The purpose of the paper is to establish a robust safety index for road safety and road traffic violation control systems. While many researchers studied vehicular to vehicular network info system, some focused on CCTV camera based information for the road networks, many created AI based algorithms directed towards road safety and accident reduction systems. Some have also focused on the behavioral aspects and weather conditions all with the help of various information communication technology and Artificial Intelligence based technologies. However, this research has not taken an approach integrating all of the databases in the road safety and traffic violation databases. This research paper suggests taking a much larger approach such as integrating all of the databases such as road accident database, road profile database, integrated traffic management system, integrate existing camera systems, weather information, drivers’ license database, road traffic accident database, and traffic violation database. With integration and use of proper artificial intelligence technologies, deep learning technologies, and cloud computing can bring real time road safety data at the fingertips of drivers and travelers. For administration and other concerned departments, it may reduce the burden of accidents and road safety concerns as they will get live data before any mishap happens. Departments will be able to take better decisions for road safety management and also to manage road accidents with minimum casualty. Also, the black spots will be dynamically updated based on real data.