Abstract:In this study, new performance measures are proposed for hotspot identification in urban intersections. These measures reflect severity factor weights, which are determined based on data mining. To estimate the severity factor weights of crashes at urban intersections, the study utilizes tree-based random forest (RF) and extreme gradient boosting (XGB) methods. The importance of variables in the severity classification model is standardized and utilized for calculating the score of each crash, which is aggrega… Show more
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