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Open AccessArticle

Map Matching for Urban High-Sampling-Frequency GPS Trajectories

by Minshi Liu 1,2, Ling Zhang 1,3,4, Junlian Ge 1,3,4,*, Yi Long 1,3,4,* and Weitao Che 5,6
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, China
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Authors to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(1), 31;
Received: 10 December 2019 / Revised: 23 December 2019 / Accepted: 30 December 2019 / Published: 5 January 2020
As a fundamental component of trajectory processing and analysis, trajectory map-matching can be used for urban traffic management and tourism route planning, among other applications. While there are many trajectory map-matching methods, urban high-sampling-frequency GPS trajectory data still depend on simple geometric matching methods, which can lead to mismatches when there are multiple trajectory points near one intersection. Therefore, this study proposed a novel segmented trajectory matching method in which trajectory points were separated into intersection and non-intersection trajectory points. Matching rules and processing methods dedicated to intersection trajectory points were developed, while a classic “Look-Ahead” matching method was applied to non-intersection trajectory points, thereby implementing map matching of the whole trajectory. Then, a comparative analysis between the proposed method and two other new related methods was conducted on trajectories with multiple sampling frequencies. The results indicate that the proposed method is not only competent for intersection matching with high-frequency trajectory data but also superior to two other methods in both matching efficiency and accuracy. View Full-Text
Keywords: map matching; GPS trajectory; high sampling frequency; road network map matching; GPS trajectory; high sampling frequency; road network
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Liu, M.; Zhang, L.; Ge, J.; Long, Y.; Che, W. Map Matching for Urban High-Sampling-Frequency GPS Trajectories. ISPRS Int. J. Geo-Inf. 2020, 9, 31.

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