Theobjective ofthisstudy wasto understand howrole authority and communication initiative of autonomous agents impact Human-Autonomy Team (HAT) performance, trust, workload, and cohesion. The study employed a 2 (role authority: peer vs.subordinate) x 2 (communication initiative: proactive vs.reactive robot communication) mixed factorial design.Participantsworkedcollaboratively with Boston Dynamic’s Spot robotto conductanin-person search and rescue taskin afield environment.The study revealedthe subordinate role authority condition, where therobot-is-subordinate tothehuman, imposed a higher workload thanthe peer condition, where the robot-is-peertothe human.
Get full access to this article
View all access options for this article.
References
1.
AzharM. Q.SklarE. I. (2017). A study measuring the impact of shared decision making in a human-robot team.The International Journal of Robotics Research,36, 461–482. https://doi.org/10.1177/0278364917710540
2.
BeerJ.FiskA. D.RogersW.A. (2014). Toward a framework for levels of robot autonomy in human-robot interaction. In Journal of Human-Robot Interaction3 (2) 74-99. http://dx.doi.org/10.5898/JHRI.3.2.Beer.
3.
CaseyS.A.De PaolaC. (2000). The measurement of cohesion in work teams. Small Group Research, 31, 71–88.
4.
Casey-CampbellM.MartensM. L. (2009). Sticking it all together: A critical assessment of the group cohesion– performance literature. International Journal of Management Reviews, 11, 223–246
5.
ChenJ. Y.BarnesM. J. (2012). Supervisory control of multiple robots: Effects of imperfect automation and individual differences. Human Factors, 54, 157–174.
6.
De CubberG.DorofteiD.RodaR.SilvaE.OurevitchS.MatosA.RudinK. (2017). Chapter Introduction to the Use of Robotic Tools for Search and Rescue.http://dx.doi.org/10.5772/intechopen.69489.
7.
DemirM.McNeeseN. J.CookeN. J. (2016). Team communication behaviors of the human- automation teaming conference session. 2016 IEEE International Multi- Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA) (pp. 28–34). IEEE
8.
EndsleyM. R. (2015). Autonomous horizons: System autonomy in the air force – A path to the future (Autonomous Horizons No. AF/ST TR15-01). Washington DC: Department of the Air Force Headquarters of the Air Force. Retrieved from
9.
FanX.OhS.McNeeseM.YenJ.CuevasH.StraterL.EndsleyM. R. (2008). The influence of agent reliability on trust in human-agent collaboration. Proceedings of the 15th European Conference on Cognitive Ergonomics: the Ergonomics of Cool Interaction (pp. 1–8).
10.
HartS.G.StavelandL.E. (1988). Development of NASA-TLX (task load index): Results of empirical and theoretical research. Advances in Psychology, 52, 3-4.
JohnsonM.BradshawJ. M.FeltovichP. J.JonkerC.van RiemsdijkB.SierhuisM. (2012). Autonomy and interdependence in human-agent robot teams. IEEE Intelligent Systems, 27, 43–51. https://doi.org/10.1109/MIS.2012.1
13.
KelleyJ. F. (1984). An iterative design methodology for user-friendly natural-language office information applications. ACM Transaction son Office Information Systems, 2, 26-41.
14.
LyonsJ. B.MahoneyS.WynneK. T.RoebkeM. A. (2018). Viewing machines as teammates: A qualitative study. 2018 AAAI Spring Symposium Series
15.
McNeeseN. J.DemirM.CookeN. J.MyersC. (2018). Teaming with a synthetic teammate: Insights into human- autonomy teaming. Human Factors, 60, 262–273. https://doi.org/10.1177/0018720817743223
16.
NeubauerC.ForsterD.E.BlackmanJ.LakhmaniS.FitzhughS. M.KrausmanA.SchaeferK.E.BergS.RoviraE. (2021). Developing a New Human-Autonomy Team Cohesion Scale. DEVCOM Army Research Laboratory.
17.
NomuraT.SuzukiT.KatoK. (2004). “Psychology in human-robot communication: an attempt through investigation of negative attitudes and anxiety toward robots,” RO-MAN 2004. 13th IEEE International Workshop on Robot and Human Interactive Communication, pp. 35-40, doi: 10.1109/ROMAN.2004.1374726.
18.
O’NeillT.McNeeseN.BarronA.SchelbleB. (2020). Human–autonomy teaming: A review and analysis of the empirical literature. Human Factors, 0018720820960865.
19.
RoviraE.McGarryK.ParasuramanR. (2007). Effects of imperfect automation on decision making in a simulated command and control task. Human Factors, 49(1), 76-87.
20.
SchaeferK. E. (2016). Measuring trust in human robot interactions: Development of the “trust perception scale-HRI”. In Robust Intelligence and Trust in Autonomous Systems (pp. 191-218). Springer, Boston, MA.
21.
SheridanT. B.VerplankW. L. (1978). Human and computer control of undersea teleoperators. Massachusetts Institute of Technology Cambridge: Man-Machine Systems Lab. https://doi.org/10.21236/ada057655
22.
WalliserJ. C.MeadP. R.ShawT. H. (2017). The perception of teamwork with an autonomous agent enhances affect and performance outcomes. Proceedings of theHuman Factors and Ergonomics Society Annual Meeting, 61, 231–235.
23.
WrightJ. L.ChenJ. Y. C.BarnesM. J. (2018). Human–automation interaction for multiple robot control: The effect of varying automation assistance and individual differences on operator performance. Ergonomics, 61, 1033–1045. https://doi.org/10.1080/00140139.2018.1441449
