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This paper considers the problem of modeling dynamic fluctuations in aircraft concentration within a group of air traffic control sectors. Using simultaneous time series recorded for each of the sectors, a multiple transfer function noise model is constructed. The modeling procedure demonstrates a data-dependent approach to ATC systems analysis which does not rely on describing the movement of individual aircraft.

The statistical analysis of counting processes obtained from extensive sets of traffic data is often complicated by the presence of long‐term fluctuations in the rate of traffic flow. This paper describes a technique which corrects for the effects of a non‐homogeneous rate function by transforming the observed process to a time scale in which the traffic rate is approximately constant. The transformation is based on properties of the non‐homogeneous Poisson process, but it is useful in estimation and testing of a much broader class of point process models. In determining the appropriate transformation for a sequence of aircraft arrivals, both kernel estimators and exponential polynomial models for the rate function are employed. The effect of the transformation on the estimated coefficient of variation for the headway distribution and on tests for serial dependence is demonstrated. The transformation allows stationary parametric models to be constructed for traffic indices in periods of fluctuating flow r...

The construction of forecasts using interactive data analysis systems is greatly aided by the availability of graphical procedures. Data exploration, model identification and estimation, and interpretation of final forecasts are made considerably easier by the visual relay of information. This article discusses some recent developments in time series graphics designed to assist in the forecasting process. A discussion of requirerients for effective use of graphics in interactive forecasting is included as illustrated through an application of the Box-Jenkins methodology. Illustrations are included from the STATGRAPHICS system, a prototype implementation in APL.

A parametric time series model is employed to simulate the number of aircraft present in an air traffic control sector. Borrowing from the work of Box and Jenkins, the identification, parameter estimation and associated tests of adequacy are illustrated using data from a low altitude control sector. The fitted model provides a useful algorithm and reflects the time dependency which exists between the number of aircraft measured in consecutive time periods. The simulation is part of a larger air communications system simulation which is under development.