The Impact of Automation on Air Traffic Controller’s Behaviors

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Yanjun Wang - , Nanjing University of Aeronautics and Astronautics (Autor:in)
  • Rongjin Hu - , Nanjing University of Aeronautics and Astronautics (Autor:in)
  • Siyuan Lin - , Nanjing University of Aeronautics and Astronautics, AVIC ATM System and Equipment Co. (Autor:in)
  • Michael Schultz - , Professur für Technologie und Logistik des Luftverkehrs (Autor:in)
  • Daniel Delahaye - , Ecole Nationale de l Aviation Civile (Autor:in)

Abstract

Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reducing the controller’s task-load. Much attention has been devoted to developing advanced automation in the last decade. However, less is known about the impact of automation on the behaviors of air traffic controllers. Here, we empirically tested the effects of three levels of automation—including manual, attention-guided, and automated—as well as varying traffic levels on eye movements, situation awareness and mental workload. The results showed that there are significant differences in the gaze and saccade behaviors between the attention-guided group and automated group. Traffic affected eye movements under the manual mode or under the attention-guided mode, but had no effect on eye movements under the automated mode. The results also supported the use of automation for enhancing situation awareness while reducing mental workload. Our work has potential implications for the design of automation and operation procedures.

Details

OriginalspracheEnglisch
Aufsatznummer260
FachzeitschriftAerospace
Jahrgang8
Ausgabenummer9
PublikationsstatusVeröffentlicht - 13 Sept. 2021
Peer-Review-StatusJa

Externe IDs

Scopus 85115245250

Schlagworte

Schlagwörter

  • air traffic controller, air transportation, automation, eye movements, human factors