Detection And Analysis Of Traffic Parameters Based On Video

Traffic flow parameters detection is an important research field of intelligent transportation system. It includes vehicle flow, vehicle velocity,road-occupied and so on, and there are many kinds of ways to measure parameters. In the numbers of detection techniques, the technology of traffic flow detection based on video image processing has been a hot field in the ITS because of it’s outstanding advantage that large detection area, informative and flexible system setup. There are broad application prospects.The main work is divided into two parts:traffic parameters detection based on video and Analysis of the relationships among the traffic parameters.Secondly, according to the vehicle detection, this paper proposes video-based detection of traffic flow, speed and other traffic parameters and calculates the traffic density according to the method of time share. And the relationship between three traffic parameters were studied.Thirdly, using the video of the traffic in the real environment, proposed vehicle detection algorithm and the traffic parameters detection algorithm Through MATLAB/GUI programming are tested. The results show the effectiveness of vehicle detection and the accuracy of traffic parameters.Finally, the parameters of the obtained by experimental data is analysed. After processing the data, which was combined with the Greenshields, Greenberg and Underwood model and was fitted. And then the paper analyzed the speed and the traffic density of the video recording for the time period.