Vehicle Matching between Adjacent Intersections by Vehicle Type Classification

Traffic signal control is proposed for alleviating heavy traffic congestions in urban areas. It is important to measure traveling time along each network link in order to optimize urban traffic signal control. Traveling time measurement by using vision sensor has an advantage in cost compared with those by using spot sensor, license plate reader or floating car. Therefore, we have developed a vision sensor which is able to measure traveling time between the adjacent intersections, installing a single camera at each intersection. This vision sensor covers whole the area of an intersection, and detects a region of vehicle in an image and classifies vehicle sizes and colors. The two vehicle feature sequences are compared with DP Matching to search the same vehicle sequences. Upstream vehicle feature sequences and downstream vehicle feature sequences are segmented into units called fragments and these fragments are compared in DP matching. By matching vehicles on the plane, multiple paths are obtained. Only one path is determined according to two rules; minimize turning frequency of lines, and maximize length of cross line. Measured traveling time has a margin of error of 4.5 % one way or the other for true traveling time. Even if some vehicles fail to match, traveling time of vehicle sequence can be measured according to the vehicles which run around the vehicles. Therefore, this method is very practical.