幹線鉄道の臨時列車運行計画の策定支援にむけた日・時間帯単位の需要波動の予測手法

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: 2020/10/01

タイトル(英語): Forecasting Method of Long-Distance Rail Passenger Demand Fluctuations by Day/Time to Support Extra Train Transport Service Planning

著者名: 松本　涼佑（公益財団法人鉄道総合技術研究所），奥田　大樹（公益財団法人鉄道総合技術研究所），深澤　紀子（公益財団法人鉄道総合技術研究所）

著者名(英語): Ryosuke Matsumoto (Railway Technical Research Institute), Daiki Okuda (Railway Technical Research Institute), Noriko Fukasawa (Railway Technical Research Institute)

キーワード: 独立成分分析，時系列分析，需要波動，臨時列車　independent component analysis，time series analysis，demand fluctuation，extra train

要約(英語): A train schedule in Japan includes regular trains which is fixed on annual basis and pre-planned extra trains whose operation dates are not predetermined. Accordingly, in order to provide efficient transport services, a plan for the daily operation of extra trains must be established based on accurate passenger demand fluctuations forecasts by day/time. Therefore, we developed a method to forecast for the demand fluctuation by day/time on a certain day in the future. The method was developed by combining several fundamental waves, which are extracted by applying independent component analysis to actual ridership records with calendar information, and information on events which was held in target areas. We confirmed that the method has high accuracy by verifying its reproducibility and forecasting accuracy. In addition, the extra trains' operation planning system, which implements the forecasting method, can estimate the load factor of all trains between stations on the planning schedule based on the forecasted demand fluctuations. Then, the system can suggest an optimal extra trains' operation plan based on these values. We estimated the load factor based on forecasted demand fluctuations with the system, and we verified its accuracy. As a result, we confirmed that we can estimate the load factor with high accuracy.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.140 No.10 （2020） 特集：IoT時代を支えるスマートファシリティ関連技術

本誌掲載ページ: 769-781 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/140/10/140_769/_article/-char/ja/