To reduce traffic accidents, an accurately estimated model is needed to capture the true
relationships between the injury severity and risk factors. This study aims to propose a …

In many related works, nominal classification algorithms ignore the order between injury
severity levels and make sub-optimal predictions. Existing ordinal classification methods …

In order to improve traffic safety, the authors conducted an analysis to identify the causes
significantly affecting the severity of road accidents. The study employed the methods of …

Thorough evaluations on injury risk (IR) are fundamental for guiding interventions toward the
enhancement of both the road infrastructure and the active/passive safety of vehicles. Well …

Traffic crash data is often greatly imbalanced with the majority of non-fatal crashes and only
a small number of fatal crashes. Such data imbalance issue poses a challenge for crash …

Objectives This study aimed to build and test the models of machine learning (ML) to predict
the mortality of hospitalised motorcycle riders. Setting The study was conducted in a level-1 …

With the considerable increase in ownership of motor vehicles, traffic crashes have become
a challenge. This paper presents a study of naturalistic driving conducted to collect driving …

Smart cities came out as highly knowledgeable bio-networks, offering intelligent services
and innovative solutions to urban problems. With rapid development, urbanization, and …

Due to the small range of plastic deformation temperatures during hot rolling of Zircaloy-4
plates, it is important to determine the appropriate flow behaviors for plate profile control of …

Examining the relationship between streetscape features and road traffic accidents is pivotal
for enhancing roadway safety. While previous studies have primarily focused on the …