… crash severity level was carried out in this study, with an emphasis on the evaluation of the
relationship between poor pavement conditions and crash severity … traffic crash severity levels…

… function to predict the severity of traffic crashes. Underlying this … The data used in the analysis
include a sample of traffic crashes … affecting the occurrence and severity of those crashes. …

… location, road alignment, light condition, road surface condition, and speed limit has significant
impacts on traffic crash severity. Higher crash severity are associated with rural roadways…

… Machine learning approaches in traffic crash severity modelling This section reviews ML
applications in crash severity analysis identified in Section 2. Each subsection is dedicated to a …

… yield control, and no traffic control. Identifying those geometric and traffic factors leading to
severe crashes at unsignalized intersections is an essential task of traffic safety analysts. This …

… risk factors in this study) on the severity of traffic crashes, which mainly refers to the number
… damage caused by traffic crashes, and thereby predict the severity level of the crashes. This …

… Our results suggest that the level of traffic congestion does not affect the severity of road
crashes on the M25 motorway. The impact of traffic flow on the severity of crashes, however, …

… were explored to predict crash severity, only a … crash severity using different deep learning
approaches. This study aimed to classify and predict the injury severity level of traffic crashes …

… Table 2 gives the influencing variables of freeway traffic crash severity in this research.
Since the selected factor variables include attribute variables and continuous variables, they …

… affecting highway crash severity in Louisiana. Three candidate models were fit to the crash
data … was selected as the crash severity prediction model of choice. The factors contributing to …