https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Bruggemann_McFadyen_2018aBruggemann McFadyen 2018a - Revision history2026-04-30T18:47:42ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Bruggemann_McFadyen_2018a&diff=192831&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 586872130 to Bruggemann McFadyen 2018a2021-01-28T18:15:24Z<p>Scipediacontent moved page <a href="/public/Draft_Content_586872130" class="mw-redirect" title="Draft Content 586872130">Draft Content 586872130</a> to <a href="/public/Bruggemann_McFadyen_2018a" title="Bruggemann McFadyen 2018a">Bruggemann McFadyen 2018a</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Bruggemann_McFadyen_2018a&diff=192830&oldid=prevScipediacontent: Created page with " == Abstract == This paper introduces the concept of network design for an Unmanned Traffic Management (UTM) system. First, data-driven air traffic modelling and analysis is..."2021-01-28T18:15:20Z<p>Created page with " == Abstract == This paper introduces the concept of network design for an Unmanned Traffic Management (UTM) system. First, data-driven air traffic modelling and analysis is..."</p>
<p><b>New page</b></p><div><br />
== Abstract ==<br />
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This paper introduces the concept of network design for an Unmanned Traffic Management (UTM) system. First, data-driven air traffic modelling and analysis is used to define feasible low-level urban airspace regions suitable to embed the network. Second, a modified k-centres approach is used to define candidate network node locations by considering the geographical coverage of typical unmanned aircraft operations expected in urban areas. Third, k-nearest neighbours and graph theory concepts are used to define an Unmanned Traffic Network (UTN) structure that attempts to maximise coverage without impacting existing manned air traffic operations. The approach is applied to Brisbane, Australia and is the first known attempt to realistically model the spatial structure of an Unmanned Traffic Network.<br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [https://eprints.qut.edu.au/113185/1/itsc2017conf_utmstruct_ds.pdf https://eprints.qut.edu.au/113185/1/itsc2017conf_utmstruct_ds.pdf]<br />
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* [http://xplorestaging.ieee.org/ielx7/8307147/8317580/08317690.pdf?arnumber=8317690 http://xplorestaging.ieee.org/ielx7/8307147/8317580/08317690.pdf?arnumber=8317690],<br />
: [http://dx.doi.org/10.1109/itsc.2017.8317690 http://dx.doi.org/10.1109/itsc.2017.8317690]<br />
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* [https://eprints.qut.edu.au/113185 https://eprints.qut.edu.au/113185],<br />
: [https://dblp.uni-trier.de/db/conf/itsc/itsc2017.html#McFadyenB17 https://dblp.uni-trier.de/db/conf/itsc/itsc2017.html#McFadyenB17],<br />
: [https://qa-eprints.qut.edu.au/113185 https://qa-eprints.qut.edu.au/113185],<br />
: [https://core.ac.uk/display/132565451 https://core.ac.uk/display/132565451],<br />
: [https://academic.microsoft.com/#/detail/2790316077 https://academic.microsoft.com/#/detail/2790316077]</div>Scipediacontent