Air traffic controllers' practical part of basic training on computer based simulation device

Pavlinović, Mira; Juričić, Biljana; Antulov-Fantulin, Bruno

doi:10.23919/mipro.2017.7973554

Cited by 7 publications

(5 citation statements)

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“…The process of ATC training involves at least three people: a trainee, an instructor and a pseudo-pilot (17) . The simulation circuit consists of an ATC trainee workstation and pseudo-pilot workstations connected to the system manager, in which all airspace and air traffic data and communication settings are stored (Fig.…”

Section: Methodsmentioning

confidence: 99%

ATCO radar training assessment and flight efficiency: the correlation between trainees’ scores and fuel consumption in real-time simulations

et al. 2020

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Air traffic controller training is highly regulated but lacks prescribed common assessment criteria and methods to evaluate trainees at the level of basic training and consideration of how trainees in fluence flight efficiency. We investigated whether there is a correlation between two parameters, viz. the trainees’ assessment score and fuel consumption, obtained and calculated after real-time human-in-the-loop radar simulations within the ATCOSIMA project. Although basic training assessment standards emphasise safety indicators, it was expected that trainees with higher assessment scores would achieve better flight efficiency, i.e. less fuel consumption. However, the results showed that trainees’ assessment scores and fuel consumption did not correlate in the expected way, leading to several conclusions.

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Section: Methodsmentioning

confidence: 99%

ATCO radar training assessment and flight efficiency: the correlation between trainees’ scores and fuel consumption in real-time simulations

et al. 2020

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“…The volume and complexity of these communications can vary greatly depending on factors such as the airspace conditions and seasonal fluctuations, with ATCos often facing increased workloads during peak travel seasons [25]. As such, ATCo trainees must be prepared to handle high-stress and complex airspace situations through a combination of intensive training and simulation exercises with human simulation-pilots [33]. In addition to mastering the technical aspects of air traffic control, ATCo trainees must also develop strong communication skills, as they are responsible for ensuring clear and precise communication with pilots at all times.…”

Section: Virtual Simulation-pilot Systemmentioning

confidence: 99%

“…Due to the crucial aspect of ATC, efforts have been made to develop simulation interfaces for their training [33][34][35]. Previous works includes optimization of the training process [36], post-evaluation of each training scenario [37,38], and virtual simulation-pilot implementation, for example, a deep learning (DL)-based implementation [39].…”

Section: Virtual Simulation-pilot Systemmentioning

confidence: 99%

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

et al. 2023

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In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken communications from ATCo trainees, and it performs automatic speech recognition and understanding. Thus, it goes beyond only transcribing the communication and can also understand its meaning. The output is subsequently sent to a response generator system, which resembles the spoken read-back that pilots give to the ATCo trainees. The overall pipeline is composed of the following submodules: (i) an automatic speech recognition (ASR) system that transforms audio into a sequence of words; (ii) a high-level air traffic control (ATC)-related entity parser that understands the transcribed voice communication; and (iii) a text-to-speech submodule that generates a spoken utterance that resembles a pilot based on the situation of the dialogue. Our system employs state-of-the-art AI-based tools such as Wav2Vec 2.0, Conformer, BERT and Tacotron models. To the best of our knowledge, this is the first work fully based on open-source ATC resources and AI tools. In addition, we develop a robust and modular system with optional submodules that can enhance the system’s performance by incorporating real-time surveillance data, metadata related to exercises (such as sectors or runways), or even a deliberate read-back error to train ATCo trainees to identify them. Our ASR system can reach as low as 5.5% and 15.9% absolute word error rates (WER) on high- and low-quality ATC audio. We also demonstrate that adding surveillance data into the ASR can yield a callsign detection accuracy of more than 96%.

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“…Controllers are responsible for the safe, expeditious, and orderly flow of air traffic in aerodromes and airspaces (Bakare, & Junaidu, 2013;Malakis et al, 2019;Mooji, & Corker, 2002;Pavlinovic, Juricic, & Antulov-Fantulin, 2017). Controllers must ensure that all aircraft, including UAVs, fly safely and without any issues in airspace.…”

Section: Introductionmentioning

confidence: 99%

Air Traffic Controllers' Perspectives on Unmanned Aerial Vehicles Integration into Non-Segregated Airspace

Tuncal

2024

Journal of Aviation

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The integration of Unmanned Aerial Vehicles (UAVs) into non-segregated airspace presents both opportunities and challenges for air traffic control (ATC). The aim of the study is to explore the perspectives of air traffic controllers on the current and anticipated challenges, workload, stress factors, performance errors, and mitigation strategies related to UAV integration. The sample consisted of 213 air traffic controllers in Türkiye. UAV operations have been available in Türkiye not only for military purposes but also for purposes such as forest fires, earthquakes, security, and others for a long time, and these UAV operations are provided with air traffic services (ATS) by air traffic controllers. The results show that air traffic controllers are concerned about mid-air collisions due to UAV technology limits and regulatory gaps, along with managing risks and unique flight characteristics. Addressing technology limitations, regulatory ambiguity, and other factors necessitates a comprehensive strategy. Solutions must prioritize collision avoidance systems, clear communication guidelines, and defined no-fly zones. It is recommended that future studies focus on the comprehensive impact of UAVs on air traffic operations and the development of regulations.

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Air traffic controllers' practical part of basic training on computer based simulation device

Cited by 7 publications

References 0 publications

ATCO radar training assessment and flight efficiency: the correlation between trainees’ scores and fuel consumption in real-time simulations

ATCO radar training assessment and flight efficiency: the correlation between trainees’ scores and fuel consumption in real-time simulations

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Air Traffic Controllers' Perspectives on Unmanned Aerial Vehicles Integration into Non-Segregated Airspace

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