Shah Parva Dharmendrakumar

CM4050

The objective of the study is to identify high-risk zones prone to accidents on both divided and undivided highways using data analytics and propose effective mitigation strategies. The project entails collecting data from diverse sources, including traffic flow, historical accident records, road conditions, and environmental elements. Utilizing statistical analysis and pattern recognition methods, the goal is to develop a comprehensive understanding of accident-prone areas. Additionally, the project aims to suggest practical safety measures such as improved signage, road markings, lighting upgrades, and adjustments to speed limits. Detailed analysis report highlighting identified accident-prone stretches, along with recommended safety measures for divided and undivided highways.