Estimation Method of Traffic Volume Using Big-Data

  • Kazuki Someya
  • Ryozo KiyoharaEmail author
  • Masashi Saito
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1036)


Traffic jams have recently become a significant problem in provincial cities that tend to have poor railway services in Japan. Therefore, the main means of transportation are public buses, taxies, and private vehicles. Moreover, traffic accidents and road construction sites frequently block traffic. It is therefore difficult to estimate the travelling time from the origin to destination in real-time. To estimate the travelling time, we must predict the behaviors of many vehicles that depend on an “origin to destination” (OD) traffic volume. In our previous study, we proposed an estimation method for OD traffic volume using two types of big data, a road traffic census and mobile spatial statistics. In this study, we evaluated our proposed method on various situations through a traffic simulation.



This work was supported by JSPS KAKENHI Grant No. 16K00433. Data on the Mobile Spatial Statistics in Kanazawa and Nonoichi were provided by NTT DoCoMo.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Graduate School of Kanagawa Institute of TechnologyAtsugiJapan
  2. 2.Kanagawa Institute of TechnologyAtsugiJapan
  3. 3.Kanazawa Institute of TechnologyNonoichiJapan

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