Recent applications of big data analytics in railway transportation systems: A survey. (May 2018)

• Record Type: Journal Article
• Authors: Ghofrani, Faeze; He, Qing; Goverde, Rob M.P.; Liu, Xiang
• Is Part Of: Transportation research. Volume 90(2018)
• Page Start: 226
• Page End: 246
• Publication Date: 2018-05
• Subjects: Survey -- Big data -- Data analytics -- Railway transportation systems; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2018.03.010
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Survey studies of big data analytics in railway transportation. Apply a content analysis methodology to conduct the review. Classify the studies in three areas: Maintenance, Operations, Safety. Classify the studies with three levels: descriptive, predictive, and prescriptive. Identify the research gaps and directions. Abstract: Big data analytics (BDA) has increasingly attracted a strong attention of analysts, researchers and practitioners in railway transportation and engineering. This urges the necessity for a review of recent research development in this field. This survey aims to provide a comprehensive review of the recent applications of big data in the context of railway engineering and transportation by a novel taxonomy framework, proposed by Mayring (2003). The survey covers three areas of railway transportation where BDA has been applied, namely operations, maintenance and safety. Also, the level of big data analytics, types of big data models and a variety of big data techniques have been reviewed and summarized. The results of this study identify the existing research gaps and thereby directions of future research in BDA in railway transportation systems.