Development of Hybrid Simulation Model of Air Traffic Management in the Terminal Control Area

Medianto, Rully; Pasaribu, Hisar M.; Muhammad, Hari

doi:10.1088/1757-899x/645/1/012003

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…The simulation model has several advantages in describing the air traffic system and its complexity, i.e. the movement of the aircraft can be visualized to analyze and validate it [19]. The simulation parameters also can be modified easily to obtain various scenarios.…”

Section: √ √mentioning

confidence: 99%

Terminal Control Area Complexity Measurement Using Simulation Model

Medianto

Adinda

Jenie

et al. 2023

IIUMEJ

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Traffic density in the terminal control area will increase flight safety risks. One effort to reduce the risk is to minimize the controller’s workload when affected by air traffic complexity. This research uses a simulation model to measure air traffic complexity in terminal control areas. The aircraft performance model has been constructed from ADS-B data and represents the aircraft movement in the terminal control area of Soekarno-Hatta International Airport. The simulation model can detect and resolve conflicts to keep separations between aircraft at a specified minimum separation limit. Air traffic complexity measurement uses several indicators, i.e., aircraft density, number of climbing and descending aircraft, aircraft type mixing, conflict control, aircraft speed difference, and controller communication. The weighting factor for each indicator has been obtained from Jakarta Air Traffic Service Center (JATSC) controller perception using an analytic hierarchy process. The simulation results show that the variation of resolution type affects the complexity level significantly. The results of this study can be used as consideration for improving air traffic control procedures and air space structures. ABSTRAK: Kepadatan trafik di kawasan terminal kawalan bakal menyebabkan peningkatan risiko keselamatan penerbangan. Salah satu cara bagi mengurangkan risiko adalah dengan meminimumkan beban kerja pengawal yang terlibat dengan kesesakan trafik udara. Kajian ini menggunakan model simulasi bagi mengukur kesesakan trafik udara di kawasan terminal kawalan. Model pretasi pesawat telah dibina menggunakan data ADS-B dan ini mewakili pergerakan pesawat di terminal kawalan lapangan terbang antarabangsa Soekarno-Hatta. Model simulasi ini dapat mengesan konflik dan membuat resolusi bagi mengekalkan penjarakan antara pesawat mengikut had penjarakan minimum yang ditetapkan. Beberapa indikator telah digunakan bagi mengukur kerumitan trafik udara, iaitu: ketumpatan pesawat, bilangan pesawat mendaki dan menurun, jenis pesawat, kawalan konflik, perbezaan kelajuan pesawat dan pengawal komunikasi. Faktor pemberat bagi setiap indikator telah diperoleh daripada pengawal persepsi Pusat Servis Trafik Udara Jakarta (JATSC) menggunakan proses analisis hierarki. Keputusan simulasi menunjukkan pelbagai jenis resolusi mempengaruhi tahap kerumitan dengan ketara. Hasil kajian ini boleh digunakan bagi menambah baik prosedur kawalan trafik udara dan struktur ruang udara.

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Section: √ √mentioning

confidence: 99%

Terminal Control Area Complexity Measurement Using Simulation Model

Medianto

Adinda

Jenie

et al. 2023

IIUMEJ

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Stochastic modeling of aircraft flight parameters in terminal control area based on automatic dependent surveillance-broadcast (ADS-B) data

Medianto

Jusuf

Oktafianto

et al. 2021

IOP Conf. Ser.: Mater. Sci. Eng.

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A critical step in developing good traffic management (ATM) system simulation model is to build a kinematic model of an aircraft movement that can represent the actual conditions. This study aims to obtain flight parameters for aircraft operating in the terminal control area of Soekarno-Hatta International Airport using Automatic Dependent Surveillance-Broadcast (ADS-B) data, which is openly available on Flight Radar24. Flight parameters were measured for several flight phases, such as take-off, initial climb, climb, cruise, descend, and final approach. In addition to these flight phases, flight parameters at waypoints on the arrival and departure were also measured. Furthermore, all flight parameters are modeled stochastically through the probability distribution function (PDF) approach. The best model for each parameter is obtained using the Maximum Likelihood method (MLE) with some relevant Kosmolgrove Smirnov Test criteria. The use of ADS-B data along with the stochastic model presented in this paper provides comprehensive information on flight behavior, which can be further utilized for an aircraft simulation model of an Air Traffic Management system.

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Development of Hybrid Simulation Model of Air Traffic Management in the Terminal Control Area

Cited by 2 publications

References 4 publications

Terminal Control Area Complexity Measurement Using Simulation Model

Terminal Control Area Complexity Measurement Using Simulation Model

Stochastic modeling of aircraft flight parameters in terminal control area based on automatic dependent surveillance-broadcast (ADS-B) data

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