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| Presentation | 2020-10-20 10:50 System operation for estimation of road condition using tire vibration data Satoru Kawamata (Bridgestone), Tomoko Matsui (ISM), Mitsuhiro Nishida, Takeshi Masago (Bridgestone)  IBISML2020-10 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In a system that estimates the road surface condition from tire sensor data and supports safe driving, it is crucial to deal with three problems, (1) robust, high-speed and lightweight calculation of feature quantities from tire sensor data, (2) data selection, and (3) continuous update of the road surface condition classifier to respond to changes in tires over time. In this paper, we apply a feature extraction method that is robust against changes in speed and road surface unevenness, a data selection method by kernel herding, and a semi-supervised learning method. In the experiments with two types of road surface conditions, dry and wet, the effectiveness of these methods is examined. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Intelligent tire / road surface condition / kernel herding / semi-supervised learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 195, IBISML2020-10, pp. 14-19, Oct. 2020. | |
| Paper # | IBISML2020-10 | |
| Date of Issue | 2020-10-13 (IBISML) | |
| 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) | |
| Download PDF | IBISML2020-10 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2020-10-20 - 2020-10-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Organized Sessions on Frontiers of Machine Learning and General Sessions |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2020-10-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | System operation for estimation of road condition using tire vibration data |
| Sub Title (in English) | |
| Keyword(1) | Intelligent tire |
| Keyword(2) | road surface condition |
| Keyword(3) | kernel herding |
| Keyword(4) | semi-supervised learning |
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| 1st Author's Name | Satoru Kawamata |
| 1st Author's Affiliation | Bridgestone (Bridgestone) |
| 2nd Author's Name | Tomoko Matsui |
| 2nd Author's Affiliation | Institute of Statistical Mathematics (ISM) |
| 3rd Author's Name | Mitsuhiro Nishida |
| 3rd Author's Affiliation | Bridgestone (Bridgestone) |
| 4th Author's Name | Takeshi Masago |
| 4th Author's Affiliation | Bridgestone (Bridgestone) |
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| Speaker | Author-1 |
| Date Time | 2020-10-20 10:50:00 |
| Presentation Time | 25 minutes |
| Registration for | IBISML |
| Paper # | IBISML2020-10 |
| Volume (vol) | vol.120 |
| Number (no) | no.195 |
| Page | pp.14-19 |
| #Pages | 6 |
| Date of Issue | 2020-10-13 (IBISML) |
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