A Spatial, Temporal Complexity Metric for Tactical Air Traffic Control

Wee, Hong Jie; Lye, Sun Woh; Pinheiro, Jean-Philippe

doi:10.1017/s0373463318000255

Cited by 17 publications

(9 citation statements)

References 11 publications

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“…The complexity is related with the closure angle and time of flight as indicated by aircraft speed (Hilburn, 2004), as well as by location and time to form a ‘flight shape profile’ of future trajectory (Wee et al, 2018). Another study by Wee et al (2019) attempted to measure the complexity of a dynamic airspace using the eye-tracking method and develop a framework for it by syncing the raw eye data and the raw radar data involving aircraft position and label data.…”

Section: Literature Reviewmentioning

confidence: 99%

EEG-Based Analysis of Air Traffic Conflict: Investigating Controllers’ Situation Awareness, Stress Level and Brain Activity during Conflict Resolution

et al. 2019

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The effects of air traffic conflict geometry have been well investigated in prior studies, particularly in the context of the pilot, though little in the context of the air traffic control officer (ATCO). No study to date has investigated the effects of conflict geometry on human factors variables of ATCOs through objective and physiological approaches. This study examines the effects of conflict geometries on ATCO situation awareness, stress level and brain activity during conflict resolution. Fifteen participants were instructed to resolve six different conflict geometries: crossing level, crossing non-level, converging level, converging non-level, overtaking level, and overtaking non-level. The results indicate that converging and crossing conflicts led to lower situation awareness (SA), higher stress level, and higher theta activation at the temporal and parietal lobes. Level conflict led to lower SA. The findings offer two implications, providing insights for the formal guidelines in ATC conflict resolution training and provision of inputs for the conflict resolution aid development.

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Section: Literature Reviewmentioning

confidence: 99%

EEG-Based Analysis of Air Traffic Conflict: Investigating Controllers’ Situation Awareness, Stress Level and Brain Activity during Conflict Resolution

et al. 2019

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“…Some complexity models which use expert ATCO knowledge are described in [8][9][10][11][12][13][14][15][16][17]. Other models which use complexity indicators are based on mathematical or statistical methods (e.g., [18][19][20][21][22][23][24][25]). On one hand, the latter make the development of the model easier since it is difficult to acquire ATCO input.…”

Section: Air Traffic Complexity Models and Indicatorsmentioning

confidence: 99%

Defining Terminal Airspace Air Traffic Complexity Indicators Based on Air Traffic Controller Tasks

Jurinić,

Juričić,

Antulov-Fantulin

et al. 2024

Aerospace

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This paper focuses on terminal air traffic complexity indicators. By thorough analysis of previous research, the benefits and limitations of the existing terminal complexity models are identified. According to these findings, a new approach for determining terminal air traffic complexity indicators is proposed which assumes that terminal complexity could be determined based on approach air traffic controller (ATCO) tasks. The comprehensive list of general approach ATCO tasks was defined using a literature review and observation of training exercises, forming the basis for subsequent expert group workshops which enabled the acquisition of ATCOs’ knowledge data. Through these workshops, new approach ATCO tasks were additionally identified, and terminal complexity indicators were defined with airspace and traffic parameters. These new tasks and indicators present a novelty in this field of research since they incorporate ATCOs’ knowledge as the data input and consider various traffic scenarios, all types of traffic, weather conditions, and off-nominal situations.

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“…Besides, Wang et al [14] proposed a complex networks based method to describe air traffic complexity and elaborate its evolutionary laws. Wee et al [15] developed a dynamic tactical complexity model, Conflict Activity Level, by establishing an overall score for an entire region or sub-regions of interest.…”

Section: Overall Frameworkmentioning

confidence: 99%

Establishing the Correlation Between Complexity and Performance for Arrival Operations

Zhang

Xiang

Zhou

et al. 2022

PROMTT

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Air traffic complexity indicators play an essential role in measuring operational performance and controller workload. However, current studies mainly depend on the manual scoring method to scale performance or workload. This paper focuses on arrival operations and presents a data-driven strategy to establish the correlation between complexity and performance to avoid the subjectivity of the currently used manual scoring method. Firstly, we present twenty-six indicators for describing air traffic complexity and two indicators for arrival operational performance. Secondly, the clustering method distinguishes peak and off-peak situations for arrival operation. Moreover, clustering results are compared to investigate the correlation between complexity and performance initially. Thirdly, the classification method is adopted to determine such correlation further. In addition, we also identify the affecting factors which could influence operational performance. Finally, trajectories of arrival aircraft landing at Guangzhou Baiyun International Airport (ZGGG) are used for case validation. The results indicate that there is a strong correlation between complexity and performance. The accuracy and precision of classification are approximately 90%. Furthermore, the number of aircraft significantly impacts the arrival operational performance within TMA.

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A Spatial, Temporal Complexity Metric for Tactical Air Traffic Control

Cited by 17 publications

References 11 publications

EEG-Based Analysis of Air Traffic Conflict: Investigating Controllers’ Situation Awareness, Stress Level and Brain Activity during Conflict Resolution

EEG-Based Analysis of Air Traffic Conflict: Investigating Controllers’ Situation Awareness, Stress Level and Brain Activity during Conflict Resolution

Defining Terminal Airspace Air Traffic Complexity Indicators Based on Air Traffic Controller Tasks

Establishing the Correlation Between Complexity and Performance for Arrival Operations

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