The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

Abstract

A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decisionsupport tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automation's ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

Influences of Uncertainties and Traffic Scenario Difficulties in a Human-in-the-Loop Simulation

“…Two controller of each team operated one high-altitude sector and one low-altitude sector, which fed the northwest corner of the Atlanta Terminal Radar Approach Control (TRACON). The main tasks were to provide safe air traffic operations and deliver the aircraft to the metering fix within ±25 seconds of the scheduled arrival time with the help of the following decision support tools [2,11]:…”

“…The count of loss of separation events, the metering fix delivery accuracy and the controller workload represent performance indicators to evaluate the controller ability to work with imprecise decision support tools. The goal was to find a point at which trajectory prediction uncertainties underlying the decision support tools would become unacceptable for the controllers [2]. This paper will investigate the question: Do the traffic scenarios have a bigger impact on performance and workload than error conditions?…”

Modeling of Complex and Diverse Aircraft Trajectories with the Trajectory Synthesizer Generalized Profile Interface

“…The fuel burn estimation tool was applied to simulated track data generated in a Human-In-The-Loop (HITL) simulation. 24 The tool can work with radar track data as well, although tolerance parameters must be adjusted to handle the greater noise in the radar track data. The goal of the HITL simulation was to evaluate the impact of a trajectory predictor's accuracy on controllers' acceptance of the decision support tools.…”

How do Air Traffic Controllers Use Automation and Tools Differently During High Demand Situations?

“…Again, interested parties can look at Ref. 12 for an overview of results regarding the primary experimental conditions for all trials.…”

“…11 A third paper gives a more general overview of the experiment and provides findings from a priori conditions. 12 The human-in-the-loop experiment required ATCs to manage aircraft in en route sectors which feed Atlanta TRACON with arrivals to Hartsfield-Jackson Atlanta International Airport. The ATCs were given decision support tools and automation to assist in their tasks, but gave voice commands to aircraft flying within their sector.…”