Publication Type

Conference Proceeding Article

Publication Date

9-2015

Abstract

The accuracy and completeness of a digital map plays a critical role in determining the quality of most location-based services. Unfortunately, road networks change frequently. Consequently, we study the issue of automatic map update in this paper. We propose a system called COBWEB which takes all the unmatched trajectories as input and generates the missing road segments with both the geometry properties and topology features well preserved. We conduct a comprehensive experimental study via real trajectory data generated by roughly 15,000 taxis in Singapore within a 5-month period. Compared with existing work, COBWEB demonstrates a better and more stable performance and a stronger resilience to various sampling rates and data sizes.

Keywords

map update, map inference, GPS trajectories, GPS noise, low sampling rate, map matching

Discipline

Computer Sciences | Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing

First Page

927

Last Page

937

Identifier

10.1145/2750858.2804286

Publisher

ACM

City or Country

New York

Additional URL

http://dl.acm.org/citation.cfm?id=2750858.2804286

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