Relating Air Traffic Controller Perceived Complexity to Characteristics of Individual En-Route Flights

Abstract

Increasing levels of automation in the ATM system are required to allow for higher traffic densities without exceeding the ATCo’s mental capacity. Maastricht Upper Area Control Centre envisions to first automate the control of, so called, ``basic’’ traffic. For this strategy to work, an allocation model is required to determine the complexity of each individual flight entering the airspace, based on objective and predictable flight characteristics, which can allocate a flight to human or automation control. Five metrics are proposed related for the individual flight complexity, and their predictive ability is tested with a human-in-the-loop experiment, where air traffic controllers were tasked with assessing the complexity of an individual flight in a series of static scenarios and indicate which other flights in the scenario affected the complexity score.
Results show that the complexity is depends mostly on flights that near each other within 10 NM in the horizontal plane and have overlapping flight levels. Furthermore, flights requiring a flight level change are considered more complex as the number of possible interactions increases due to the vertical change and the additional dimension increases the uncertainty of the trajectory. The performance of the metrics indicated a dependency on different traffic patterns, leading to the conclusion that the use of only one metric is too limited to describe the complexity, and future research is needed to better understand the interdependence between the metrics.