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Spatiotemporal traffic network analysis: technology and applications

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Abstract

The rapid development of intelligent transportation systems and the emergence of the sharing economy have given rise to vast amounts of spatiotemporal data. Consequently, spatiotemporal traffic network analysis has become a crucial approach to traffic managers in traffic control, route guidance, traffic policy adjustment, and transportation network planning. This study provides a comprehensive survey of recent developments in spatiotemporal traffic network analysis and reviews the latest research ranging from 2000 to 2016. This paper focuses on overall methods and general characteristics involved in traffic network analysis. First, we introduce some potential applications of spatiotemporal traffic network analysis. Second, we discuss data sources and corresponding pretreatment methods. Then, we investigate various existing methodologies to examine the state of the art in traffic network analysis. At the end of this survey, we provide more detailed discussions on future research challenges and new research points.

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Acknowledgements

Our deepest gratitude goes to the anonymous reviewers for their careful work and thoughtful suggestions that have helped improve this paper substantially. And also, special gratitude goes to the editors and staffs of the journal, thanks for all your understanding, patience and guidance during the whole process; we are very grateful for your contributions on this paper.

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  1. School of Economics and Management, Beijing Jiao Tong University, Beijing, China

    Huiyu Zhou

  2. IPS Research Center, Waseda University, Kitakyushu, Japan

    Kotaro Hirasawa

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  1. Huiyu Zhou
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  2. Kotaro Hirasawa
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Correspondence to Huiyu Zhou.

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This work was supported by the National Natural Science Foundation of China [Grant No. 61602028]. Beijing philosophy and social science program [Grant No. 15JGC166], and the Fundamental Research Funds for the Central Universities [Grant No. 2015jbwy007].

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Zhou, H., Hirasawa, K. Spatiotemporal traffic network analysis: technology and applications. Knowl Inf Syst 60, 25–61 (2019). https://doi.org/10.1007/s10115-018-1225-7

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