Modeling Congestion Propagation in Multistage Schedule within an Airport Network

Abstract

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.

Analysis of Airport Risk Propagation in Chinese Air Transport Network

“…In recent years, researchers around the world have largely investigated the risk assessment of the civil aviation industry [6] as well as the propagation of single risk factors such as flight delay [7][8][9][10][11], congestion [12][13][14], and aircraft conflicts [15]. Although there has been rich research on assessment and propagation of risk in the civil aviation domain, they mainly focused on the civil aviation macroindustry with less consideration on the network level.…”

“…As for spatial local risk factors, congestion is a representative index in ATN and has attracted more and more attention in recent years [12][13][14].…”

Modeling and optimization of the terminal control area with holding unit

“…In this case, a heterogeneous network model that considers congestion connections/degrees is applied to predict departure flight delays [ 2 , 3 ]. In order to alleviate flight delays, it is also necessary to understand the mechanism of air traffic congestion and its propagation process [ 4 , 5 ]. In this way, the congestion management module can be employed to describe the performance and throughput of the airspace.…”

Study of Flight Departure Delay and Causal Factor Using Spatial Analysis

“…Tu et al [12] employed a smoothing spline model to identify the relationship between seasonal trends, random effects, and daily delay propagation pattern. Delay propagation has also been deeply investigated by many researches to help to understand the air congestion [13][14][15] and alleviate fight delay [16,17]. The effects of day and time were assumed to be additive, and the residuals were assumed to be identically and independently distributed in the study.…”