Trajectory uncertainty and the impact on sector complexity and workload

Abstract

Complexity metrics are tools to quantify the perceived workload felt by the controller in various traffic situations. Previous complexity measures have focused on traffic density and the geometry of interacting flights. These metrics can be useful for evaluating sector and airspace design, distributing workload, benchmarking cost and productivity. These measures do not, however, address the improvements in trajectory uncertainty related to controller workload. Data from the DFS VAFORIT system clearly identifies the relationship between trajectory uncertainty and complexity. Climbing and descending aircraft are the biggest contributors to workload, due more to uncertainty around trajectory predictions than to trajectory geometry. Current complexity measures will have limited value assessing the improvements in trajectory information through the implementation of air to ground datalink. Data communication is seen as a key transformational technology in ATC. The authors believe that a new complexity component can help to quantify the extent that controller workload is reduced with Datalink and new procedures designed to reduce trajectory uncertainty. Within this paper we will propose a metric framework, where the quality of trajectory information available to the controller is included in the complexity value. This will support a mechanism for evaluating reductions in complexity and workload, as technologies and procedures associated with advanced data comm improve trajectory prediction. Our intent is to incentivize the industry to implement key data link functions. Additionally, this enables two more interesting applications: the assessment of individual complexity contribution by individual aircraft, and the mapping of sector complexity as a function of the number of Data Link equipped aircraft.