Research On Map Matching Algorithm For Fusion Geometric Information And Topological Relation Under Low Sample Rate

For vehicle navigation systems,positioning accuracy is an important indicator of its performance.Map matching method is one of the main methods to eliminate the positioning error of the vehicle navigation system.The map matching is mainly to match the current location information of the vehicle acquired by the GPS positioning device with the urban electronic map stored in the navigation system,so as to improve the accuracy of the vehicle positioning.Because the method is low cost and easy to implement,it is widely used in vehicle navigation system.In order to save the storage space and save the power of the GPS device in the practical application,it will reduce the sampling frequency of the equipment,thus forming a large number of low GPS sampling data.Compared to high sampling rate data,the available information of low sampling data is relatively low,which will lead to greater error.Although the proposed map matching algorithm for low sampling rate scenarios can accommodate simple urban roads,there is still a large error in the face of complex roads.In this paper,the geometric information and topological structure of the road are analyzed,and combined with probability method to ensure that the map matching under complex road conditions has high precision.The main work is as follows:A map matching algorithm based on travel time analysis for low sampling rate scenarios is proposed.Through the verification experiment of the existing low sampling rate algorithms,it is found that there is a road matching error when the vehicle is taking circuitous routes between the two sampling points.In order to solve this problem,the algorithm improves the spatial analysis function of IVMM(Interactive Voting Map Matching),and combined with the actual travel time analysis.The similarity between the actual travel time and the estimated travel time is added in the process of calculating the probability of candidate points,which successful match the sampling point to the actual traveling road.The matching result is improved by 30.5%-44.9%compared with the existing algorithm.A low sampling rate map matching algorithm which takes into account the azimuth of driving and its road scenarios.Through the analysis of the matching process of the existing low sampling rate algorithm,it is found that the utilization of vehicle sampling information is not sufficient in the matching process.Therefore,based on geometric analysis,topological analysis and travel time analysis,this algorithm adds the similarity analysis to the direction of the vehicle and the direction of the nearby road,and assigns different weight proportion to different road scenarios,which effectively reduce the matching error in intersections.The results show that the algorithm improves the accuracy of 35.1%and 6.6%compared with MIV-Matching and TIVMM(Time Interactive Voting Map Matching)by using the actual data collected.This paper is based on the Java programming language and Google Earth to implement the algorithm and the experiment part,and the algorithm is compared with three aspects of the matching error distance,the standard deviation and the variance of the error by using the actual GPS data and the urban electronic map,which provides a simple and effective method for the realization and evaluation of map matching algorithm in complex road environment.