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Summary & Details

Machine Learning Based Modeling for Ride Comfort of Passenger Vehicle on Public Roads in Thailand

タイ一般道における乗り心地官能評価モデルの構築

Delivery: Available on this site

Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20215187

Paper/Info type: Proceedings (Spring)

No.42-21

Pages: 1-5(Total 5 p)

Date of publication: May 2021

Publisher: JSAE

Language: Japanese

Event: 2021 JSAE Annual Congress (Spring)[Online Meeting]

Detailed Information

Author(J)	1) 高岸洋一, 2) 神村耕二, 3) 角南高匡, 4) 小林倫之, 5) 山本敦也
Author(E)	1) Yoichi Takagishi, 2) Koji Kamimura, 3) Takamasa Sunami, 4) Noriyuki Kobayashi, 5) Atsuya Yamamoto
Affiliation(J)	1) コベルコ科研, 2) Kobelco Research International, 3) コベルコ科研, 4) Kobelco Research International, 5) Kobelco Research International
Affiliation(E)	1) Kobelco Research Institute, 2) KRIT, 3) Kobelco Research Institute, 4) KRIT, 5) KRIT
Abstract(J)	タイ国の一般道を対象とし、車両振動データから乗り心地を予測する機械学習モデルを構築した。様々な路面・ルートにおける加速度等の計測値を説明変数とし、官能試験被験者の心拍数およびアンケート結果を感情三方向にベクトル化した値を目的変数とした。本モデルにより、計測やCAE等からの高精度な乗り心地予測が期待される。 Translation
Abstract(E)	Ride comfort prediction model of passenger vehicle on public roads in Thailand has been developed based on Machine Learning. The measurement values including acceleration in each direction were adopted as explanatory variables, and the vectorized values of the questionnaire results and the heart rate data were used as objective variables. This model makes it possible to predict ride comfort from CAE or measurement data.

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