On the relevance of data science for flight delay research: a systematic review. Issue 4 (4th July 2021)

• Record Type: Journal Article
• Authors: Carvalho, Leonardo; Sternberg, Alice; Maia Gonçalves, Leandro; Beatriz Cruz, Ana; Soares, Jorge A.; Brandão, Diego; Carvalho, Diego; Ogasawara, Eduardo
• Is Part Of: Transport reviews. Volume 41:Issue 4(2021)
• Page Start: 499
• Page End: 528
• Publication Date: 2021-07-04
• Subjects: Flight delay -- data science -- data management -- data analytics -- systematic review; Transportation -- Periodicals; Transportation engineering -- Periodicals; 380.5
• DOI: 10.1080/01441647.2020.1861123
• Languages: English
• ISSNs: 0144-1647

Abstract

ABSTRACT: Flight delays are a significant problem for society as they evenly impair airlines, transport companies, air traffic controllers, facility managers, and passengers. Studying prior flight data is an essential activity for every player involved in the air transportation system. Besides, developing accurate prediction models for flight delays is a crucial component of the decision-making process. Prescribing actions to solve on-going delays is an even challenging task due to the air transportation system complexity. In this regard, this paper presents a thorough literature review of data science techniques used for investigating flight delays. This work proposes a taxonomy and compiles the initiatives used to address the flight delay studies. It also offers a systematic literature review that describes the trends of the field and methods to analyse the applicability of newly proposed methods.