Crossroads traffic density monitoring and injection mitigation through visual recognition

Abstract

Monitor and control traffic conditions are important in intelligent transport systems to reduce congestion, especially at intersections. The approach is needed to reduce the negative effects of the congestion at junctions and steps taken to control traffic at the intersection. The project identifies the number of cars through video image detection and thus take into account traffic and road width at each branch junction to resolve congestion by coordinating traffic lights. This project involves with the design, manufacture, and analysis of traffic monitoring system through computer technology and profile intersection. The system notifies the congestion monitored in three stages (empty, medium and many) and the size of the width of the road, road capacity and type of intersection. This study uses Indonesian Highway Capacity Manual (IHCM) with Fuzzy algorithm to detect vehicles using surveillance cameras at four traffic lights junctions. The green light is determined by the density of the vehicle and the type of intersection using adobe flash simulated.