Traffic Volume Analysis and Its Application to Traffic Control Using Point Process Modeling
| Project/Area Number |
18K13846
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 22050:Civil engineering plan and transportation engineering-related
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| Research Institution | Kanazawa University (2021-2022)
Tokyo Institute of Technology (2018-2020) |
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Principal Investigator |
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2021: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 交通量変動 / 点過程 / 時空間相関 / 点過程モデル / 車両到着密度 / 時空間相関構造 / 車両到着頻度 / 対数線型モデル / 非定常分布 / 非線形モデル / 動的変動 |
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| Outline of Final Research Achievements |
The research question of this study was whether modelling vehicle arrival timings on the road as non-aggregate data could lead to new developments in current traffic control methods. The following results were obtained.
First, the previous point process modelling was reviewed and the requirements for its application to traffic volumes were organised. Vehicle arrivals at several vehicle detectors were then modelled as a point process, and spatio-temporal traffic volume fluctuations were described in a unified model. At the same time, in order to improve the consistency of the micro-macroscopic relationship, the time units in which traffic volumes are aggregated and the method for describing the within-day variation of traffic volumes were examined. Also, the method for describing the flow-density relationship was improved.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義は以下にまとめられる。まず、既存の他分野における点過程モデルを整理することで、交通量変動の記述に適用するための見通しを得た。また、対数線形モデルを用いた時空間構造化により、多地点・複数車線での観測データを単一のモデルで統一的に扱う枠組みを構築した。同時に、従来のマクロ交通流理論を発展させることで、ミクロ的分析の結果を実際の制御に反映させる足掛かりを築いた。
本研究の社会的意義は以下に集約される。すなわち、交通量という道路上の最も簡単かつ基礎的な観測データを最大限活用するための数理的な枠組みを提示し、限られた予算の中で効率的な道路運用を行う可能性を示した点である。
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Report
(6 results)
Research Products
(17 results)
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[Presentation] Evaluation of large-scale complete vehicle trajectories dataset on two kilometers highway segment for one hour duration: Zen Traffic Data2021
Author(s)
Seo, T., Tago, Y., Shinkai, N., Nakanishi, M., Tanabe, J., Ushirogochi, D., Kanamori, S., Abe, A., Kodama, T., Yoshimura, S., Ishihara, M., Nakanishi, W.
Organizer
2020 International Symposium on Transportation Data and Modelling
Related Report
Int'l Joint Research
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