Research on Map Matching Method Based on Hidden Markov Model

For the matching defects of the map matching algorithm based on geometry information or topological information, this paper studies a global matching algorithm based on hidden Markov model and Viterbi algorithm. The candidate segments are selected based on the error circle area, the observation probability is calculated by the distance error and the direction error, the transition probability is calculated based on the distance similarity and the variation trend of distance error, the implicit state sequence of the highest probability (i.e., the best matching track) is calculated by Viterbi algorithm. Experimental results verify the effectiveness of the proposed algorithm.