Abstract
Transportation systems in mega-cities play a very important role in social and economic activities. Especially in Japan, the Tokyo city is strongly required to increase resiliency and safety of its transportation systems, because of the 2020 Olympic games and big earthquakes predicted to occur. Our research group is trying to address those challenges utilizing mobility big data. We have been archiving several mobility data sets, such as smart card data and vehicle recorder data, and developed platforms for processing, analyzing, and visualizing them. In this paper I briefly introduce our analysis and visualization of passenger flows in public transportation systems and behaviors of vehicle drivers.
This paper includes joint work with Daisaku Yokoyama, Masahiko Itoh, and Masaru Kitsuregawa (Institute of Industrial Science, the University of Tokyo). Yoshimitsu Tomita and Satoshi Kawamura (Tokyo Metro Co. Ltd.).
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References
Itoh, M., Yokoyama, D., Toyoda, M., Kitsuregawa, M.: Visual interface for exploring caution spots from vehicle recorder big data. In: Proceedings of the IEEE BigData 2015 (2015)
Itoh, M., Yokoyama, D., Toyoda, M., Tomita, Y., Kawamura, S., Kitsuregawa, M.: Visual fusion of mega-city big data: an application to traffic and tweets data analysis of metro passengers. In: Proceedings of the IEEE BigData 2014, pp. 431–440 (2014)
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Toyoda, M. (2015). Mobility Big Data Analysis and Visualization (Invited Talk). In: Kumar, N., Bhatnagar, V. (eds) Big Data Analytics. BDA 2015. Lecture Notes in Computer Science(), vol 9498. Springer, Cham. https://doi.org/10.1007/978-3-319-27057-9_8
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DOI: https://doi.org/10.1007/978-3-319-27057-9_8
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