An intelligent traffic responsive contraflow lane control system

An intelligent-self learning dynamic optimal contraflow lane control system developed for the George Massey Tunnel in southern Greater Vancouver is introduced. A program was developed to permit the accurate estimation of realtime traffic demands. Online traffic data are sorted by a fuzzy modeling algorithm to identify the best matching pattern. A self learning mechanism is utilized to modify the predicted demand incrementally. An optimization algorithm is developed for online calculation of the optimal contraflow schedule based on the predicted demand. The total delay of both traffic approaches is minimized.