| Project/Area Number |
16K16356
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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 |
Social systems engineering/Safety system
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| Research Institution | Chuo University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2019: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 最適化 / 公共交通 / 時刻表設計 / 時空間ネットワーク / 停車駅 / 混雑緩和 / 路線計画 / 列車運行計画 / バス時刻表 / バス時刻表設計 / 公共交通活性化 / ネットワーク |
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| Outline of Final Research Achievements |
The aim of this research is to design public transport by utilizing optimization techniques. The time-space network represents timetables of trains/buses and behavior of passengers. We can express the time-dependent behavior of each passenger by computing flows in the time-space network. We have proposed several mathematical models for timetable design and line planning by using the time-space network. The target areas are Iwate, Shizuoka, Kochi, and Tokyo. We have demonstrated the utility of our models by numerical experiments with the large-scale time-space networks. We have also presented a mathematical model to estimates the number of customers stopping by a kiosk by analyzing purchase behavior of train commuters at kiosks in stations.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究では，時空間ネットワークと最適化理論を融合することで，鉄道・バスの路線や時刻表の利便性をさらに高めることを目指している．対象地域の実際の時刻表データから時空間ネットワークを構築して大規模な数値実験を行い，対象地域の路線や時刻表を詳細に分析して改善すべき点を明らかにし，最適化手法を用いてより利便性の高い路線や時刻表を設計するモデルを提案した．最適化モデルでは，時空間ネットワークをはじめとする数理モデルを用いることで不便さの度合いや改善の度合いを定量化し，それらに基づいて目的関数を定めた．また，駅構内売店の購買行動分析を行い，交通分野とマーケティング分野をつなぐデータ分析の有用性を示した．
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