Globally, road crashes impose massive burdens, and understanding the complex factors
influencing crash patterns requires advanced analytical methods. This study reviews 20 …

This study aims to use machine learning methods to examine the causative factors of
significant crashes, focusing on accident type and driver's age. In this study, a wide-ranging …

This study utilizes multilevel ordinal logistic regression (M-OLR), an approach that accounts
for spatial heterogeneity, to assess the dynamics of crash severity in Virginia, USA, over the …

The factors that affect the severity of crashes must be identified for pedestrian and traffic
safety in urban roads. Specifically, in the case of urban road crashes, these crashes occur …

Identifying critical nodes in transportation networks is vital for effective maintenance and
management. While conventional methods rely on topological features alone, they often …

Parametric and bio-parametric data encompass a wide range of information, including
physiological measurements, clinical observations, and laboratory results. The collection …