For identifying the optimal model for real-time conflict prediction, there is a necessity for
proposing a quantitative analysis approach that adaptively selects the optimal prediction …

Intersection-related crashes on Thailand's highways pose a significant risk to road users,
particularly motorcyclists. This study develops customized Convolutional Neural Network …

Motorcycle crashes remain a significant public safety concern, requiring diverse analytical
approaches to inform countermeasures. This study uses machine learning to analyze injury …

Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on
highways. Comprehending the contributing factors to these occurrences is paramount in …

Crashes involving heavy goods trucks (HGVs) are of significant concern as it poses a higher
risk of fatality to light motor vehicles (LMVs). The study constructs three Deep Forest models …

The development of Rwanda was accompanied by rapid growth of various modes of
transport and the occurrence of road traffic crashes (RTCs). RTC severity has also increased …

In traffic accidents, elderly individuals face a significantly higher risk of mortality compared
with other age groups. To investigate the factors contributing to elderly pedestrian accidents …

Road traffic accidents remain a major cause of fatalities and injuries worldwide. Effective
classification of accident type and severity is crucial for prompt post-accident protocols and …

Urban road traffic accidents are severely threatening the safety of human life and property. In
this study, the Random Forest (RF) algorithm was used to identify the significant risk factors …

Traffic accidents continue to be a significant cause of fatalities, injuries, and considerable
disruptions on our highways. Understanding the underlying factors behind these incidents is …