| Project/Area Number |
26820208
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Civil engineering project/Traffic engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
XU YONGWEI 東京大学, 空間情報科学研究センター, 特任研究員 (10726897)
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| Project Period (FY) |
2014-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 人の流れ / データ同化 / Kalman filter / データ復元 / 人の流れモデル |
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| Outline of Final Research Achievements |
This study introduced a novel assimilation method for reconstructing people flow in areas that are partially invisible to sensors. In contrast to traditional individual-based analysis, we consider pedestrians as a whole entity by incorporating dynamic continuum flow theory and demonstrating how it is applied in our kernel-function-based model of people flow density. The proposed method integrates the Kalman filter algorithm with an additional Laplace smoothing constraint, which significantly boosts the accuracy and stability of the algorithm. Under coverage about 40% of the invisible areas, the similarity of reconstructed people flow density for the real tracking data, showed that the estimated density in the invisible area is acceptably close to the true value.
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