Metrics for Traffic Complexity Management in Self-Separation Operations

Abstract

Distributed control concepts, where some air traffic management functions are performed by airspace users, have been proposed to help address the rising demand for air travel. For example, delegation of traffic separation responsibility to the flight crew can be enabled by new cockpit automation that supports the separation task for that aircraft. As more equipped aircraft provide their own separation service, it creates the potential to adapt airspace capacity to the increasing demand. However, this distribution of tasks and decision making raises the concern that independent user actions will increase the complexity of the traffic system, possibly leading to a disruption of scheduled operations as safety is maintained. To address this concern, the authors propose the introduction of decision-making metrics for preserving user trajectory flexibility. The hypothesis is that such metrics, when added to trajectory management automation, will make independent user actions naturally mitigate traffic complexity. In this paper, trajectory flexibility is formally and mathematically defined in terms of robustness and adaptability to disturbances. A metric estimation method is developed assuming discrete time and discrete maneuvering-degree-of-freedom changes, resulting in a map of flexibility over the trajectory solution space which can be used by a real-time trajectory planner. Initial insights into the relationship between trajectory planning using this metric map and traffic complexity are demonstrated through analyzing a simple scenario including required time of arrival and traffic constraints. The scenario demonstrates that preserving flexibility results in reducing relative heading between aircraft—one method for potentially reducing apparent traffic complexity.