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Systemization of reconstruction method for secure and open people flow depending on types of CDRs data

Research Project

Project/Area Number 16H03119
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Social systems engineering/Safety system
Research InstitutionThe University of Tokyo

Principal Investigator

Sekimoto Yoshihide  東京大学, 生産技術研究所, 准教授 (60356087)

Co-Investigator(Kenkyū-buntansha) 金杉 洋  東京大学, 空間情報科学研究センター, 特任研究員 (00526907)
瀬戸 寿一  東京大学, 空間情報科学研究センター, 特任講師 (80454502)
Project Period (FY) 2016-04-01 – 2019-03-31
Project Status Completed (Fiscal Year 2018)
Budget Amount *help
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2018: ¥6,630,000 (Direct Cost: ¥5,100,000、Indirect Cost: ¥1,530,000)
Fiscal Year 2017: ¥7,150,000 (Direct Cost: ¥5,500,000、Indirect Cost: ¥1,650,000)
Fiscal Year 2016: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Keywords人流データ / パーソントリップデータ / オープンデータ / 強化学習 / 人流 / GPSデータ / 携帯通信データ / 精度検証 / 社会システム / 人の流動 / 携帯電話 / 位置情報 / 地理情報システム(GIS) / 交通工学・国土計画 / 情報通信工学
Outline of Final Research Achievements

Understanding people flow at a citywide level is critical for urban planning and commercial development. However, high cost and severe privacy policy constraints still complicate utilization of these data in practice. There is no dataset that
anyone can freely access, use, modify, and share for any purpose. To tackle this problem, we propose a novel dataset creation approach (called Open PFLOW) that continuously reports the spatiotemporal positions of all individual’s in urban areas based on open data. With fully consideration of the privacy protection, each entity in our dataset does not match the actual movement of any real person, so that the dataset can be totally open to public as part of data infrastructure. We evaluate the accuracy of the dataset by comparing it with commercial datasets and traffic census indicates that it has a high correlation with mesh population and link-based traffic volume.

Academic Significance and Societal Importance of the Research Achievements

近年、携帯電話等を活用した人々の流動に関する高精度なデータがあるものの、これらは高価なものであり、広く使うのは一般的に難しかった。しかし、Open PFLOWデータセットにより、無償で色々な人が使えることによって、広く人の流動データを使ってもらうことが可能である。

Report

(4 results)
  • 2018 Annual Research Report   Final Research Report ( PDF )
  • 2017 Annual Research Report
  • 2016 Annual Research Report
  • Research Products

    (11 results)

All 2018 2017 2016

All Journal Article (4 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 4 results,  Open Access: 1 results) Presentation (6 results) (of which Int'l Joint Research: 6 results,  Invited: 1 results) Book (1 results)

  • [Journal Article] Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas2017

    • Author(s)
      Takehiro Kashiyama, Yanbo Pang, and Yoshihide Sekimoto
    • Journal Title

      Transportation Research Part C.

      Volume: 85 Pages: 249-267

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Modeling and reproducing human daily travel behavior from GPS data: A Markov Decision Process approach2017

    • Author(s)
      Yanbo Pang, Kota Tsubouchi, Takahiro Yabe and Yoshihide Sekimoto
    • Journal Title

      The 1st International Workshop on Prediction of Human Mobility (PredictGIS 2017) in conjunction with the SIGSPATIAL2017

      Volume: 1 Pages: 8-8

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Human Mobility Estimation Following Massive Disaster Using Filtering Approach2016

    • Author(s)
      Akihito Sudo, Takehiro Kashiyama, Takahiro Yabe, Hiroshi Kanasugi, and Yoshihide Sekimoto
    • Journal Title

      Journal of Disaster Research

      Volume: 11 Issue: 2 Pages: 217-224

    • DOI

      10.20965/jdr.2016.p0217

    • NAID

      130007673655

    • ISSN
      1881-2473, 1883-8030
    • Year and Date
      2016-03-01
    • Related Report
      2016 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Real-Time Prediction of People’s Movement under Disaster Situations using Particle Filter2016

    • Author(s)
      矢部 貴大, 関本 義秀, 樫山 武浩, 金杉 洋, 須藤 明人
    • Journal Title

      JSTE Journal of Traffic Engineering

      Volume: 2 Issue: 2 Pages: A_19-A_27

    • DOI

      10.14954/jste.2.2_A_19

    • NAID

      130005125366

    • ISSN
      2187-2929
    • Related Report
      2016 Annual Research Report
    • Peer Reviewed
  • [Presentation] Replicating Urban Dynamics by Generating Human-like Agents from Smartphone GPS Data2018

    • Author(s)
      Yanbo Pang, Kota Tsubouchi, Takahiro Yabe, Yoshihide Sekimoto
    • Organizer
      The 26th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018)
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Deep Reinforcement Learning Approach for Train Rescheduling Utilizing Graph Theory2018

    • Author(s)
      Mitsuaki Obara, Takehiro Kashiyama and Yoshihide Sekimoto
    • Organizer
      The Workshop of IEEE International Conference on Big Data (IEEE Big Data 2018)
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Prediction of mass people movement from agent model and observation data2017

    • Author(s)
      Yoshihide Sekimoto
    • Organizer
      1st Workshop on Prediction of Human Mobility (PredictGIS 2017) in conjunction with SIGSPATIAL2017
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Particle Filter for Real-time Human Mobility Prediction following Unprecedented Disaster2016

    • Author(s)
      Akihito Sudo, Takehiro Kashiyama, Takahiro Yabe, Hiroshi Kanasugi, Xuan Song, Tomoyuki Higuchi, Shin'Ya Nakano, Masaya Saito and Yoshihide Sekimoto
    • Organizer
      The 24th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2016)
    • Place of Presentation
      サンフランシスコ,米国
    • Year and Date
      2016-11-01
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] A Framework for Evacuation Hotspot Detection after Large Scale Disasters using Location Data from Smartphones: Case Study of Kumamoto Earthquake2016

    • Author(s)
      Takahiro Yabe, Kota Tsubouchi, Akihito Sudo and Yoshihide Sekimoto
    • Organizer
      The 24th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2016)
    • Place of Presentation
      サンフランシスコ,米国
    • Year and Date
      2016-11-01
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Estimating Evacuation Hotspots using GPS data: What happened after the large earthquakes in Kumamoto, Japan?2016

    • Author(s)
      Takahiro Yabe, Kota Tsubouchi, Akihito Sudo and Yoshihide Sekimoto
    • Organizer
      The 5th International Workshop on Urban Computing (UrbComp 2016) in conjunction with the 22th ACM SIGKDD 2016
    • Place of Presentation
      サンフランシスコ,米国
    • Year and Date
      2016-08-13
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Book] 岩波データサイエンス(特集:地理空間情報処理)2016

    • Author(s)
      岩波データサイエンス刊行委員会編
    • Total Pages
      12
    • Publisher
      岩波書店
    • Related Report
      2016 Annual Research Report

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Published: 2016-04-21   Modified: 2020-03-30  

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