Simulation Tool for Estimation of Air Traffic Distribution

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00377601" target="_blank" >RIV/68407700:21260/24:00377601 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.23919/NTCA60572.2024.10517846" target="_blank" >https://doi.org/10.23919/NTCA60572.2024.10517846</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23919/NTCA60572.2024.10517846" target="_blank" >10.23919/NTCA60572.2024.10517846</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Simulation Tool for Estimation of Air Traffic Distribution

Popis výsledku v původním jazyce

This paper deals with the development of a software tool for visualization of current and predicted future air traffic. The software, implemented in the Python programming language, uses real air traffic data from the OpenSky Network that represents the general air traffic situation for further understanding of the distribution of aircraft over European airspace. The methodology includes clustering of initial air traffic data sets using various clustering algorithms and the Gaussian mixture model to generate or remove aircraft from air traffic that allows users to increase and decrease air traffic based on their needs, for example following the air traffic forecast, and observe the generated air traffic distribution enabled by the visualization. This work contributes to advancements in analyzing and visualizing the evolution of air traffic and enables simulations in different areas of Air Traffic Management where forecasting future air traffic is crucial.

Název v anglickém jazyce

Simulation Tool for Estimation of Air Traffic Distribution

Popis výsledku anglicky

This paper deals with the development of a software tool for visualization of current and predicted future air traffic. The software, implemented in the Python programming language, uses real air traffic data from the OpenSky Network that represents the general air traffic situation for further understanding of the distribution of aircraft over European airspace. The methodology includes clustering of initial air traffic data sets using various clustering algorithms and the Gaussian mixture model to generate or remove aircraft from air traffic that allows users to increase and decrease air traffic based on their needs, for example following the air traffic forecast, and observe the generated air traffic distribution enabled by the visualization. This work contributes to advancements in analyzing and visualizing the evolution of air traffic and enables simulations in different areas of Air Traffic Management where forecasting future air traffic is crucial.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

New Trends in Civil Aviation: Proceedings of the 24th International Conference on New Trends in Civil Aviation 2024

ISBN

978-80-01-07181-6

ISSN

2694-7854

e-ISSN

—

Počet stran výsledku

6

Strana od-do

165-170

Název nakladatele

České vysoké učení technické v Praze

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

25. 4. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001223424800033