Research On The Traffic Parameters Extrating Method Oriented The Traffic Information Sharing Platform

With the rapid economic development, the car ownership rates are increasing.However, the urban roads are difficult to expand, and it has caused serious traffic jamsand become the main traffic problem in some big cities, causing a great impact onpeople’s life and economic growth. Therefore，the traffic information sharing platformhas been the main idea to solve traffic problems, especially settling the problem oftraffic congestion greatly. This thesis takes the traffic information sharing platform asthe main research direction, from the traffic parameters extracting method, proposingthe detecting algorithm of the road speed based on video and the estimating method ofthe road vehicle space occupancy based on remote sensing image.The detecting algorithm of the road speed based on video is the key technologyfor traffic information sharing system. Due to the reliability and real-time highrequirements of speed detecting system in practical application, video speedmeasurement algorithm has better robustness and faster computing speed. Accordingto the new conditions, this thesis gives processing method in the corner detection,corner matching video speed in the past. In this method, velocity measurement systembased on video is divided into four steps: moving target detection module, videocapture module on the road vehicle, Harris corner detection module, vehicle cornermatching module and coordinate transformation module. The detailed steps of thisapproach for the first use of moving vehicle detection on the road mixed Gauss modeltarget and extract its prospect, and Harris corner detection principle to detect cornersof the foreground image, the corner matching principle angle on vehicle cornermatching, the first rough matching and finally to the coarse matching，then using themethod of single vision to coordinate transformation, and then obtain the moreaccurate vehicle speed.The estimation method of space occupancy of vehicles on roads based on remotesensing image is complementary to video processing technology, and is the key technology of the traffic information acquisition and processing. The thesis draws aconclusion that the aeronautical sensing data is relatively easier to acquire, contrastingwith remote sensing satellite data，close-spatial data and aeronautical data，so the dataof simulation in this thesis takes sample of aeronautical sensing data. To get the roadnetwork structure is by enhancement processing of road image, denoising, openingoperation, closing operation and binarization. This thesis estimates the length of roadsection by Hough and the length of vehicles by fuzzy processing techniques，thusgetting the space occupancy of vehicles. To obtain the space occupancy from remotesensing images, the length of both roads and vehicles must be extracted. Therefore,the extraction of the road length and the vehicle length is very important. Moreover,an effective and correct method about fuzzy processing techniques is introducedbecause of the unclearness and errors in remote sensing image. Through the exampleanalysis results, the proposed two traffic parameter extracting methods provide strongtechnical support for traffic information platform in the implementation ofmulti-source multi-dimensional information perception.