Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …

The prediction of the likelihood of vehicle crashes constitutes an indispensable component
of freeway safety management. Due to data collection limitations, studies have used mainly …

Selecting an appropriate exposure measure and functional form for Safety Performance
Functions (SPFs) is critical in precisely predicting crash counts by different crash types for …

About 40 percent of motor vehicle crashes in the US are related to intersections. To deal with
such crashes, Safety Performance Functions (SPFs) are vital elements of the predictive …

Intersections are established dangerous entities of a highway system due to the challenging
and unsafe roadway environment they are characterized for drivers and other road users. In …

Both crash count and severity are thought to quantify crash risk at defined transport network
locations (eg intersections, a particulate section of highway, etc.). Crash count is a measure …

One challenge faced by the random-parameter count models for crash prediction is the
unavailability of unique coefficients for out-of-sample observations. The means of the …

Traditionally, road safety is described in terms of number of accidents or injuries that occur in
traffic. While such indicators have the most direct connection with the subject studied, they …

The objective of this study is to quantify the safety performance of horizontal curves on two-
way, two-lane rural roads relative to tangent segments. Past research is limited by small …

Random parameters model has been demonstrated to be an effective method to account for
unobserved heterogeneity that commonly exists in highway crash data. However, the …