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Paper Abstract and Keywords
Presentation 2020-12-11 14:20
Prediction of Train Delays at Stations Using Convolutional Neural Networks with Actual Operation Data
Tsukasa Takahashi, Takumi Fukuda, Sei Takahashi (Nihon Univ.), Hideo Nakamura (The Univ. of Tokyo) DC2020-63
Abstract (in Japanese) (See Japanese page) 
(in English) Trains in the metropolitan area have high congestion rates during rush hours. Congestion causes delays, and there is a lot of research and countermeasures to mitigate the delays. In order to evaluate the effect of the countermeasure against delay, we need to evaluate the delays before and after the countermeasures. When the evaluation is done by simulation, it is necessary to predict the delays according to the driving conditions. We defined a series to facilitate the extraction of features from the actual operation data, and used a convolutional neural network to learn the features, and obtained the highest prediction accuracy of 67.1% for Station I.
Keyword (in Japanese) (See Japanese page) 
(in English) Delay resolution / Delay improvement / Train delay / Operation management / Machine learning / Convolutional neural network / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 288, DC2020-63, pp. 23-26, Dec. 2020.
Paper # DC2020-63 
Date of Issue 2020-12-04 (DC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee DC  
Conference Date 2020-12-11 - 2020-12-11 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To DC 
Conference Code 2020-12-DC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Prediction of Train Delays at Stations Using Convolutional Neural Networks with Actual Operation Data 
Sub Title (in English)  
Keyword(1) Delay resolution  
Keyword(2) Delay improvement  
Keyword(3) Train delay  
Keyword(4) Operation management  
Keyword(5) Machine learning  
Keyword(6) Convolutional neural network  
Keyword(7)  
Keyword(8)  
1st Author's Name Tsukasa Takahashi  
1st Author's Affiliation Nihon University (Nihon Univ.)
2nd Author's Name Takumi Fukuda  
2nd Author's Affiliation Nihon University (Nihon Univ.)
3rd Author's Name Sei Takahashi  
3rd Author's Affiliation Nihon University (Nihon Univ.)
4th Author's Name Hideo Nakamura  
4th Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
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Speaker Author-1 
Date Time 2020-12-11 14:20:00 
Presentation Time 20 minutes 
Registration for DC 
Paper # DC2020-63 
Volume (vol) vol.120 
Number (no) no.288 
Page pp.23-26 
#Pages 4 
Date of Issue 2020-12-04 (DC) 

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