Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 7, Issue 1


Published
on

September 5, 2022


Pages

2459-2466


DOI

Article

Studying a matching method combining distance proximity and buffer constraints

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Authors

Fengping Wang Affiliation:
Department of Data Science and Big Data Technology, School of Computer Science, Xi’an Polytechnic University, Xi’an 710048, Shaanxi, China


Abstract

In order to achieve fast matching of global navigation satellite system (GNSS) track data and vector road network data, a rough-to-fine matching method combining distance proximity and buffer constraints is studied. The GNSS track data is preprocessed: A rasterisation method is used to eliminate the low-quality track data and obtain the binary graph; then, the road centrelines are obtained by a skeleton extraction method; the thinning data is converted into line segments or closed lines starting from nodes by the boundary tracking method, which is stored in the vector form. Finally, the boundary tracking method is used to convert the thinning data into closed lines and store them in the vector form. A two-layer rough-to-fine matching strategy is applied: First, the changing state of the road arc is determined according to the rough matching strategy of road segment distance. Next, according to the buffer constraint criterion, a rectangular or circular buffer is selected to achieve precise matching of road network data. The results show that the proposed method has good matching effect, which is especially suitable for working with more GNSS track data.


Keywords

Matching algorithm, GNSS track data, road node, road arc


Citation

Wang, F. (2022). Studying a matching method combining distance proximity and buffer constraints. Applied Mathematics and Nonlinear Sciences, 7(1), 2459–2466. https://doi.org/10.2478/amns.2022.1.00019

Published by: Engineering Journals

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