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A Trajectory Clustering Framework to Analyse Air Traffic Flows

Abstract : This paper describes a framework to automatically identify air traffic flows from a set of trajectories by using a clustering algorithm. The framework offers two methods to cluster trajectories, each one using a different distance/similarity measure between trajectories. Results and performance characteristics of both methods are compared by applying them to real trajectories over a French Area Control Center. The framework can output statistics and figures for flow analysis and its use is facilitated by the relatively low number of parameters to be provided by the user. Its aim is to help support the SESAR vision of flow-centric operations by being integrated into Air Traffic Management tools, e.g. for airspace design/management or for analysis of traffic patterns in a free route environment.
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Submitted on : Tuesday, December 5, 2017 - 10:35:38 AM
Last modification on : Tuesday, October 19, 2021 - 11:02:50 AM


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  • HAL Id : hal-01655747, version 1



Luis Basora, Jérôme Morio, Corentin Mailhot. A Trajectory Clustering Framework to Analyse Air Traffic Flows. SID 2017, 7th SESAR Innovation Days, Nov 2017, Belgrade, Serbia. ⟨hal-01655747⟩



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