Exploring Spatial Variations in Factors Influencing Cyclist Injury Severity in Traffic Crashes: A Comparison of Geographically Weighted Regression and Spatial Machine Learning
Results show that older cyclist age, higher vehicle speeds, intersection locations, multi-lane roadways, and dark conditions are associated with higher probabilities of evident or more severe injuries, highlighting the predictive capability of spatial machine learning while retaining interpretable geographic variation,...