LAUSR

Traffic Signal Control is an effective mean of solving urban traffic problems by providing appropriate signal timings for road intersections. In this paper, we propose a novel approach originated from methods and applications of recommendation systems to select the most suitable signal timings for various traffic demands. Specifically, we use the idea of computational experiments and the well-known recommendation technology called Collaborative Filtering to find the best signal timings from a database filled with large amounts of traffic data. When the database is not large enough for some special traffic situations, traditional approaches are adopted. Corresponding data with good performance will be recorded.