Dynamic Density: An Air Traffic Management Metric

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms

Describing Air Traffic Flows Using Stochastic Programming

International audienceThe objectives of Air Traffic Management (ATM) system is to ensure safe and efficient operation of an individual flight as well as to maximize the overall capacity and minimize the adverse environmental impacts of the air transportation system. To achieve these objectives, airspace capacity, which drives capacity and traffic flow management policies, should be more properly estimated according to the detailed traffic configuration. There have been some efforts to describe the complexity of a traffic situation based on the idea of modeling airspace onto a dynamical system. This paper extends the previous research efforts by accounting for uncertainties on aircraft's positions and velocities. The proposed method is illustrated with examples