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Summary & Details

Automated Design of Vehicle Load Characteristics and Structures for Pedestrian Protection Using Machine Learning

機械学習を活用した歩行者保護のための車両荷重特性と構造の自動設計

Delivery: Available on this site

Format: PDF

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

Publication code: 20264078

Paper/Info type: Symposium Text

No.13-25

Pages: 98-109(Total 12 p)

Date of publication: Jan 2026

Publisher: JSAE

Language: Japanese

Event: JSAE Symposium 2025

Detailed Information

Category(J)	PPT資料 Translation
Category(E)	PPT slides
Author(J)	1) 山本直人, 2) 鈴木香織, 3) 大嶺慶太, 4) 佐藤大知
Author(E)	1) Naoto Yamamoto, 2) Kaori Suzuki, 3) Keita Ohmine, 4) Daichi Sato
Affiliation(J)	1) マツダ株式会社, 2) マツダ株式会社, 3) マツダ株式会社, 4) マツダ株式会社
Affiliation(E)	1) Mazda Motor Corporation, 2) Mazda Motor Corporation, 3) Mazda Motor Corporation, 4) Mazda Motor Corporation
Abstract(J)	レイアウト制約下で車両デザインと衝突安全を両立する構造設計は、一般にシミュレーションの繰り返しで多くの時間を要する。そこで歩行者保護を例に、機械学習で最適な荷重特性・必要スペースを高速に導出するモデルと、構造から荷重特性を予測するモデルを構築し、車両デザインと衝突安全のトレードオフを迅速に解決した。 Translation
Abstract(E)	Structural design that balances vehicle design and collision safety under layout constraints generally requires a lot of time due to repeated simulations.Using pedestrian protection as an example, we developed a model that uses machine learning to quickly derive optimal load characteristics and required space, as well as a model that predicts load characteristics from the structure, quickly resolving the trade-off between vehicle design and collision safety.

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