Utilizing support vector machine in real-time crash risk evaluation

► We introduce support vector machine models to perform real-time crash risk evaluation. ► SVM models with different kernel functions were compared with logistic regression models. ► Hierarchical Bayesian logistic regression models were used to capture unobserved heterogeneity. ► Extension analyses about the explanatory variables used in the SVM models have been conducted.