Air transportation delay propagation analysis with uncertainty in coloured–timed Petri nets

Author:

Shao Quan1ORCID,Xu Chenchen2

Affiliation:

1. Associate Professor, College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China (corresponding author: )

2. Graduate Student, College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China

Abstract

In the transport management of aviation networks, uncertain factors and delay propagation are two main sources of flight delays. However, the impacts of uncertainty and the degree of delays are difficult to calculate empirically in daily operations. In this paper, a novel delay propagation model is introduced utilising the mathematical modelling tool coloured–timed Petri nets. This model enables descriptions of the delay propagation progress and flight delay calculation under the influence of uncertain factors. In order to understand the influence of airline network operations with uncertainties, the mechanisms of the main uncertainties (weather factors, air traffic control (ATC) factors and other low-probability random factors) are studied and probability functions are obtained. To simulate conditions under different uncertainties, experiments were carried out on an aviation network comprising 13 airports under different settings of bad weather and ATC. The simulation results revealed the influence of different uncertain factors, delay propagation time through flight chains and delay prediction in the aviation network. Based on the predicted flight delays, flight sequence update rules were established, which showed that the updated flight sequence significantly reduced flight delays compared with the original flight sequence.

Publisher

Thomas Telford Ltd.

Subject

Transportation,Civil and Structural Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Flight delay propagation modeling: Data, Methods, and Future opportunities;Transportation Research Part E: Logistics and Transportation Review;2024-05

2. Modeling and adaptive control of demand oscillation propagation in an uncertain aerial transportation network;OPSEARCH;2024-03-02

3. A Flight Arrival Time Prediction Method Based on Cluster Clustering-Based Modular With Deep Neural Network;IEEE Transactions on Intelligent Transportation Systems;2023

4. Evaluation of Airport Size and Delay Causal Factor Effects on Delay Propagation Dissipation;Transportation Research Record: Journal of the Transportation Research Board;2021-11-17

5. Editorial;Proceedings of the Institution of Civil Engineers - Transport;2020-12

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