This project aims at developing an Automated Traffic Surveillance system with Computer Vision techniques. In a scientific and technological point of view we pretend to develop real-time algorithms for video sequence analysis of traffic scenes and explore innovative extended field of view camera systems (panoramic), with the final goal of price reduction and performance gain with respect to currently existing systems. In particular we address the applications of measuring traffic flow and detecting abnormal events on highways and critical urban areas. Traffic flow monitoring records statistical data on traffic distribution along time (number of vehicles, average velocity, average wait time on queues, etc.). We propose to develop a system that monitors a traffic region, acquires statistical data on traffic density and makes this data available on the Internet. Automatic event detection can help in speeding-up reaction to abnormal events, like accidents and serious transgressions to traffic rules. We propose to develop a system that detects abnormal events on critical traffic points, records the event history and send alarm signals to control stations.