Abstract
Abstract Previous real-time map matching algorithms for in-vehicle navigation systems had some efficiencies and defects on time lagging and low accuracy. As a response, this paper proposes a new algorithm that integrates STP (spatio-temporal proximity) and IWC (improved weighted circle), in which the new algorithm proposes STP to dynamically refine candidate matching roads, and IWC to adaptively identify the optimal matching road. Specifically, three spatio-temporal proximity indicators are defined in STP to build a three-dimensional stereoscopic cone, and then the two-dimensional projection of the cone are adopted to dynamically select the candidate matching roads. Further, by adaptively setting the weight, the IWC algorithm is developed to integrate three new parameters to adaptively determine the optimal matching road. The test results show that the matching accuracy of the algorithm is over 95%, much higher than that of the existing algorithm, which demonstrates the feasibility and efficiency of the new algorithm.
Highlights
Previous real-time map matching algorithms for in-vehicle navigation systems had some efficiencies and defects on time lagging and low accuracy
To respond to the algorithm‘s problems in terms of time lag and low accuracy in real-time map matching for invehicle navigation systems, this paper proposes a new algorithm that integrates spatio-temporal proximity and improved weighted circle methods, i.e., STP-improved weight circle (IWC) algorithm, to refine candidate roads adaptively and identify the best road, so as to improve accuracy and efficiency of real-time map matching
To verify timeliness and accuracy of STP-IWC algorithm in this paper, we combine C# programming and ArcGIS Engine 10.2 to design some experiments under Windows 10 operating system to compare the performance and efficiency of this algorithm with the existing direct matching algorithm and curve fitting algorithm
Summary
Previous real-time map matching algorithms for in-vehicle navigation systems had some efficiencies and defects on time lagging and low accuracy. This paper proposes a new algorithm that integrates STP (spatio-temporal proximity) and IWC (improved weighted circle), in which the new algorithm proposes STP to dynamically refine candidate matching roads, and IWC to adaptively identify the optimal matching road. Three spatio-temporal proximity indicators are defined in STP to build a three-dimensional stereoscopic cone, and the two-dimensional projection of the cone are adopted to dynamically select the candidate matching roads. By adaptively setting the weight, the IWC algorithm is developed to integrate three new parameters to adaptively determine the optimal matching road. The test results show that the matching accuracy of the algorithm is over 95%, much higher than that of the existing algorithm, which demonstrates the feasibility and efficiency of the new algorithm
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