Time-series analysis and prediction of OD traffic volume using ETC data

Origin-Destination (OD) traffic volume data are expected to improve the performance of traffic simulators by providing more precise demand input, which can support efficient traffic management and operation. This study analyzed the temporal fluctuation of OD traffic volume in the whole Tokyo metropo...

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Bibliographic Details
Published inSEISAN KENKYU Vol. 74; no. 1; pp. 101 - 106
Main Authors SHITAMA, Takahiro, ITOSHIMA, Fumihiro, XING, Jian, TORIUMI, Azusa, SUDO, Hajime, ZHANG, Jiahua, TANIUE, Nobuyuki, OGUCHI, Takashi
Format Journal Article
LanguageEnglish
Published Institute of Industrial Science The University of Tokyo 01.02.2022
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ISSN0037-105X
1881-2058
DOI10.11188/seisankenkyu.74.101

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Summary:Origin-Destination (OD) traffic volume data are expected to improve the performance of traffic simulators by providing more precise demand input, which can support efficient traffic management and operation. This study analyzed the temporal fluctuation of OD traffic volume in the whole Tokyo metropolitan expressway network using electronic toll collection (ETC) data in 7 months. Specifically, by applying the state space model, traffic volume hourly fluctuation in a day and daily fluctuation in a week were extracted for each OD pair. A prediction model of OD traffic volume based on these fluctuations was proposed. The temporal fluctuation patterns and their proportions in specific OD pair groups were further investigated using hierarchical clustering.
ISSN:0037-105X
1881-2058
DOI:10.11188/seisankenkyu.74.101