马超, 孙群, 陈换新, 温伯威. 利用路段分类识别复杂道路交叉口[J]. 武汉大学学报 ( 信息科学版), 2016, 41(9): 1232-1237. DOI: 10.13203/j.whugis20160073
引用本文: 马超, 孙群, 陈换新, 温伯威. 利用路段分类识别复杂道路交叉口[J]. 武汉大学学报 ( 信息科学版), 2016, 41(9): 1232-1237. DOI: 10.13203/j.whugis20160073
MA Chao, SUN Qun, CHEN Huanxin, WEN Bowei. Recognition of Road Junctions Based on Road Classification Method[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1232-1237. DOI: 10.13203/j.whugis20160073
Citation: MA Chao, SUN Qun, CHEN Huanxin, WEN Bowei. Recognition of Road Junctions Based on Road Classification Method[J]. Geomatics and Information Science of Wuhan University, 2016, 41(9): 1232-1237. DOI: 10.13203/j.whugis20160073

利用路段分类识别复杂道路交叉口

Recognition of Road Junctions Based on Road Classification Method

  • 摘要: 道路网数据中微观结构的识别对于多尺度路网建模、步行导航等至关重要。复杂道路交叉口是重要的道路微观结构之一,针对目前道路复杂交叉口基于几何形状描述与图形匹配识别方法存在的不足,从复杂交叉口识别与化简的角度出发,提出了一种利用路段分类进行复杂道路交叉口识别与化简的方法。该方法首先通过点密度聚类的方法对道路交叉口进行定位,然后利用路段的规模、形状和属性等特征构建特征空间,将交叉口的识别作为一种区分主干路段与辅助路段的两类分类问题,利用支持向量机的方法对交叉口区域内的路段进行分类,从而完成交叉口的识别与化简。利用开放街道地图(Open Street Map)数据进行实验,结果表明,该方法能够有效地识别道路交叉口。

     

    Abstract: The recognition of microstructures such as road junctions in road networks is of importance for multi-scale road modeling and pedestrian navigation. Aiming to resolve deficiencies in the current recognition methodsfor geometric shape description and shape matching with complex road junctions, the paper presents a road junction recognition method based on the classification of roads and starting with recognition and reduction. Firstly, junctions are located by the node cluster density detection. Then the characteristic vectors are built by analyzing and quantifying the sizes, shapes, and attributes of roads; treating this issue as a two-class classification problem for differentiating main roads and the auxiliary sections, solved by using a support vector machine. Using Open Street Map data for experimental verification, our results show that this method can effectively recognize road junctions.

     

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