Comparison of four statistical and machine learning methods for crash severity prediction
Comparison of four statistical and machine learning methods for crash severity prediction
Motor vehicle drivers’ injuries in train–motor vehicle crashes
Motor vehicle drivers' injuries in train-motor vehicle crashes
Cluster-Based Approach to Analyzing Crash Injury Severity at Highway–Rail Grade Crossings
Case Study of Crash Severity Spatial Pattern Identification in Hot Spot Analysis
Pedestrian and Bicyclist Violations at Highway–Rail Grade Crossings
Train-Level and Car-Level Modeling of Hazardous Materials Release in Railroad Incidents
Comparison of Driver Behavior at Highway–Railroad Crossings in Two Cities
Distracted Motor Vehicle Driving at Highway–Rail Grade Crossings
Reducing Undesirable Actions of Motor Vehicle Drivers at Railroad–Highway Grade Crossings
Reducing Undesirable Actions of Motor Vehicle Drivers at Railroad-Highway Grade Crossings
Injury Severity of Truck Drivers in Crashes at Highway-Rail Grade Crossings in the United States
Modeling the Probability of Hazardous Materials Release in Crashes at Highway–Rail Grade Crossings
Deep Learning Model for Crash Injury Severity Analysis Using Shapley Additive Explanation Values
A Spatial–Temporal Multitask Collaborative Learning Model for Multistep Traffic Flow Prediction