Research On Urban Traffic State Assessment Based On KD Searching-tree

The traffic congestion has become one of the main problems in the city all over the world. With the rapid growth of our national economy and the unprecedented speed up of urbanization, the number of automobile increases rapidly year by year, which result in traffic-jams in many cities. Even if many cities have increased their input in construction of traffic facilities, it still cannot resolve the contradiction between the increasing need of transportation and the low utilization of traffic facilities. Intelligent traffic state system has been seemed as the best acknowledged method to solve problems in traffic field at present. So the traffic state processing methods which based on the KD searching-tree is put forward to solve the traffic congestion.This paper firstly introduces the concept of floating car, map-matching and some other technologies about traffic state processing, including floating car data(FCD) collection and preprocessing methods, determination of the number of floating car, searching the candidate road with the method of the KD searching-tree, traffic state evaluation system and GIS digital map development. Based on the analysis of map-matching algorithms, the road network of Jinan was built, and we use the large-scale increment precise map-matching algorithm to increase the matching accuracy. We calculate the average speed of road. According to the corresponding evaluation standard, we determine the level of road traffic congestion.In this paper, we mainly introduce two algorithms which are used to select candidate road sections. They mainly contains the methods of using the rectangle area and KD searching-tree. Both the efficiency of the two algorithm is better than the original method called the ellipse area. And when the data to be processed becomes more and more,the efficiency of the KD searching-tree is better than using the rectangle area.At the same time, the article uses the Baidu-map API interface which is for professionals to develop the traffic state display system.