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Airport Delay Prediction with Temporal Fusion Transformers

2024-05-14 · Ke Liu, Kaijing Ding, Xi Cheng, Guanhao Xu, Xin Hu, Tong Liu, Siyuan Feng, Binze Cai, Jianan Chen, Hui Lin, Jilin Song, Chen Zhu

Since flight delay hurts passengers, airlines, and airports, its prediction becomes crucial for the decision-making of all stakeholders in the aviation industry and thus has been attempted by various previous research. However, previous delay predictions are often categorical and at a highly aggregated level. To improve that, this study proposes to apply the novel Temporal Fusion Transformer model and predict numerical airport arrival delays at quarter hour level for U.S. top 30 airports. Inputs to our model include airport demand and capacity forecasts, historic airport operation efficiency information, airport wind and visibility conditions, as well as enroute weather and traffic conditions. The results show that our model achieves satisfactory performance measured by small prediction errors on the test set. In addition, the interpretability analysis of the model outputs identifies the important input factors for delay prediction.

📄 PDF Abstract BibTeX arXiv:2405.08293

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Decision Making Prediction

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Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map

2021-05-19 · Wei Shao, Arian Prabowo, Sichen Zhao, Piotr Koniusz 외

To model and forecast flight delays accurately, it is crucial to harness various vehicle trajectory and contextual sensor data on airport tarmac areas. These heterogeneous sensor data, if modelled correctly, can be used …

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2022-07-14 · Yuankai Wu, Hongyu Yang, Yi Lin, Hong Liu

Demystifying the delay propagation mechanisms among multiple airports is fundamental to precise and interpretable delay prediction, which is crucial during decision-making for all aviation industry stakeholders. The prin…

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Aeolus: A Multi-structural Flight Delay Dataset

2025-10-30 · Lin Xu, Xinyun Yuan, Yuxuan Liang, Suwan Yin 외 arxiv

We introduce Aeolus, a large-scale Multi-modal Flight Delay Dataset designed to advance research on flight delay prediction and support the development of foundation models for tabular data. Existing datasets in this dom…

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