Conference Proceeding Article
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.
map update, map inference, GPS trajectories, GPS noise, low sampling rate, map matching
Computer Sciences | Databases and Information Systems
Data Management and Analytics
UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
City or Country
Zhangqing Shan; Hao Wu; Weiwei Sun; and ZHENG, Baihua.
COBWEB: A Robust Map Update System using GPS Trajectories. (2015). UbiComp '15: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing. 927-937. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2697