Abstract
Most Koreans have mobile and their location information is collected based on location of the base station in one second increments. Mobile base stations are installed at intervals of 50 m in cities, and up to 2 km apart in rural areas. We developed an algorithm that builds an individual trip chain using mobile base station data and distinguishes home from work area by analyzing daily traffic patterns. The purpose of this study is to analyze traffic generation unit and traffic characteristics through seamless trip chain analysis of individual mobile base station data. A new method and experimental approach are established to estimate the passenger O/D based on mobile base station data. A new method has been analyzed to overcome many of the shortcomings of the existing O/D estimation methods that are based on household surveys, such as zero cells and inaccuracy due to low sampling rates.
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Acknowledgments
This research was supported by a grant (#20TLRP-B148659-03: Development of Future Transport Operation Technology based on Big Data & AI) from Transportation & Logistics Research Program (TLRP) funded by the Ministry of Land, Infrastructure and Transport of Korean government.
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Kim, J., Kim, D. (2020). Traffic Behavior Analysis Using Mobile Base Station Data. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_8
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DOI: https://doi.org/10.1007/978-3-030-50943-9_8
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