As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …

Highlights•Conflict-based real-time safety performance functions are developed for
signalized intersections.•Several Tobit models including GRP-Tobit, RI-Tobit, and GRP-Tobit …

With the recent advancements in computer vision and artificial intelligence, traffic conflicts
occurring at an intersection and associated traffic characteristics can be obtained at the …

Intersections are among the most dangerous roadway facilities due to the complex traffic
conflicting movements and frequent stop-and-go traffic. However, previous intersection …

Traffic accidents have been one of the most important global public problems. It has caused
a severe loss of human lives and property every year. Studying the influential factors of …

This study proposes a novel approach to predict real time crash risk at signalized
intersections at the signal cycle level. The approach uses traffic conflicts extracted from …

Diabetes mellitus (DM) has become the third chronic non-infectious disease affecting
patients after tumor, cardiovascular and cerebrovascular diseases, becoming one of the …

Abstract Machine learning (ML) model interpretability has attracted much attention recently
given the promising performance of ML methods in crash frequency studies. Extracting …

In measuring road safety, accident severity is a key concern. Crash severity prediction
models inform researchers about the severity of a crash based on a variety of criteria. To …

Driven by the high social costs and emotional trauma that result from traffic accidents around
the world, research into understanding the factors that influence accident occurrence is …