Flight delay propagation modeling: Data, Methods, and Future opportunities

Chi Li, Jianfeng Mao, Lingyi Li, Jingxuan Wu, Lianmin Zhang, Jianyu Zhu and Zibin Pan

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 185, issue C

Abstract: Persistent flight delays have continually posed a substantial challenge within the aviation sector. These delays infiltrate the air transportation network, precipitating disruptions to schedules and negatively impacting operational efficiency, passenger satisfaction, environmental considerations, and economic performance. Over the years, numerous methods have been developed for modeling flight delay propagation; however, a systematic review that encapsulates and synthesizes these approaches remains absent. This paper endeavors to examine the literature pertaining to flight delay propagation modeling, culminating in salient observations for future research potential. Initially, a comprehensive taxonomy framework is presented for delay propagation modeling. An extensive elucidation of data sources and application scenarios for various data types, two primary modeling perspectives, and an in-depth evaluation of seven modeling methods follows, accompanied by their characteristics and suitable application scopes. Subsequently, current research trends are summarized, and future research opportunities for modeling methods and research questions are detailed, establishing a solid foundation for continued exploration. The conclusions derived from these findings are anticipated to equip researchers, practitioners, and policymakers in the aviation industry with augmented comprehension of flight delay propagation patterns, thereby empowering them to prioritize resource allocation while enhancing overall system performance.

Keywords: Flight delay; Delay propagation; Graph neural networks; Queueing models; Complex networks; Bayesian networks (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103525

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