Spatial analyses of crashes have been adopted in road safety for decades in order to
determine how crashes are affected by neighboring locations, how the influence of …

This study aims at contributing to the literature on pedestrian and bicyclist safety by building
on the conventional count regression models to explore exogenous factors affecting …

The safety of signalized intersections has often been evaluated at an aggregate level
relating collisions to annual traffic volume and the geometric characteristics of 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 …

Road traffic crashes pose a significant challenge worldwide, necessitating increased efforts
to reduce them and promote sustainable transport systems. This study aimed to investigate …

Existing advanced traffic management and emerging connected vehicles (CVs) technology
can generate considerable amount of data on vehicle positions and trajectories. This data …

Reduced visibility conditions increase both the probability of rear-end crash occurrences
and their severity. Crash warning systems that employ data from connected vehicles have …

This study aims to explore the effects of drivers' visual environment on speeding crashes by
using different machine learning techniques. To obtain the data of drivers' visual …

In the twentieth year of the twenty-first century, humanity is facing an unprecedented global
crisis owing to the COVID-19 pandemic. It has brought about drastic changes in the way we …

This study aims to propose a new algorithm to evaluate the rear-end collision risk under fog
conditions considering reduced visibility. The proposed algorithm compares the safe …