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A Gaussian process based decision support tool for air-traffic management

A Gaussian process based decision support tool for air-traffic management
A Gaussian process based decision support tool for air-traffic management
Technological developments in the last decade have shifted challenges in traffic flow management from obtaining and storing data, to analysing and presenting the enormous amount of available trajectory data in a comprehensible manner.
This paper introduces a novel approach to visualising air-traffic, shifting the focus from displaying traffic density, towards directly visualising the flight corridors used by air-traffic.

Such an approach is suitable for visualising air-traffic in three dimensions, which is particularly helpful in the vicinity of an airport where the air-traffic often changes level.

Furthermore, the approach is data-driven, allowing the comparison of multiple trajectory datasets in order to identify changes in traffic corridors related to changing air-traffic and weather conditions.

Finally, by using the probabilistic nature of the approach, it is possible to quantify the air-traffic complexity in terms of the traffic structure.

The results presented in this paper show the approach applied to a trajectory dataset as measured by ground-radar near Denver airport (DEN).
Data-driven, Trajectory analysis, information visualisation, Visual analytics
American Institute of Aeronautics and Astronautics
Eerland, Willem
7f5826c3-536f-4fdc-955e-0f9870c96a0e
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Eerland, Willem
7f5826c3-536f-4fdc-955e-0f9870c96a0e
Box, Simon
2bc3f3c9-514a-41b8-bd55-a8b34fd11113
Fangohr, Hans
9b7cfab9-d5dc-45dc-947c-2eba5c81a160
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b

Eerland, Willem, Box, Simon, Fangohr, Hans and Sobester, Andras (2017) A Gaussian process based decision support tool for air-traffic management. In 17th AIAA Aviation Technology, Integration, and Operations Conference: AIAA AVIATION Forum. American Institute of Aeronautics and Astronautics. 16 pp . (doi:10.2514/6.2017-4264).

Record type: Conference or Workshop Item (Paper)

Abstract

Technological developments in the last decade have shifted challenges in traffic flow management from obtaining and storing data, to analysing and presenting the enormous amount of available trajectory data in a comprehensible manner.
This paper introduces a novel approach to visualising air-traffic, shifting the focus from displaying traffic density, towards directly visualising the flight corridors used by air-traffic.

Such an approach is suitable for visualising air-traffic in three dimensions, which is particularly helpful in the vicinity of an airport where the air-traffic often changes level.

Furthermore, the approach is data-driven, allowing the comparison of multiple trajectory datasets in order to identify changes in traffic corridors related to changing air-traffic and weather conditions.

Finally, by using the probabilistic nature of the approach, it is possible to quantify the air-traffic complexity in terms of the traffic structure.

The results presented in this paper show the approach applied to a trajectory dataset as measured by ground-radar near Denver airport (DEN).

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More information

Accepted/In Press date: 3 May 2017
e-pub ahead of print date: 5 June 2017
Published date: 2017
Keywords: Data-driven, Trajectory analysis, information visualisation, Visual analytics
Organisations: Aeronautics, Astronautics & Comp. Eng, Computational Engineering & Design Group, Civil Maritime & Env. Eng & Sci Unit, Transportation Group, Education Hub

Identifiers

Local EPrints ID: 408419
URI: http://eprints.soton.ac.uk/id/eprint/408419
PURE UUID: 6eca2592-a1f3-4150-83f7-19d1909fd149
ORCID for Willem Eerland: ORCID iD orcid.org/0000-0002-4559-6122
ORCID for Hans Fangohr: ORCID iD orcid.org/0000-0001-5494-7193
ORCID for Andras Sobester: ORCID iD orcid.org/0000-0002-8997-4375

Catalogue record

Date deposited: 20 May 2017 04:03
Last modified: 25 Oct 2023 01:40

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Contributors

Author: Willem Eerland ORCID iD
Author: Simon Box
Author: Hans Fangohr ORCID iD
Author: Andras Sobester ORCID iD

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