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Map-matching algorithm based on the junction decision domain and the hidden Markov model

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  • Hui Qi
  • Xiaoqiang Di
  • Jinqing Li

Abstract

Map-matching technology is a key and difficult technology in the development of vehicle navigation systems. Only by correctly identifying the road segment on which the vehicle is traveling can the navigation system make the right decision. At the same time, the complexity of the road network structure and a variety of error factors have introduced great challenges to map matching and have attracted the attention of many researchers as well. This paper analyzes various map-matching algorithms, determines that the key to the matching performance is the junction matching, performs an in-depth study on the junction-matching problem, and puts forward the junction decision domain model. The model mainly involves information regarding the width of the road segment, the angle between two road segments, the accuracy of GPS and the accuracy of the road network. In this paper, we use this model to improve the map-matching algorithm based on a hidden Markov model (HMM). The experimental results show that the improved matching algorithm can effectively reduce the error rate of junction matching and improve the matching performance of a navigation system.

Suggested Citation

  • Hui Qi & Xiaoqiang Di & Jinqing Li, 2019. "Map-matching algorithm based on the junction decision domain and the hidden Markov model," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-20, May.
    • Handle: RePEc:plo:pone00:0216476
    DOI: 10.1371/journal.pone.0216476
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    Cited by:

    1. Zhengang Xiong & Bin Li & Dongmei Liu, 2021. "Map-Matching Using Hidden Markov Model and Path Choice Preferences under Sparse Trajectory," Sustainability, MDPI, vol. 13(22), pages 1-15, November.

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