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決定木を用いた運転士の遅延回復運転の分析

決定木を用いた運転士の遅延回復運転の分析

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カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2018/11/01

タイトル(英語): Analysis of Delay Recovery Operation of Railway Drivers using Decision Trees

著者名: 落合 康文(小田急電鉄(株)),増間 義樹(千葉工業大学情報科学部情報工学科),富井 規雄(千葉工業大学情報科学部情報工学科)

著者名(英語): Yasufumi Ochiai (Odakyu Electric Railway Co., Ltd.), Yoshiki Masuma (Department of Computer Science, Chiba Institute of Technology), Norio Tomii (Department of Computer Science, Chiba Institute of Technology)

キーワード: 列車遅延,遅延対策指標,遅延対策箇所の抽出手法  train delay,drivers' operation,decision tree

要約(英語): In railways where trains run densely, once a delay occurs, the delay easily propagates to other trains. In order to make their timetables more robust, railway companies are taking various steps. However, to date they have not been interested in the analysis of drivers' operation, although this factor is closely related with the robustness. It would be useful to know the difference between “good driving”, which reduces delay and “poor driving”, which increases delay so that we can give advice to drivers for improvement of their driving. We have developed an algorithm to find the factors that differentiate between “good” and “poor” driving based on the decision tree. The inputs of our algorithm are track occupation records. The algorithm receives “good” examples and “poor” examples as the input, and then produces a decision tree from which we can determine the dominant factors to differentiate between the good examples and the poor examples. We have applied our algorithm to actual data and found a driving pattern that is common to poor drivers. Then based on the results, we improved signaling systems and learned that we succeeded in improving the robustness of the timetable.

本誌: 電気学会論文誌D(産業応用部門誌) Vol.138 No.11 (2018)

本誌掲載ページ: 877-883 p

原稿種別: 論文/日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/138/11/138_877/_article/-char/ja/

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