A Path Increment Map Matching Method for High-Frequency Trajectory

• Published in: IEEE transactions on intelligent transportation systems Vol. 24; no. 10; pp. 1 - 15
• Main Authors: Haoyan, Wang, Yuangang, Liu, Shaohua, Li, Bo, Liang, Zongyi, He
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-10-2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; complex urban road network; Complexity; Distance factor; Filtration; Global Positioning System; Heuristic algorithms; Hidden Markov models; High-frequency trajectory; increment; map matching; Matching; Real-time systems; Roads; Topology; Trajectories; Trajectory
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2023.3281418

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.