Abstract
The development of Information and Communications Technology (ICT) and the Internet provide Intelligent Transport Systems (ITS) with a huge amount of real-time data. These data are the so-called “Big Data” which can be collected, interpreted, managed and analyzed in a proper way in order to improve the knowledge around the transport system. The use of these technologies has greatly enhanced the efficiency and user friendliness of ITS, providing significant economic and social impacts, contributing positively to the management of sustainable mobility.
In this paper, different sources of big data that have been used in ITS are presented, while their advantages and limitations are further discussed. Analytically, big data sources that have been used within the last 10 years are identified. Then, a review of current applications is done, in order to disclose the most used and proper data source per case.
Aim of the present study is to improve the knowledge around the usage of big data in transport planning and to contribute to the better support of ITS, by providing a roadmap to decision makers for big data collection methods.
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This work has been supported by the ALLIANCE project (http://alliance-project.eu/) and has been funded within the European Commission’s H2020 Programme under contract number 692426. This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper.
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Karatsoli, M., Nathanail, E. (2018). A Thorough Review of Big Data Sources and Sets Used in Transportation Research. In: Kabashkin, I., Yatskiv, I., Prentkovskis, O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2017. Lecture Notes in Networks and Systems, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-74454-4_52
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