• ISSN 0258-2724
  • CN 51-1277/U
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Volume 28 Issue 3
Jun.  2015
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Article Contents
Journal of Southwest Jiaotong University  > 2015  >  28(3): 497-503.
SHEN Jingwei, ZHOU Tinggang, ZHANG Hongtao. A Map-Matching Algorithm Based on Improved AOE Network for Low Frequency Floating Car Data[J]. Journal of Southwest Jiaotong University, 2015, 28(3): 497-503. doi: 10.3969/j.issn.0258-2724.2015.03.018
Citation: SHEN Jingwei, ZHOU Tinggang, ZHANG Hongtao. A Map-Matching Algorithm Based on Improved AOE Network for Low Frequency Floating Car Data[J]. Journal of Southwest Jiaotong University, 2015, 28(3): 497-503. doi: 10.3969/j.issn.0258-2724.2015.03.018
shu

A Map-Matching Algorithm Based on Improved AOE Network for Low Frequency Floating Car Data

doi: 10.3969/j.issn.0258-2724.2015.03.018
  • Received Date: 03 Dec 2014
  • Publish Date: 25 Jun 2015
    Abstract
  • Due to the long time interval characteristic, the existing map-matching algorithms are not suitable for the low-frequency FCD (floating car data). By analyzing local map-matching algorithms and global map-matching algorithms, and overall considering the FCD trace, a map-matching algorithm for low-frequency FCD based on improved AOE (activity on edge) network was proposed. Firstly, intersection analysis between a buffer around a GPS point and road segments was carried out to acquire the candidate road segments and candidate map-matching points. Secondly, quadtree spatial index and Dijkstra algorithm were introduced to obtain the shortest path between the adjacent candidate map-matching points. Thirdly, the improved AOE network was built to search the FCD shortest path and the map-matching points were acquired. Lastly, the proposed algorithm was evaluated in terms of time efficiency and accuracy. Results show that the accuracy of the proposed algorithm is 95.3%, and the total program execution time is 96.8 s. The accuracy is respectively 13.6% and 2.8% higher than that of the local map-matching algorithm and global map-matching algorithm.

     

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