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  •   University of Thessaly Institutional Repository
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  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
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Exploring the Big Data Usage in Transport Modelling

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Author
Tzika-Kostopoulou D., Nathanail E.
Date
2021
Language
en
DOI
10.1007/978-3-030-61075-3_107
Keyword
Smart cards
Literature survey
Research challenges
Research interests
Special applications
Transport modelling
Transport planning
Transport systems
Travel demand modelling
Big data
Springer Science and Business Media Deutschland GmbH
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Abstract
Continuous growth of information and the increasing volume of data with high coverage in space and time open up new possibilities in the field of transport planning. In recent years, there is great research interest in how big data can be applied to the modelling and planning of transport systems. A literature survey of existing methodologies and applications of big dada in transportation is a useful tool for identifying strengths and capabilities for big data exploitation in different fields of application. The main objective of this paper is to provide a comprehensive overview of big data usage in transport planning, focusing on travel demand modelling. More specifically, the paper aims to examine whether analyzing big data can facilitate transport planning and to summarize the relative scientific discussion. Three big data sources have been examined: smart cards, mobile phones and social networks. Existing theories and studies are presented and classified according to the source of data, the methodology, the extracted transportation features and the validation of results. In the course of the review, the different big data sources are further analyzed regarding their special applications in the transport planning field. Finally, the paper concludes by presenting the barriers and gaps in the existing approaches as well as new research challenges. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
URI
http://hdl.handle.net/11615/80252
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