A human-centred approach based on functional near-infrared spectroscopy for adaptive decision-making in the air traffic control environment: A case study. (August 2021)

• Record Type: Journal Article
• Authors: Li, Qinbiao; Ng, Kam K.H.; Fan, Zhijun; Yuan, Xin; Liu, Heshan; Bu, Lingguo
• Is Part Of: Advanced engineering informatics. Volume 49(2021)
• Publication Date: 2021-08
• Subjects: Air traffic control -- Adaptive decision-making -- Functional Near-Infrared spectroscopy -- Human factors -- Intelligent automation; ATC Air traffic control -- ATM Air traffic management -- ATCOs Air traffic controll officers -- HFs Human factors -- DM Decision-making -- IA Intelligent automation -- EEG Electroencephalography -- fNIRS Functional near-infrared spectroscopy -- fMRI Functional magnetic resonance imaging -- GSR Galvanic skin response -- VAS Visual analogue scoring -- RPFC right prefrontal cortex -- LRFC left prefrontal cortex -- RMC light motor cortex -- LMC left motor cortex -- ROL right occipital lobe -- LOL left occipital lobe; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2021.101325
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: Safety-critical systems like air traffic control (ATC) are usually less automated than might be expected by the public, so human intelligence will remain at the core in the decision-making (DM) process. Meanwhile, human factors (HFs) need to be fully considered in the DM process, which can design the ATC system to be more intelligent and more adaptive to the behaviour of the user. However, the existing DM research lacks the systematic methods that fully consider human performance in a smart manner. This study proposed a human-centred adaptive DM methodology that combines subjective and objective measurements made by functional near-infrared spectroscopy (fNIRS) via intelligent automation (IA). Moreover, this paper also described a case study of radar display map operation, including descriptive and optimised maps, to illustrate the proposed approach and verify its feasibility and effectiveness. The results were determined by jointly considering the user-generated and system-generated data and suggested that the proposed approach could capture subjective and objective data, take into consideration the HFs information to provide real-time online feedback and adjust the decision support system to HFs. It is hoped that this study can promote the methodology of human-centred subjective and objective data-driven applications in the future ATC environment adaptive decision research.