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A Path Increment Map Matching Method for High-Frequency Trajectory

Haoyan Wang, Yuangang Liu, Shaohua Li, Bo Liang, HE Zongyi

2023IEEE Transactions on Intelligent Transportation Systems10 citationsDOI

Abstract

Aiming at the problems of low matching accuracy and slow matching speed of high-frequency trajectory data in complex urban road networks, this paper proposes a matching method based on path increment. This method consists of two parts: combined filtering and incremental matching. Firstly, the road network is simplified through combined filtering, and then the incremental matching is carried out by taking the paths as increments. In the matching procedure, a comprehensive evaluation scheme of similarity based on distance factor and curvature is adopted. The above measures effectively reduce the impact of complex road segments on the matching results, while the path increment method enables the matching process to be executed more rapidly and accurately. The experiments were conducted using the Geolife datasets. The results show that our algorithm has obvious advantages over similar algorithms in terms of matching accuracy and efficiency, and shows good stability in road matching tests with different complexity.

Topics & Concepts

Matching (statistics)Path (computing)TrajectorySimilarity (geometry)Map matchingProcess (computing)Blossom algorithmOptimal matchingCurvatureStability (learning theory)Computer scienceAlgorithmArtificial intelligenceMathematicsGlobal Positioning SystemImage (mathematics)StatisticsMachine learningOperating systemGeometryProgramming languagePhysicsAstronomyTelecommunicationsData Management and AlgorithmsAutomated Road and Building ExtractionTraffic Prediction and Management Techniques
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