The Research Of Urban Traffic Congestion Detection System Based On Video

With the rapid growth of the motor vehicle and the very limited road networkcapacity unbalanced, the major cities in the worldwide all have a big problem ----urban traffic congestion. Practice has proved that it is very difficult to solve the trafficcongestion only with the traffic demand or traffic supply. In china many cities all facewith the embarrassment of no available land to create the new road facilities. At thistime, traffic management becomes particularly important, and the better trafficmanagement can maximize the network capacity, otherwise it will reduce the capacityof the road network. In recent years, an intelligent and efficient means of trafficmanagement have emerged ---- Intelligent Transportation Systems, abbr. ITS.Intelligent Transportation Systems applies the effectively integrate advancedinformation technology, the communication technology, the sensor technology, thecontrol technology and the computer technology to the entire system, and builds aall-round role, large scale , real-time, accurate and efficient integrated transportationmanagement system. Many developed countries and regions have already begun toresearch and use of intelligent transportation system, and China has graduallyincreased the research in this area in recent years, its broad application prospects,economic value and social value make the study of the intelligent transportationsystem become an emerging hot research topic.Intelligent transportation system is a large and complex system, the video-basedurban traffic congestion detection system proposed in this study is one of the mostbasic subsystem. The main fuction of this system is to detecte and discriminate thereal-time traffic status of the main roads in the city, then provide the accurate results tothe public security traffic management department and help them make the rightdecision. Many researchers have carried out many studies of this system, but the wholetraffic congestion detection system is seldom in our country. In this paper, based on theadvanced hardware and software technology design a set of intelligent video-basedtraffic congestion detection system, and introduce all the design details of the system and the implementation process.In this paper, the core algorithm includes two aspects: the traffic parametersdetection algorithm and congestion detection algorithm. The traffic parametersdetection algorithm uses the advanced video detection technology for trafficparameters detection. First, through a simple background difference method to obtainthe vehicle target, but with the limitations of the background subtraction methodmake the extraction of the vehicle target with the vehicle shadow, then the normalizedcorrelation algorithm is used to remove the vehicle shadow and then get the wholevehicle targets; Then combinate the virtual test line and the virtual test face to thevirtual coil detection method to detect the three traffic parameters---- traffic flow,traffic speed and the traffic sharing. In the part of the congestion detection algorithm,analyze the definition of the countries congestion state and then divide the congestionstate in to four levels ---- smooth, mild crowding, congestion and severe overcrowding,then refernce the classical algorithm in related areas ---- Ant Colony Algorithm andFuzzy C-means Clustering Algorithm to get the traffic congestion status of the fourhierarchical clustering center. Calculate the grade standard of membership of thecurrent traffic parameters to detemine the current traffic state of the traffic parameters.The part of the system design in this study includes two aspects. Hardware sectionmainly introduces a processing platform ----TMS320DM642, which is ahigh-performance didital signal processor developed by TI, then introduces somethingabout the hardware configuration of the video capture and the playback; Softwaresection describes the system software development environment, and focus on thesoftware implmentation process of each subsystem module. Then combined with aconcrete example, verificate the reliability and the feasibility of the algorithmproposed in this study.At last, make a comprehensive summary of the whole thesis, showing theshortcoming of this system and some ideas of some parts needed to be improved.