Airspace statistical proximity maps based on data-driven flow modeling

Erwan Salaün, Maxime Gariel, Adan E. Vela, Eric Feron, John Paul B. Clarke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

This paper presents a new methodology that aims to rapidly generate 3-D sector proximity maps, which indicate the probability of presence of at least one or two aircraft at any given point in a considered sector. The maps are generated using an aircraft flow model driven from historical data. Time-varying flow characteristics such as routes, speed, probability density function of the inter-arrival time between two consecutive aircraft, were determined using ETMS data. The maps are intended to be a predictive tool for traffic flow management in order to anticipate for a given time period how different flows may interact together and to predict which "critical" regions may be subject to possible conflict between aircraft. Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc.
Original languageEnglish (US)
Title of host publicationAIAA Infotech at Aerospace 2010
StatePublished - Dec 16 2010
Externally publishedYes

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