A road network modeling method for map matching on lightweight mobile devices

Wu, Peili, Liu, Kuien, Zheng, Kai, Ding, Zhiming and Tan, Yuan (2015) A road network modeling method for map matching on lightweight mobile devices. Distributed and Parallel Databases, 33 2: 145-164. doi:10.1007/s10619-013-7138-2

Author Wu, Peili
Liu, Kuien
Zheng, Kai
Ding, Zhiming
Tan, Yuan
Title A road network modeling method for map matching on lightweight mobile devices
Journal name Distributed and Parallel Databases   Check publisher's open access policy
ISSN 1573-7578
Publication date 2015-06
Year available 2013
Sub-type Article (original research)
DOI 10.1007/s10619-013-7138-2
Open Access Status
Volume 33
Issue 2
Start page 145
End page 164
Total pages 20
Place of publication New York, NY, United States
Publisher Kluwer Academic Publishers
Collection year 2016
Language eng
Abstract With proliferation of lightweight mobile devices such as mobile phones and explosion of location-based social networking services, there is a growing demand for matching between geographic locations and road networks on mobile devices. Nonetheless, existing methods for map matching only focus on accuracy and/or efficiency improvement, whereas they seldom take into account the capacity for storing map data and energy consumption during the matching process. This paper presents a method that is specifically designed for lightweight mobile devices with limited storage and computing resources, thereby providing an effective solution for map matching on mobile and embedded environments. Extensive experiments were carried out to compare proposed method against traditional approaches. The results indicate that our method can cut down the storage cost for road networks by 75 % compared to traditional methods, with only 3–5 % extra running time, which demonstrates the practical usefulness and superiority of our proposal in real-world mobile applications.
Keyword Lightweight mobile device
Map matching
Map modeling
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
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