How Does the Pre-crash Environment Affect Injury Risk? Injury Prediction and Analysis Based on Graph Neural Network
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- Publication code
- 20264068
- Paper/Info type
- International Journal of Automotive Engineering
Vol.17 No.1
- Pages
- 15-21(Total 7 p)
- Date of publication
- Jan 2026
- Publisher
- JSAE
- Language
- English
Detailed Information
| Category(E) | Research paper |
|---|---|
| Author(E) | 1) Wei Junhao, 2) Yusuke Miyazaki, 3) Fusako Sato |
| Affiliation(E) | 1) Institute of Science Tokyo, 2) Institute of Science Tokyo, 3) Japan Automobile Research Institute |
| Abstract(E) | Injury severity in vehicle crashes is influenced by various factors within the pre-crash environment, including the environment, vehicle, driver, and other attributes. To investigate the relationships among these factors and identify the key determinants of injury outcomes, this study employed a graph neural network to model complex interactions and dependencies from a police-reported tabular database. The analysis revealed critical contributors to injury severity, uncovering the relationships among the variables in the pre-crash environment. These findings provide actionable insights for enhancing traffic safety and developing effective injury-prevention strategies. |