Smart Road Safety Enhancement System Using OpenCV

Absract—Traffic accidents on the road are a fatal worldwide issue; especially on the high-speed extra-urban freeways, bad conditions, and driver carelessness of drivers are major contributors of accidents. This project is a detailed safety analysis system with an aim of reducing the severity and frequency of accidents. It combines the statistical analysis of the Italian historical data on accidents at the Tangenziale freeways with field experiment data of eye-tracking, and vehicle exchange data to determine the primary risk behavioral factors, such as distraction and lane positioning. In addition, the system itself entails the adoption of a modular pothole detection system based on a YOLOv8 model to monitor real-time infrastructure through the prism of a web application developed using Django. The measurement of these effects in terms of autonomous automobile navigation and proactive intervention in high-risk areas, by synergistically integrating infrastructure analytics and behavioral research, allows municipal authorities to act upon the insights given by the system, and thus provides a long-term goal of smarter, safer road infrastructure.