COBWEB: A Robust Map Update System using GPS Trajectories

• Main Authors: Zhangqing Shan, Hao Wu, Weiwei Sun, ZHENG, Baihua
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: map update; map inference; GPS trajectories; GPS noise; low sampling rate; map matching; Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/2697; https://ink.library.smu.edu.sg/context/sis_research/article/3697/viewcontent/cobweb_paper.pdf
• Institution: Singapore Management University

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.