Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment.
Adaptive Automation(AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both theunder- andover-loadconditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard,passive Brain-Computer Interface(pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behavior (e.g., mental workload) of a subject by analyzing its neurophysiological signals (i.e., brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realisticAir Traffic Management(ATM) research simulator developed and hosted at ENAC (École Nationale de l'Aviation Civileof Toulouse, France). TwelveAir Traffic Controller(ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e., overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator's workload level toward potentially dangerous conditions of underload.
Department of Molecular Medicine, Sapienza University of RomeRome, Italy; BrainSigns Co. Ltd, Spin-off Company from Sapienza University of RomeRome, Italy; Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy.
Pietro
P
Aricò
Department of Molecular Medicine, Sapienza University of RomeRome, Italy; BrainSigns Co. Ltd, Spin-off Company from Sapienza University of RomeRome, Italy; Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy.
Gianluca
G
Borghini
BrainSigns Co. Ltd, Spin-off Company from Sapienza University of RomeRome, Italy; Neuroelectrical Imaging and BCI Lab, Fondazione Santa Lucia (IRCCS)Rome, Italy; Department of Anatomical, Histological, Forensic Medicine and Orthopedic Sciences, Sapienza University of RomeRome, Italy.
Gianluca
G
Di Flumeri
Department of Anatomical, Histological, Forensic Medicine and Orthopedic Sciences, Sapienza University of Rome Rome, Italy.
Alfredo
A
Colosimo
DeepBlue srl Rome, Italy.
Stefano
S
Bonelli
DeepBlue srl Rome, Italy.
Alessia
A
Golfetti
DeepBlue srl Rome, Italy.
Simone
S
Pozzi
École Nationale de l'Aviation Civile Toulouse, France.
Jean-Paul
JP
Imbert
École Nationale de l'Aviation Civile Toulouse, France.
Géraud
G
Granger
École Nationale de l'Aviation Civile Toulouse, France.
Raïlane
R
Benhacene
Department of Molecular Medicine, Sapienza University of RomeRome, Italy; BrainSigns Co. Ltd, Spin-off Company from Sapienza University of RomeRome, Italy.
Fabio
F
Babiloni
Adaptive Automation (AA); Air Traffic Management (ATM); electroencephalogram (EEG); human factors; human machine interaction; machine learning; mental workload; passive brain-computer interface (pBCI)