Towards a greener Extended-Arrival Manager in air traffic control: A heuristic approach for dynamic speed control using machine-learned delay prediction model

Lim, Zhi Jun; Alam, Sameer; Dhief, Imen; Schultz, Michael

doi:10.1016/j.jairtraman.2022.102250

Cited by 19 publications

(7 citation statements)

References 9 publications

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“…These timelines of the CLC work steps would then provide a ground truth against which the results of the proposed method could be compared based on temporal distribution and consistency. The similarity function (1) proposed in Section 5.5 could be used to assess the similarity between the ground truth and the timeline of work phases inferred by the model for an ATCO. This evaluation procedure could be repeated in a leave-one-participant-out fashion.…”

Section: Comparing Extracted Work Phases With the Clc Stepsmentioning

confidence: 99%

“…Air Traffic Management (ATM) is currently progressing rapidly toward automation and digitalisation assistance to support the ATCO. Examples are AI-supported decision-making, which helps en-route ATCOs to solve conflicts or the Arrival Manager, proposing an inbound sequence of arriving movements, and many more that come along with remote tower technologies [1,2]. Automation has the purpose of relieving the ATCO from workload or decreasing uncertainty in the work quality by addressing a sub-task.…”

Section: Introductionmentioning

confidence: 99%

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Extraction of CD&R Work Phases from Eye-Tracking and Simulator Logs: A Topic Modelling Approach

et al. 2023

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Automation in Air Traffic Control (ATC) is gaining an increasing interest. Possible relevant applications are in automated decision support tools leveraging the performance of the Air Traffic Controller (ATCO) when performing tasks such as Conflict Detection and Resolution (CD&R). Another important area of application is in ATCOs’ training by aiding instructors to assess the trainees’ strategies. From this perspective, models that capture the cognitive processes and reveal ATCOs’ work strategies need to be built. In this work, we investigated a novel approach based on topic modelling to learn controllers’ work patterns from temporal event sequences obtained by merging eye movement data with data from simulation logs. A comparison of the work phases exhibited by the topic models and the Conflict Life Cycle (CLC) reference model, derived from post-simulation interviews with the ATCOs, indicated that there was a correspondence between the phases captured by the proposed method and the CLC framework. Another contribution of this work is a method to assess similarities between ATCOs’ work strategies. A first proof-of-concept application targeting the CD&R task is also presented.

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Section: Comparing Extracted Work Phases With the Clc Stepsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extraction of CD&R Work Phases from Eye-Tracking and Simulator Logs: A Topic Modelling Approach

et al. 2023

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“…A review of different approaches to flight delay prediction and how this problem is addressed is presented in [20]. They compare the prediction models used, such as operational research [21], machine learning [22], Bayesian network approach [23], probabilistic models, statistical analysis, a super statistical approach [24] and ensemble methods and select representative algorithms [25]. A novel predictive model applying graphs to sequence learning architecture is studied in [26].…”

Section: State Of the Artmentioning

confidence: 99%

Estimating the Volatility of Flights and Risk of Saturation of Airspaces in the European Core Area: A Methodological Proposal

Galarraga,

Abadie,

Standfuss

et al. 2023

Applied Sciences

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Despite having some fluctuations and the impact of the COVID-19 crisis, the demand for flights had a general growing trend for the past years. As the airspace is limited, efforts to better manage the total number of flights are noteworthy. In addition, volatility (i.e., unpredicted changes) in the number of flights has been observed to be increasing. Efforts to improve flight forecasting are thus necessary to improve air traffic efficiency and reduce costs. In this study, volatility in the number of flights is estimated based on past trends, and the outcomes are used to project future levels. This enables risk situations such as having to manage unexpectedly high numbers of flights to be predicted. The methodological approach analyses the Functional Airspace Block of Central Europe (FABEC). Based on the number of flights for 2015–2019, the following are calculated: historic mean, variance, volatility, 95th percentile, flights per hour and flights per day of the week in different time zones in six countries. Due to the nature of air traffic and the overdispersion observed, this study uses counting data models such as negative binomial regressions. This makes it possible to calculate risk measures including expected shortfall (ES) and value at risk (VaR), showing for each hour that the number of flights can exceed planned levels by a certain number. The study finds that in Germany and Belgium at 13:00 h there is a 5% worst-case possibility of having averages of 683 and 246 flights, respectively. The method proposed is useful for planning under uncertainties. It is conducive to efficient airspace management, so risk indicators help Air Navigation Service Providers (ANSPs) to plan for low-probability situations in which there may be large numbers of flights.

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“…Because of sequence optimization, waiting times, the associated flown distances, fuel consumption, and emissions are reduced. An analysis of the impact of these concepts on the environment and cost-efficiency was conducted for Free Route airspace in [20,21], and for AMAN/DMAN in [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Preliminary Impact Assessment of the Ad Hoc Separation Minima: A New Separation Mode

Serrano-Mira,

Sanz,

Pérez-Castán

et al. 2024

Applied Sciences

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A major challenge for the Air Traffic Management system is the need to boost airspace capacity, which is near saturation in some situations. Separation minima are one of the factors related to airspace capacity, and the SESAR program promotes research into advanced separation modes. Ad Hoc separation, a novel separation mode, involves applying different pairwise separation minima in the same volume of airspace depending on a set of factors, such as encounter geometry, aircraft models, and flight level, among others. This research examines the impact of implementing this concept in different en-route scenarios. The goal is to determine whether applying this concept proves advantageous or, conversely, results in an increase in the complexity of the system without significant benefits in the key performance areas of capacity, environment, and cost-efficiency. Fast Time Simulations are conducted in RAMS software, with the concept being implemented in the LECMZMU, LECMTLU, and LECMDGU sectors of the Madrid ACC. The results reveal favorable capacity outcomes with increases of around 2% and the LECMZMU sector exhibits the most significant environmental and cost-efficiency benefits. Furthermore, implementing the Ad Hoc concept in a larger scenario could yield even greater environmental and cost-efficiency benefits.

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Towards a greener Extended-Arrival Manager in air traffic control: A heuristic approach for dynamic speed control using machine-learned delay prediction model

Cited by 19 publications

References 9 publications

Extraction of CD&R Work Phases from Eye-Tracking and Simulator Logs: A Topic Modelling Approach

Extraction of CD&R Work Phases from Eye-Tracking and Simulator Logs: A Topic Modelling Approach

Estimating the Volatility of Flights and Risk of Saturation of Airspaces in the European Core Area: A Methodological Proposal

Preliminary Impact Assessment of the Ad Hoc Separation Minima: A New Separation Mode

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