Machine Learning Algorithms for Improving Transportation Safety

The integration of machine learning (ML) algorithms in transportation safety is transforming the way traffic systems operate, reducing accidents, and enhancing predictive maintenance for vehicles and infrastructure. By leveraging artificial intelligence (AI), computer vision, and real-time analytics, transportation agencies can analyze traffic patterns, detect safety risks, and optimize vehicular movements. This paper explores the role of ML in improving transportation safety, covering key applications such as AI-powered collision detection, predictive accident analysis, and smart traffic management. Additionally, challenges such as data privacy, real-time processing limitations, and ethical concerns in autonomous vehicle decision-making are discussed, along with emerging trends in AI-driven transportation safety innovations.