Decision support systems for air traffic controllers based on the analysis of their decision-making processes

Abstract

The growth of air traffic generates a multitude of data and parameters that makes it increasing difficult for air traffic controllers to choose rapidly and safely what to decide. The study of air-traffic control of full or partial automation over the past years highlights the need for better tools to meet the challenges of modern air-traffic management. Initial attempts of full automation have mistakenly side lined air-traffic controllers in their role as key players in air-traffic management. This has led to human-machine cooperation studies that actively involve air-traffic controllers in the resolution of problems. Such studies show the advantages of creating cooperative tools in concert with the conflict management process. The designing of conflict resolution tools in this way implies, however, detailed knowledge of air traffic controllers’ decision-making processes. To do this, we have developed a cooperative multi-criteria approach based on data taken from case study interviews. This shows how it is possible to extract criteria and preferences in designing bottom-up decision aiding tools. In doing this, we have laid down the foundation for the creation of decision support system.