From Canopy to Collision: A Hybrid Predictive Framework for Identifying Risk Factors in Tree-Involved Traffic Crashes

This study develops a hybrid predictive framework using machine learning (CatBoost, SHAP) and logistic regression to identify and quantify risk factors contributing to injury severity in tree-involved traffic crashes. It analyzes CRSS data from 2020-2023 to understand high-energy impacts often resulting in fatal or severe injuries.