Journal of agricultural safety and health
40079959
HIGHLIGHTS: An AI-driven system for predicting and preventing ATV crashes was developed. Machine learning model achieved rollover prediction accuracy of over 99%. The system has the potential to significantly reduce ATV-related injuries and fatalitie...
INTRODUCTION: Transportation companies have increasingly shifted their workforce from permanent to outsourced roles, a trend that has consequences for self-employed truck drivers. This transition leads to extended working hours, resulting in fatigue ...
INTRODUCTION: Driver distraction and inattention (DDI) are major causes of road crashes, especially on rural highways. However, not all instances of distracted or inattentive driving lead to crashes. Previous studies indicate that DDI-related driving...
Driver drowsiness remains a critical factor in road safety, necessitating the development of robust detection methodologies. This study presents a dual-framework approach that integrates a convolutional neural network (CNN) and a facial landmark anal...
As the quantity of motor vehicles and drivers experiences a continuous upsurge, the road driving environment has grown progressively more complex. This complexity has led to a concomitant increase in the probability of traffic accidents. Ample resear...
The safety of pedestrians in urban transportation systems has emerged as a significant research topic. As a vulnerable group within this transportation framework, pedestrians encounter heightened safety risks in complex urban road environments. Prote...
Recently, real-time traffic conflict prediction has drawn increasing attention due to its significant potential in proactive traffic safety systems. While various statistical and machine learning models have been developed for conflict prediction, tr...
The widespread deployment of intelligent vehicles necessitates comprehensive testing across diverse driving scenarios. A significant challenge is generating critical testing scenarios to accurately evaluate vehicle performance. To overcome the limita...
Many traffic accidents occur nowadays as a result of drivers not paying enough attention or being vigilant. We call this driver sleepiness. This results in numerous unfavourable circumstances that negatively impact people's life. The identification o...
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...