Publication Type

Conference Proceeding Article

Publication Date

9-2016

Abstract

Locating only one GPS position to a road segment accurately is crucial to many location-based services such as mobile taxihailing service, geo-tagging, POI check-in, etc. This problem is challenging because of errors including the GPS errors and the digital map errors (misalignment and the same representation of bidirectional roads) and a lack of context information. To the best of our knowledge, no existing work studies this problem directly and the work to reduce GPS signal errors by considering hardware aspect is the most relevant. Consequently, this work is the first attempt to solve the problem of locating one GPS position to a road segment. We study the problem in a data-driven view to make this process ubiquitous by proposing a tractable, efficient and robust generative model. In addition, we extend our solution to the real application scenario, i.e., taxi-hailing service, and propose an approach to further improve the result accuracy by considering destination information. We use the real taxi GPS data to evaluate our approach. The results show that our approach outperforms all the existing approaches significantly while maintaining robustness, and it can achieve an accuracy as high as 90% in some situations.

Keywords

GPS, Location-based services, Map matching, Positioning

Discipline

Databases and Information Systems | Geographic Information Sciences

Research Areas

Data Management and Analytics

Publication

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Heidelberg, Germany, September 12-16, 2016

First Page

740

Last Page

751

ISBN

9781450344616

Identifier

10.1145/2971648.2971702

Publisher

ACM

City or Country

New York

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/2971648.2971702

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