Air Traffic Conflict Models

Abstract

Semi-empirical random variable models of the expected number of air traffic conflicts as a function of air traffic density are derived. Model parameters are determined from analysis and simulation of real air traffic data. These models are applied to simulated air traffic scenarios to analyze conflict properties in various conflict resolution strategies. It is shown that under free routing conditions (i.e. aircraft do not necessarily fly along structured jet routes), the expected number of conflicts is well represented by a binomial random variable model. Using this model, it is further demonstrated how conflict resolution may cause a chain reaction, leading to an increased number of conflicts for all aircraft, and how the model may be used to predict the airspace capacity for a given conflict resolution strategy. In a separate study, it is shown that for an iterative horizontal-plane conflict resolution strategy, a random variable model with the geometric distribution closely matches empirical data. This model also predicts the aircraft density at which the airspace becomes saturated. It is shown how analysis of conflicts in the horizontal plane may be scaled and applied to the analysis of conflicts in 3-dimensional airspace. In this paper, probabilistic models of air traffic conflict situations are derived and analyzed to gain physical insight into the relationship between increasing air traffic density and the expected number of conflicts between aircraft. The first section examines the expected number of conflicts under both a structured routing system and under a free routing system. It is shown that a binomial random variable model closely matches observations of the number of conflicts when conflict resolution is not applied. The effect of conflict resolution maneuvering on the expected number of conflicts is also examined. An analytical model is derived, and simulation results are used to verify the model. The second main section of this paper introduces a model of the expected number of conflicts when an iterative approach to conflict resolution is taken. This model is examined to show how it may be used to predict maximum airspace capacity.