Construction of Injury Prediction Model for Car Occupants using Gradient-Boosting Decision Tree Model

DOI

Bibliographic Information

Other Title
  • 勾配ブースティング決定木を用いた乗員傷害予測モデルの構築

Abstract

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.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390861703748489472
  • DOI
    10.11351/jsaeronbun.55.56
  • ISSN
    18830811
    02878321
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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