Show simple item record

dc.contributor.authorLiu, S
dc.contributor.authorZhang, J
dc.contributor.authorGuo, H
dc.contributor.authorThe 6th ENRI International Workshop on ATM/CNS
dc.date.accessioned2020-11-17T11:04:39Z
dc.date.available2020-11-17T11:04:39Z
dc.date.issued2019-10-31
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/68363
dc.description.abstractTo improve operational efficiency and facilitate decision support in the air traffic management domain, a method is proposed to evaluate the air traffic steadiness in arrival operations, referring to the quality of arrival traffic that is steady--regular as well as unvarying, in addition, focusing on two aspects: the smoothness of intervals of flight time & distance between arrivals on final and the coherence of arrival trajectories. Firstly, the intervals of flight time & distance between arrivals when reaching 1,000ft on final are counted, then both qualitative and quantitative analyses are applied to explore the distribution form, parameter characteristics, and statistical data for illustrating the performance. Secondly, two sub-methods are used in terms of the coherence of trajectories: on the one hand, research the similarity between the arrival trajectories simplified by Douglas-Peucker algorithm and standard terminal arrival routes based on the vertical distance to show the degree of STARs’ execution; on the other hand, cluster trajectories based on multiple features through DBSCAN algorithm to detect outliers, reflecting the uniformity of trajectories between each other. Finally, taking a typical Chinese airport into account, a case study comparing the performance of two periods is carried out to validate the provided methods.en_US
dc.publisherElectronic Navigation Research Instituteen_US
dc.subjectAir Traffic Steadinessen_US
dc.subjectStatistical Analysisen_US
dc.subjectTrajectory Clusteringen_US
dc.subjectInterval Smoothnessen_US
dc.subjectTrajectory Coherenceen_US
dc.titleEvaluation of Air Traffic Steadiness in Arrival Operations based on Statistical Analysis and Trajectories Clusteringen_US
dc.typeConference Proceedingen_US
dc.rights.holder© 2019 The Author(s)
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.publisher-urlhttps://www.enri.go.jp/eiwac/eiwac_2019_eng.htmlen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record