Automatic Detection of Flight Maneuvers with the Use of Density-based Clustering Algorithm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F18%3A00322802" target="_blank" >RIV/68407700:21260/18:00322802 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21460/18:00322802

Result on the web

<a href="http://dx.doi.org/10.1109/NTAD.2018.8551680" target="_blank" >http://dx.doi.org/10.1109/NTAD.2018.8551680</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/NTAD.2018.8551680" target="_blank" >10.1109/NTAD.2018.8551680</a>

Result language

angličtina

Original language name

Automatic Detection of Flight Maneuvers with the Use of Density-based Clustering Algorithm

Original language description

Ever-changing situation in the aviation demands a change in flight training programs that would reflect present needs and threats in contrary to the traditional training that didn’t changed much for decades. Therefore, new alternative training concepts have been developed that cover these needs. However, these concepts do not apply to initial training which seem to be a crucial phase of a pilot training. Thus, the aim was to create a software solution that would identify individual flight maneuvers and evaluate them so that the overall evaluation would be done by considering objective evaluation and flight instructors’ subjective expertise. A study was done with strictly given flight schedules. For the purpose of automatic maneuver detection, density-based spatial clustering of applications with noise – DBSCAN clustering algorithm was used, which could determine maneuvers and thus exclude the noise from clusters of maneuvers. The results indicate that the proposed solution was able to identify the prescribed maneuvers with high sensitivity. The solution could be extended in the future to identify all flight maneuvers considering as many parameters from flight data recorder as possible and thus carry out complete objectively based pilot performance evaluation.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of New Trends in Aviation Development 2018. The XIII. International Scientific Conference

ISBN

978-1-5386-7918-0

ISSN

—

e-ISSN

—

Number of pages

5

Pages from-to

82-86

Publisher name

Czechoslovakia Section IEEE

Place of publication

Prague

Event location

Košice

Event date

Aug 30, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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