Quantifying the Effects of Uncertainty in a Decentralized National Airspace System

Abstract

Modernization of the National Air Traffic Control System is on the horizon and with it the likely introduction of autonomous air vehicles into the national airspace. With the increase in air traffic to an already congested management scheme, the implementation of a decentralized control protocol may be the answer to replace the current classical centralized management system. Equipping each aircraft with the information necessary to navigate safely through integrated airspace becomes an information-sharing problem: How much information about other aircraft is required for a pilot to fly the gamut of a heavily populated airspace safely? What paradigm shifts may be necessary for safe and efficient use of available airspace? This paper describes the development of a tool for testing alternative traffic management systems—centralized and decentralized—in the presence of uncertainty. Applying a computational fluid dynamics–inspired approach to the problem both creates a simulation tool to model the movement of traffic within the airspace and allows study of the effects of interactions between vehicles. With incorporation of a model based on smoothed particle hydrodynamics, discrete particle aircraft each carry a set of unique deterministic and stochastic properties. With this model, aircraft interaction can be studied for better understanding of how variations in the nondeterministic properties of the system affect its overall efficiency and safety. The tool is structured to be sufficiently flexible to allow incorporation of different governing equations (right-of-way rules) for aircraft traffic management.