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Paper Abstract and Keywords
Presentation 2013-03-15 15:35
Towards driving behavior prediction: Applying nonparametric Bayesian approach to driving operation time series data
Ryunosuke Hamada, Takatomi Kubo, Kazushi Ikeda, Zujie Zhang, Tomohiro Shibata (NAIST), Takashi Bando, Masumi Egawa (DENSO) CAS2012-142 SIP2012-173 CS2012-148
Abstract (in Japanese) (See Japanese page) 
(in English) Prediction of driving behaviors is important problem in developing a next-generation driving support system. In order to take account of diverse driving situations, it is necessary to deal with multiple time series data considering commonalities and differences among them. In this study we utilize the beta process autoregressive hidden Markov model (BP-AR-HMM) that can model multiple time series considering common and different features among them using the beta process as a prior distribution. We apply the BP-AR-HMM to actual driving operation data to estimate vector autoregressive process parameters that represent the segmental driving behaviors, and with the estimated parameters we investigate whether we can predict the driving behaviors of unknown test data. Prediction accuracy of test data using BP-AR-HMM is compared with that of using classical HMM. The results suggest that it is possible to identify the dynamics behaviors of driving operations using BP-AR-HMM, and with BP-AR-HMM we can predict driving behaviors precisely in actual environment than with HMM.
Keyword (in Japanese) (See Japanese page) 
(in English) time series analysis / driving operation prediction / Bayesian nonparametric approach / beta process autoregressive hidden Markov model / beta process / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 485, SIP2012-173, pp. 265-270, March 2013.
Paper # SIP2012-173 
Date of Issue 2013-03-07 (CAS, SIP, CS) 
ISSN Print edition: ISSN 0913-5685    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)
Download PDF CAS2012-142 SIP2012-173 CS2012-148

Conference Information
Committee SIP CAS CS  
Conference Date 2013-03-14 - 2013-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Keio Univ. Tsuruoka Campus (Yamagata) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network Processor, Signal Processing for communication, and Wireless LAN/PAN, etc. 
Paper Information
Registration To SIP 
Conference Code 2013-03-SIP-CAS-CS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Towards driving behavior prediction: Applying nonparametric Bayesian approach to driving operation time series data 
Sub Title (in English)  
Keyword(1) time series analysis  
Keyword(2) driving operation prediction  
Keyword(3) Bayesian nonparametric approach  
Keyword(4) beta process autoregressive hidden Markov model  
Keyword(5) beta process  
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Keyword(8)  
1st Author's Name Ryunosuke Hamada  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Takatomi Kubo  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Kazushi Ikeda  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
4th Author's Name Zujie Zhang  
4th Author's Affiliation Nara Institute of Science and Technology (NAIST)
5th Author's Name Tomohiro Shibata  
5th Author's Affiliation Nara Institute of Science and Technology (NAIST)
6th Author's Name Takashi Bando  
6th Author's Affiliation DENSO CORPORATION (DENSO)
7th Author's Name Masumi Egawa  
7th Author's Affiliation DENSO CORPORATION (DENSO)
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Speaker Author-1 
Date Time 2013-03-15 15:35:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # CAS2012-142, SIP2012-173, CS2012-148 
Volume (vol) vol.112 
Number (no) no.484(CAS), no.485(SIP), no.486(CS) 
Page pp.265-270 
#Pages 6 
Date of Issue 2013-03-07 (CAS, SIP, CS) 

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