基于自校正因果推理的航班延误时空预测方法

IF 7.9 1区 工程技术 Q1 ENGINEERING, CIVIL IEEE Transactions on Intelligent Transportation Systems Pub Date : 2024-11-01 DOI:10.1109/TITS.2024.3443261
Qihui Zhu;Shenwen Chen;Tong Guo;Yisheng Lv;Wenbo Du
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引用次数: 0

摘要

准确的航班延误预测对空中交通系统的安全有效运行至关重要。机场间关系建模的最新进展为研究多机场情景下的航班延误预测提供了一种很有前途的方法。然而,以往的预测工作只考虑了交通流量或地理距离等简单的关系,忽视了机场之间复杂的相互作用,因此被证明是不充分的。在本文中,我们利用随机推理来精确建模机场间关系,并提出了一种用于航班延误预测的自校正时空图神经网络(名为CausalNet)。具体而言,设计格兰杰因果推理与自校正模块相结合,构建机场之间的因果图,并根据当前机场的延误情况对因果图进行动态修改。此外,自适应提取因果图的特征,并利用其来解决机场的异质性问题。对中国最繁忙的前74个机场的真实数据进行了广泛的实验。结果表明,CausalNet优于基线。消融研究强调了所提出的自校正因果图和图特征提取模块的功能。所有这些都证明了所提出方法的有效性。
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A Spatio-Temporal Approach With Self-Corrective Causal Inference for Flight Delay Prediction
Accurate flight delay prediction is crucial for the secure and effective operation of the air traffic system. Recent advances in modeling inter-airport relationships present a promising approach for investigating flight delay prediction from the multi-airport scenario. However, the previous prediction works only accounted for the simplistic relationships such as traffic flow or geographical distance, overlooking the intricate interactions among airports and thus proving inadequate. In this paper, we leverage casual inference to precisely model inter-airport relationships and propose a self-corrective spatio-temporal graph neural network (named CausalNet) for flight delay prediction. Specifically, Granger causality inference coupled with a self-correction module is designed to construct causality graphs among airports and dynamically modify them based on the current airport’s delays. Additionally, the features of the causality graphs are adaptively extracted and utilized to address the heterogeneity of airports. Extensive experiments are conducted on the real data of top-74 busiest airports in China. The results show that CausalNet is superior to baselines. Ablation studies emphasize the power of the proposed self-correction causality graph and the graph feature extraction module. All of these prove the effectiveness of the proposed methodology.
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来源期刊
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems 工程技术-工程:电子与电气
CiteScore
14.80
自引率
12.90%
发文量
1872
审稿时长
7.5 months
期刊介绍: The theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS). Intelligent Transportation Systems are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds. The scope of this interdisciplinary activity includes the promotion, consolidation and coordination of ITS technical activities among IEEE entities, and providing a focus for cooperative activities, both internally and externally.
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Table of Contents Corrections to “Toward Infotainment Services in Vehicular Named Data Networking: A Comprehensive Framework Design and Its Realization” IEEE Intelligent Transportation Systems Society Information IEEE INTELLIGENT TRANSPORTATION SYSTEMS SOCIETY Scanning the Issue
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