Road traffic accidents have increased globally, which has led to significant challenges to
urban safety and public health. This concerning trend is also evident in California, where …

In recent years, the significance of machine learning in agriculture has surged, particularly in
post-harvest monitoring for sustainable aquaculture. Challenges like heterogeneity …

Reliable and interpretable traffic crash modeling is essential for understanding causality and
improving road safety. This study introduces a novel approach to predicting collision types …

This chapter presents a comprehensive study aimed at enhancing road safety in India
through the development and application of a machine-learning predictive model for traffic …

Abstract Background: Car accidents in Northwest Ethiopia have significantly increased in
severity, with increasing impacts on public safety. This study aims to predict car accident …

This paper presents a focused analysis of the primary factors contributing to road accidents,
encompassing human behavior, road conditions, and vehicle-related issues. To develop …

A road construction project involves the planning, design, and construction of roads,
highways, and related infrastructure, such as bridges, tunnels, and drainage systems. Risks …

Road traffic accidents remain a critical challenge for urban planners, transportation
authorities, and public safety stakeholders worldwide. Despite advancements in road …