基于向量识别的启发式地图匹配算法

Dongdong Wu, T. Zhu, Weifeng Lv, Xin Gao
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引用次数: 36

摘要

传统的地图匹配算法主要采用增量法和全局法两种方法。两者都有各自的优点和缺点:全局地图匹配算法的匹配结果更好,而增量算法的匹配结果质量更差。综合考虑这两种传统算法,本文提出了一种基于向量识别的启发式地图匹配算法。首先,该算法采用类似于A*算法的启发式搜索方法,利用几何运算形成约束,将与车辆GPS点形成的矢量与专用路网进行比较,启发式搜索并选择车辆可能的行驶路线;其次,通过计算地图匹配权值,对所有可能的路径进行全局比较,选择最优路径;测试结果表明,在复杂路网条件下处理大规模GPS跟踪数据时,该算法在精度和计算速度上都是高效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Heuristic Map-Matching Algorithm by Using Vector-Based Recognition
The traditional map-matching algorithms mainly use two methods: the incremental method and the global method. Both of them have advantages and disadvantages of themselves: while the global map-matching algorithm produces better matching results, the incremental algorithm produces results of lower quality faster. All things considering the two traditional algorithms, this paper proposes a heuristic map-matching algorithm by using vector-based recognition. Firstly, the algorithm uses the heuristic search method which is similar to A* algorithm, and it makes use of geometric operation to form the restriction, and make the comparison between the vector formed with the vehicular GPS points and the special road network to heuristicly search and select the vehicular possible traveling routes. Secondly, it globally compares the vehicular every possible route by calculating the map-matching weight, and then chooses the optimal one. The result of testing demonstrates the efficiency of the algorithm both at accuracy and computational speed when handling the large-scale data of GPS tracking data even under the complex road network conditions.
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