The safety and e ciency of free ight will bene t from automated con ict prediction and resolution advisories. Con ict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a con ict will occur, given a pair of predicted trajectories and their levels of uncertainty. This paper presents a method to estimate that con ict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single, equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and a Monte Carlo validation are presented.

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The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories.Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however.An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. This paper presents a method to estimate that conflict probability.The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single, equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and a Monte Carlo validation are presented. SECURITY CLASSIFICATION

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In this article we present recent work towards the development of an autonomous system that performs conflict resolution and arrival scheduling for aircraft in the terminal airspace around an airport. An autonomous air traffic control system is defined as a system that can safely solve the major traffic management problems currently handled by human controllers. It has the potential to handle higher traffic levels and a mix of conventional and unmanned aerial vehicles with reduced dependency on controllers. The main objective of this paper is to describe the fundamental trajectory algorithms that must be incorporated in such a system. These algorithms generate arrival trajectories that are free of conflicts with other traffic, and meet scheduled times of arrival for landing with specified in-trail spacings. The maneuvers the system employs to resolve separation and spacing conflicts include speed control, horizontal maneuvers, and altitude changes. Furthermore, the system can reassign arrival aircraft to a different runway in order to reduce delays. Examples of problems solved and performance statistics from a fast-time simulation using simulated traffic of arrivals and departures at the Dallas/Fort Worth International Airport and Dallas Love Field Airport are also provided.