Big Data Analytics in Intelligent Transportation Systems: A Survey

• Published in: IEEE transactions on intelligent transportation systems Vol. 20; no. 1; pp. 383 - 398
• Main Authors: Zhu, Li, Yu, Fei Richard, Wang, Yige, Ning, Bin, Tang, Tao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytics; Big Data; Big data analytics; Customer information files; Data analysis; Data management; Global Positioning System; Intelligent transportation systems; intelligent transportation systems (ITS); machine learning; Mathematical analysis; Point of sale systems; Public transportation; Rail transportation; Smart cards; Traffic accidents; Traffic accidents & safety; Traffic flow; Traffic planning; Transportation; Transportation management; Transportation services
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2018.2815678

Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.