TY  - JOUR
PY  - 2023//
TI  - Construction of injury prediction model for car occupants using gradient-boosting decision tree model
JO  - Transactions of Society of Automotive Engineers of Japan
A1  - Takahashi, Keita
A1  - Miyazaki, Yusuke
A1  - Kitamura, Koji
A1  - Sato, Fusako
SP  - 56
EP  - 62
VL  - 55
IS  - 1
N2  - It is necessary to estimate the injury of occupants during car accidents to estimate the effect of injury reduction performance of autonomous driving systems. Although there are some estimation models of injury of occupants based on logistic regression, logistic regression has the problem of being unable to express nonlinear relationships between explanatory and objective variables. In this study, we used LightGBM, a decision tree model, and our own selected explanatory variables to construct an injury prediction model to predict the probability of VAIS3+ of vehicles. It showed a significant improvement in performance from URGENCY.<p />  <p>Language: ja</p>
LA  - ja
SN  - 0287-8321
UR  - http://dx.doi.org/10.11351/jsaeronbun.55.56
ID  - ref1
ER  -