A Map Matching Algorithm to Eliminate Miscalculation Based on Low-Sample-Rate Data
Dong Wang, Zhiwei Wang, Xiaohong Li, Zhu Xiao
Available Online June 2014.
- 10.2991/csss-14.2014.51How to use a DOI?
- GPS Trajectories; Road Network; Low-Sample-Rate Data; Spatial AnalysisIntroduction
Map-matching is the technology of aligning a sequence of user’s GPS positions with the road network on a digital map. However, there exists miscalculation in map-matching for low-sampling-rate GPS trajectories. To address this problem, this paper proposes an algorithm termed MIV-Matching for low-sample-rate GPS trajectories. To improve the accuracy in map-matching, MIV-Matching considers the process of existing algorithms for low-sample-rate GPS trajectories and then discusses and corrects the process of miscalculation. This paper also evaluates the algorithm on real life data set. Experiment results show that the MIV-Matching algorithm outperforms the related method (ST-Matching and IVMM algorithm).
- © 2014, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Dong Wang AU - Zhiwei Wang AU - Xiaohong Li AU - Zhu Xiao PY - 2014/06 DA - 2014/06 TI - A Map Matching Algorithm to Eliminate Miscalculation Based on Low-Sample-Rate Data BT - Proceedings of the 3rd International Conference on Computer Science and Service System PB - Atlantis Press SP - 219 EP - 223 SN - 1951-6851 UR - https://doi.org/10.2991/csss-14.2014.51 DO - 10.2991/csss-14.2014.51 ID - Wang2014/06 ER -