An Elements Weighted Map Matching Algorithm Based On Grid Maps

As the most important application system of ITS, Vehicle Navigation System(VNS) are the core of ITS. It was created to navigate vehicle especially on urban area.Due to the positioning data acquired from Global Position System(GPS) suffers the measurement error, the efficiency of ITS would be reduced. Fortunately, this can be resolved by Map Matching(MM) most cost-effectively.MM, which realize an optimal estimation of the vehicle position by integrating the positioning data which the spatial road network data, is supposed to the key of VNS.Existing MM algorithms have weaknesses which decrease their capability to support VNS. Therefore, a robust and reliable MM algorithm is developed in this research.This thesis has discussed items as follow:First,this thesis discusses the current the map-matching algorithm at home and abroad.Second, the thesis discusses the importance of existing MM algorithms are introduced.Third, a variety of factors influenced MM are analyzed.Next, Discussed in a special section of the map matching key and difficult.Then, the elements can be used in MM algorithm are excavated.Based on above procedures, An improved map matching algorithm based on a raster maps and weighting factors is developed. In this algorithm, a simplified grid errors region is constructed to reduce the number of segments to match, and within the errors region, calculate each segments’ weighting score, which is the summary of matching score on heading, proximity and relative position, then select the segment of highest weighting score as the correct segment, on which the optimal position is estimated.Finally, the technology is verified with GPS data which collected on the part road network of Nanjing. The algorithm was tested In Matlab and get the entire program run time.Under the weight parameters properly selected cases,the result shows that the new algorithm has better matching accuracy and timeliness.