MetzgerU.ParasuramanR. (2001). The Role of the Air Traffic Controller in Future Air Traffic Management: An Empirical Study of Active Control versus Passive Monitoring. Human Factors, 43(4), 519-528.
18.
MillerC. (2004). Modeling human workload limitations on multiple UAV control, Proceedings of the 48th Annual Meeting of the Human Factors and Ergonomics Society, Santa Monica, CA: HFES, 526
19.
MitchellP. M.CummingsM. L.SheridanT. B. (2005, May). Management of multiple dynamic human supervisory control tasks. In 10th International Command and Control Research and Technology Symposium. MacLean, VA (pp. 1 - 11).
20.
NehmeC. E.KilgoreR. M.CummingsM. L. (2008, September). Predicting the impact of heterogeneity on unmanned-vehicle team performance. In Proceedings of the 52nd Annual Meeting of the Human Factors and Ergonomics Society, New York, NY22-26 September (pp. 917-921). HFES.
21.
RajivanP.JanssenM. A.CookeN. J. (2013, September). Agent-Based Model of a Cyber Security Defense Analyst Team. In Proceedings of the 57th Annual Meeting of the Human Factors and Ergonomics Society, 30 September - 4 October (pp. 314-318). San Diego, CA, HFES.
22.
TsangP. S.VelazquezV. L. (1996). Diagnosticity and multidimensional subjective workload ratings. Ergonomics, 39(3), 358-381.
23.
TyworthM.GiacobeN.MancusoV.McNeeseM.HallD (2013). A Human-In-The-Loop Approach to Understanding Situation Awareness in Cyber Defense Analysis. EAI Endorsed Transactions on Security and Safety, 13(2), 1-10.
24.
VelagapudiP.ScerriP.SycaraK.WangH.LewisM.WangJ. (2008, September). Scaling effects in multi-robot control. Intelligent robots and systems, Nice, Fr.
25.
WickensC. D.GosakanM.GacyA. M.LauxL. (2013, May). Control of multiple unmanned vehicles: A capacity model from a meta-analysis. 17th international symposium on aviation psychology, Dayton, OH6-9 May D(pp 347-350).
26.
WickensC.DixonS. (2007). The benefits of imperfect diagnostic automation: a synthesis of the literature. Theoretical Issues in Ergonomics Science, 8(3), 201-212.
