The Research Of Large-Scale And Complete Coverage Urban Road Traffic Status Collection Based On GPS Equipped Floating Car Technology

In the current traffic control system, the acquisition of traffic condition data is taken more and more seriously. Currently, the means to acquire the state of transportation mainly contain microwave radar, induction coils, video camera and so on. These detectors are mainly deployed in key sections and main road intersections.Due to the limited scope of the layout of the detectors, there are plenty of blind spots of information and "vacuum" zone on the city road. Besides, in the places distributed with fixed detectors, there is also traffic information loss because of the failure of the detector. The problem of how to obtain real-time traffic information of the whole city road accurately and totally demands prompt solutionBased on the national science and technology support program subject --Olympic electric vehicle demonstration and technical support, this paper uses taxis as floating cars and makes use of the historical GPS data of 28 thousand taxis, matches the GPS data fast on GIS map by using map matching algorithm. According to the results, matching with the actual situation of the road section, taking mainly the GPS data and other detector data for auxiliary, we can obtain real-time traffic condition of any road in the network of Beijing roads accurately and easily. So that we can solve the traffic information obtaining problems caused by the fault of the detectors as well as the road without distribution of detectors.This paper mainly includes:(1) Using the GIS map preprocessing technologies. Use of the grid of map and the methods of adding direction on the map coordinates. Improving the speed of inquiry and direction judgment during the matching process.(2) Using the fast map matching algorithm based on GIS map pretreatment techniques. Compared with common algorithm this algorithm adds functions to distinct main road and supplementary road on fast road.(3) In the matching results, with reference to the microwave data on fast road, this paper calibrates the GPS data and obtains the calibration factor.(4) With calibrated GPS data, this paper acquires the traffic state of the three representative road sections.