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基于模糊神經網絡的地圖匹配算法

Map matching algorithm based on fuzzy neural networks

  • 摘要: 提出了基于模糊神經網絡的新的地圖匹配算法.該算法綜合了數字道路信息和GPS/DR定位信息,提取兩個重要參數作為輸入變量,即定位點到候選路段的投影距離及定位航向與候選路段方位角差.設計出了四層模糊神經網絡及改進的收斂學習規則.實驗結果表明所提出的算法能很好地匹配車輛行駛路段位置.

     

    Abstract: A novel map matching method based on fuzzy neural networks was proposed. This method integrates digital road map information and GPS/DR position data, and two important variables, the projection distance from the positioning point to the candidate link and the angle difference between GPS/DR heading and the link bearing of the candidate link, are selected as input signals for fuzzy neural networks. A four-layer fuzzy neural network was designed and the improved learning rule was acquired for the fuzzy neural network. Experimental results show that the proposed algorithm has very good performance for matching the position of car running to the correct link under normal traffic conditions.

     

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