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Paper Abstract and Keywords
Presentation 2020-01-31 10:00
[Poster Presentation] Preliminary study on time series forecasting of road traffic at multiple locations for applying to traffic congestion mitigation with adaptive vehicle speed control
Satoshi Watanabe, Ryusei Aiura, Hiroaki Morino (SIT) SeMI2019-107
Abstract (in Japanese) (See Japanese page) 
(in English) We previously proposed a method to solve a traffic jam early by carrying out an appropriate speed control of a vehicle running behind congested vehicle platoon at a place where natural traffic congestion is likely to occur, such as the highway sag. In this method, it is important to detect the occurrence of congested vehicle platoon as early as possible by some means. In this paper, we report a basic study on a method to predict the congestion time at a location in real time by time series forecasting using velocity data collected at two locations including the target location and its downstream one. Here, we assume distance between two locations is relatively small (Approximately 1 km). As a prediction technique to deal with multiple time series data, we focus on VAR (Vector Auto-regression model) which is one of the autoregressive models and multivariate LSTM (Long Short Time Memory). Evaluation results using velocity data obtained by traffic flow simulation with actual highway vehicle data show that both methods achieve the same level of prediction accuracy, and that the prediction accuracy is improved in comparison with the case of predicting only from one time series data (In this case, the past time series data of the point to be predicted) using AR model and univariate LSTM.
Keyword (in Japanese) (See Japanese page) 
(in English) Sag sections / Time series prediction / Machine Learning / VAR / LSTM / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 406, SeMI2019-107, pp. 43-44, Jan. 2020.
Paper # SeMI2019-107 
Date of Issue 2020-01-23 (SeMI) 
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 SeMI  
Conference Date 2020-01-30 - 2020-01-31 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SeMI 
Conference Code 2020-01-SeMI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Preliminary study on time series forecasting of road traffic at multiple locations for applying to traffic congestion mitigation with adaptive vehicle speed control 
Sub Title (in English)  
Keyword(1) Sag sections  
Keyword(2) Time series prediction  
Keyword(3) Machine Learning  
Keyword(4) VAR  
Keyword(5) LSTM  
Keyword(6)  
Keyword(7)  
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1st Author's Name Satoshi Watanabe  
1st Author's Affiliation Shibaura Institute of Technology (SIT)
2nd Author's Name Ryusei Aiura  
2nd Author's Affiliation Shibaura Institute of Technology (SIT)
3rd Author's Name Hiroaki Morino  
3rd Author's Affiliation Shibaura Institute of Technology (SIT)
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Speaker Author-1 
Date Time 2020-01-31 10:00:00 
Presentation Time 90 minutes 
Registration for SeMI 
Paper # SeMI2019-107 
Volume (vol) vol.119 
Number (no) no.406 
Page pp.43-44 
#Pages 2 
Date of Issue 2020-01-23 (SeMI) 

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