Priority rules as a concept for the usage of scarce airport capacity

Grunewald, Erik; Knabe, Franz; Rudolph, Florian; Schultz, Michael

doi:10.1016/j.trpro.2017.12.037

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…These resources could be physical, as e.g. new runways or more air traffic controllers; but also virtual, like granting priority to flights at them landing [59], [60]. In both cases, delays at these airports will be reduced, causing a disruption in the propagation process and an improvement of the overall dynamics.…”

Section: Results: Delay Propagation Networkmentioning

confidence: 99%

Assessing Granger Causality on Irregular Missing and Extreme Data

Zanin

2021

IEEE Access

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The Granger test is one of the best known techniques to detect causality relationships among time series, and has been used uncountable times in science and engineering. The quality of its results strongly depends on the quality of the underlying data, and different approaches have been proposed to reduce the impact of, for instance, observational noise or irregular sampling. Less attention has nevertheless been devoted to situations in which the analysed time series are irregularly polluted with missing and extreme values. In this contribution I tackle this problem by comparing four different data pre-processing strategies and evaluating their performance with synthetic time series, both in dyadic tests and functional network contexts. I further apply these strategies to a real-world problem, involving inferring the structure behind the propagation of delays in an air transport system. Finally, some guidelines are provided on when and how these strategies ought to be used.

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Section: Results: Delay Propagation Networkmentioning

confidence: 99%

Assessing Granger Causality on Irregular Missing and Extreme Data

Zanin

2021

IEEE Access

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“…Many topics have been studied in ATFM area to guarantee the safety and efficiency of aviation network operations. These studies focus on the optimization of air conflict resolution [6], airspace or sector traffic and capacity management [7], runway scheduling [8][9][10], ground-delay program [11], etc. Airport slot allocation is an important one of these topics in ATFM.…”

Section: Literature Reviewmentioning

confidence: 99%

A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity

Wang

Zhao

2020

Sustainability

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Serious congestion and delay problems exist in most of the busiest airports worldwide because of imbalance between scarce airport slot resources and increasing traffic demand. Various factors, especially weather conditions, exacerbate the demand–capacity imbalance. This paper presents a robust model for simultaneous slot allocation on an airport network in multiple calendar days, considering airport capacity uncertainty. The idea of robust optimization is conducive to sustainable and stable decision-making. Robustness is represented through reducing the potential scheduling conflicts in the worst case. Then the model links the strategic decisions and pre-tactical decisions in air traffic management (ATM) through the tradeoff between strategic discrepancy cost and operational congestion cost. Under the support of the Cplex solver, numerical analyses are taken to validate the characteristics and effectiveness of the proposed model. The results show that the proposed model effectively eliminates the existing and potential scheduling conflicts, and makes effective tradeoffs between airline preference and potential airport congestion risk.

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“…Current research in the field of flight and airport operations addresses economic, operational and ecological efficiency [9][10][11][12][13][14][15][16][17][18][19][20][21][22]. As presented above, the propagation of delay in the network is paramount when assessing the impact of congestion [23,24].…”

Section: Introductionmentioning

confidence: 99%

Weather Impact on Airport Performance

et al. 2018

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Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic management airport performance weather algorithm, which aims to quantify weather conditions at airports based on aviation routine meteorological reports. Our results are computed from a data set of 20.5 million European flights of 2013 and local weather data. A methodology is presented to evaluate the impact of weather events on the airport performance and to select the appropriate threshold for significant weather conditions. To provide an efficient method to capture the impact of weather, we modelled departing and arrival delays with probability distributions, which depend on airport size and meteorological impacts. These derived airport performance scores could be used in comprehensive air traffic network simulations to evaluate the network impact caused by weather induced local performance deterioration.

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Priority rules as a concept for the usage of scarce airport capacity

Cited by 3 publications

References 3 publications

Assessing Granger Causality on Irregular Missing and Extreme Data

Assessing Granger Causality on Irregular Missing and Extreme Data

A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity

Weather Impact on Airport Performance

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