| Project/Area Number |
26420520
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Civil engineering project/Traffic engineering
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| Research Institution | Tokyo Denki University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
屋井 鉄雄 東京工業大学, 環境・社会理工学院, 教授 (10182289)
岩倉 成志 芝浦工業大学, 工学部, 教授 (20223373)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 都市鉄道 / 所要時間信頼性 / 混合分布モデル / 到着分布 / 出発時刻決定行動 / K-meansクラスタ / SVM / 鉄道通勤者 / 鉄道 / 到着時刻分布 / 潜在クラスモデル |
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| Outline of Final Research Achievements |
Recently, decrease in travel time reliability of commuter rail has become a serious issue. Then, an internet survey for railway commuters was conducted and 1000 respondents answered to the questionnaires.
Arrival situation at the destination station was investigated and Kernel density of the difference between desired arrival time and actual arrival time was estimated for each respondent. Respondent was classified according to the similarity of the shape of Kernel density. All respondents were classified into 3 classes. Teacher data for SVM was made for each class. Every respondent was classified into 3 types by SVM.
The departure time decision behavior under the travel time uncertainty was formulated and the buffer time model was estimated by adopting different distributions to each type. As the result, the classification of the respondents and adoption of mixture distribution model were available to estimate travel behavior of railway commuters.
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