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In Air Traffic Management (ATM), Air Traffic Control (ATC) is becoming increasingly challenging as controllers handle increasing volumes of air traffic while simultaneously adapting to novel technological systems. This surge in complexity places greater cognitive demands on Air Traffic Controllers (ATCOs), making their tasks more mentally demanding. This paper presents some research works coming from Single European Sky ATM Research (SESAR) projects and delivered by a large European Consortium over the past decade. Based on this work, this article seeks to present a neurophysiologically based approach to strengthening Human–Machine Teaming (HMT) in the frame of ATC/ATM by integrating neurophysiological data. By leveraging multi-modal signals, including Electroencephalography (EEG), Electrocardiography (ECG), Electrodermal Activity (EDA), Galvanic Skin Response (GSR), and eye-tracking, the framework can be based on the operator’s mental states. By targeting specific controller’s cognitive and affective states, real-time system adaptations can be used in order to decrease controller’s workload, stress and fatigue while enhancing situational awareness, vigilance, and trust. The five projects being discussed here (NINA, MOTO, ARTIMATION, TRUSTY and CODA) collectively demonstrate the growing relevance of the neurophysiology-based approach to developing the new ATC/ATM tools of the years to come.

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Toward a Neurophysiological Approach to Assess Optimal Human-Machine Teaming in the Critical Environment of Air Traffic Control

  • 会议论文

  • 发表日期：

    2026年

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  • Christophe Hurter,
  • Alexandre Veyrie,
  • Sara Kebir,
  • Guillaume Truong,
  • Stefano Bonelli,
  • Gianluca Borghini,
  • Pietro Aricò,
  • Fabio Babiloni,
  • Marc Baumgartner,
  • Juan Alberto Besada,
  • Luca Bergesio,
  • Almudena Calatrava,
  • Jose J. Cañas Delgado,
  • Lidia Garcia,
  • Raquel Garcia Lasheras,
  • Brais Iglesias,
  • Martina Jadronova,
  • Florencia Lema,
  • Alfonso Levantesi,
  • Patricia Maria Lopez De Fruto,
  • Hossein Mapar,
  • Laurie Marsman,
  • Job Smeltink,
  • Anthony Smoker,
  • Maykel van Miltenburg,
  • Anna Giulia Vicario,
  • Chen Xia,
  • Rolf Zon

摘要

In Air Traffic Management (ATM), Air Traffic Control (ATC) is becoming increasingly challenging as controllers handle increasing volumes of air traffic while simultaneously adapting to novel technological systems. This surge in complexity places greater cognitive demands on Air Traffic Controllers (ATCOs), making their tasks more mentally demanding. This paper presents some research works coming from Single European Sky ATM Research (SESAR) projects and delivered by a large European Consortium over the past decade. Based on this work, this article seeks to present a neurophysiologically based approach to strengthening Human–Machine Teaming (HMT) in the frame of ATC/ATM by integrating neurophysiological data. By leveraging multi-modal signals, including Electroencephalography (EEG), Electrocardiography (ECG), Electrodermal Activity (EDA), Galvanic Skin Response (GSR), and eye-tracking, the framework can be based on the operator’s mental states. By targeting specific controller’s cognitive and affective states, real-time system adaptations can be used in order to decrease controller’s workload, stress and fatigue while enhancing situational awareness, vigilance, and trust. The five projects being discussed here (NINA, MOTO, ARTIMATION, TRUSTY and CODA) collectively demonstrate the growing relevance of the neurophysiology-based approach to developing the new ATC/ATM tools of the years to come.