Relationship between airport congestion and at-gate delay

Wang, P.T.R.; Tene, Noam; Wojcik, Leonard A.

doi:10.1109/dasc.2002.1067926

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…The distributions of both the fixed and variable delays across flights at an airport constitutes a unique kind of airport delay "signature" that distinguished different airports. papers [7,6] in that we separate explicitly the fvted (controllable) components fkom the variable (random) components, and that a simpler and symmetric delay propagation equation is used for both amvals and departures. This paper goes beyond our previous two…”

Section: Discussionmentioning

confidence: 99%

Flight connections and their impacts on delay propagation

Wang

Schaefer

Wojcik

2003

22nd Digital Avionics Systems Conference Proceedings (Cat No 03CH37449) DASC-03

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The authors present a simple analytic model that explicitly separates the controllable factors that influence delays and propagation of delays in the National Airspace System (NAS) from those factors that are random variables in a given scenario. In this paper, the controllable type of factor will be called "futed and the random type of factor will be called "variable." Simple relationships exist among the fixed and variable factors that characterize NAS delay propagation. We show how the model can be applied to better understand delay propagation from specific NAS airports, especially the effects of flight schedule parameters on measured delay. Recorded data from actual NAS operations are used to derive estimates on key model parameters and to show how delay characteristics vary among different airports.

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Section: Discussionmentioning

confidence: 99%

Flight connections and their impacts on delay propagation

Wang

Schaefer

Wojcik

2003

22nd Digital Avionics Systems Conference Proceedings (Cat No 03CH37449) DASC-03

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“…As an important location for the outfow and infow of air trafc, the AS operation has various constraints, such as release time, available apron, and runway assignment, which cause trafc congestion. Studies on the trafc congestion on ASs have mainly focused on the queuing problem connecting the apron, taxiway, and runway [1][2][3]; fight delays [4][5][6][7]; and taxiing management [8][9][10]. Yang et al discussed the congestion of departing trafc fow but ignored the infuence of arriving trafc fow [11].…”

Section: Introductionmentioning

confidence: 99%

Ground-Air Traffic Congestion Propagation Model Based on Hierarchical Control Interdependent Network

Jiang

Zhang

Dai

2023

Journal of Advanced Transportation

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A multilayer network approach to model and analyze air traffic networks is proposed. These networks are viewed as complex systems with interactions between airports, airspaces, procedures, and air traffic flows (ATFs). A topology-based airport-airspace network and a flight trajectory network are developed to represent critical physical and operational characteristics. A multilayer traffic flow network and an interrelated traffic congestion propagation network are also formulated to represent the ATF connection and congestion propagation dynamics, respectively. Furthermore, a set of analytical metrics, including those of airport surface (AS), terminal controlled airspace (TCA), and area-controlled airspace (ACA), is introduced and applied to a case study in central and south-eastern China. The empirical results show the existence of a fundamental diagram of the airport, terminal, and intersections of air routes. Moreover, the dynamics and underlying mechanisms of congestion propagation through the AS-TCA-ACA network are revealed and interpreted using the classical susceptible-infectious-removed model in a hierarchical network. Finally, a high propagation probability among adjacent terminals and a high recovery probability are identified at the network system level. This study provides analytical tools for comprehending the complex interactions among air traffic systems and identifies future developments and automation of layered coupled air traffic management systems.

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“…Therefore, airport flight delay per hour as a result of exceeding the hourly operational capacity can be seen as the congested flights, the temporal variation of which reveals their evolution. The other indices for congestion are queuing and queuing time [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Modeling Congestion Propagation in Multistage Schedule within an Airport Network

Dai

Tian

et al. 2018

Journal of Advanced Transportation

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In order to alleviate flight delay it is important to understand how air traffic congestion evolves or propagates. In this context, this paper focusses on the aggravation of airport congestion by the accumulation of delayed departure flights. We start by applying a heterogeneous network model that takes congestion connection/degree into consideration to predict departure congestion clusters. This is on the basis of the fact that, from a micro perspective, the connection between congestion and discrete clusters can be embodied in models. However, the results show prediction to be of high accuracy and time consuming due to the complexities in capturing the connection in congested flights. The problem of being highly time consuming is resolved in this paper by improving the models by stages. Stage partitioning based on the variation of delay clusters is similar to the typical infectious cycle. For heterogeneous networks the model can describe the congestion propagation and its causes at the different stages of operation. If the connection between flights is homogeneous, the model can describe a more indicative process or trend of congestion propagation. In particular, for single source congestion, the simplified multistage models enable short-term prediction to be fast. Furthermore, for the controllers, the accuracy of prediction using simplified models can be acceptable and the speed on the prediction is significantly increased. The simplified models can help controllers to understand congestion propagation characteristics at different stages of operation, make a fast and short-term prediction of congestion clusters, and facilitate the formulation of traffic control strategies.

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Relationship between airport congestion and at-gate delay

Cited by 3 publications

References 5 publications

Flight connections and their impacts on delay propagation

Flight connections and their impacts on delay propagation

Ground-Air Traffic Congestion Propagation Model Based on Hierarchical Control Interdependent Network

Modeling Congestion Propagation in Multistage Schedule within an Airport Network

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