期刊
ADVANCED ENGINEERING INFORMATICS
卷 49, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.aei.2021.101325
关键词
Air traffic control; Adaptive decision-making; Functional Near-Infrared spectroscopy; Human factors; Intelligent automation
资金
- School of Mechanical Engineering, Shandong University, Jinan, China
- Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China [RH1W,ZVS9]
- MOE (Ministry of Education in China) Project ofHumanities and Social Sciences [17YJC760009]
- Shandong Social Science Planning Fund Program [18CCXJ23]
- Program of Qilu Young Scholar, Shandong University
This study proposed a human-centered adaptive decision-making methodology that combines subjective and objective measurements through intelligent automation to enhance the intelligence and user adaptability of the ATC system. A case study of radar map operation was described to illustrate the method's feasibility and effectiveness, showing that it could capture subjective and objective data and provide real-time online feedback.
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 humancentred 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 usergenerated 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.
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