実績列車駅停車時間に基づいた機械学習による駅出発遅延時間予測手法の検討

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2024/08/01

タイトル(英語): An Examination of Machine Learning Methods for Predicting Station Departure Delay Time Based on Actual Stopping Time Data of Trains at Stations

著者名: 福田　卓海（日本大学理工学部），佐藤　駿一（日本大学理工学部），高橋　聖（日本大学理工学部），中村　英夫（日本大学理工学部）

著者名(英語): Takumi Fukuda (College of Science and Technology, Nihon University), Shuniti Sato (College of Science and Technology, Nihon University), Sei Takahashi (College of Science and Technology, Nihon University), Hideo Nakamura (College of Science and Technology, Nihon University)

キーワード: 電気鉄道，機械学習，遅延予測，スケジューリング，シミュレータ　　electric railroad，machine learning，delay prediction，scheduling，simulator

要約(英語): In the urban railways of the metropolitan area, train delays during morning rush hours have become a significant issue. This problem isn't merely caused by large, sudden delays, but also by an accumulation of minor delays, which can escalate into substantial setbacks. This presents a disadvantage not only for the operators managing the train services but also for the users. Recent years have seen active reporting of studies predicting delay times. However, these studies do not take into account the accumulative nature of delays because the data input to the learning machine is only for stations behind the target station. Therefore, this paper aims to predict the delay time that occurs when each train departs from a station. To do so, we constructed a network that takes into account the propagation of delays by using data from stations in front of the target station as input. We will provide an overview of the network we constructed and report on its predictive accuracy.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.8 （2024） 特集Ⅰ：Smart Cityを支える高度な無線通信，センシング及び情報処理　特集Ⅱ：人と人とを繋ぐ情報・システム技術

本誌掲載ページ: 831-837 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/ieejeiss/144/8/144_831/_article/-char/ja/