多特征约束下的复杂交叉路口主辅路识别

主干道、辅路的准确识别对于实现复杂交叉路口的自动综合至关重要。传统方法多依赖于路段的笔直程度和弯曲程度描述路口的主干道和辅路,然而复杂交叉路口结构错综复杂、形态变化多样,仅依赖这两种特征进行主辅路识别的准确度有限,且部分形态相似的主辅路无法识别。为此,本文提出了一种多特征约束下的复杂交叉路口主辅路识别方法。首先提取复杂交叉路口的特征点,根据特征点对弧段进行打断,依据路段的笔直程度识别出平行弧段;然后依据道路延展性、角度、距离等特征识别平行簇获取复杂交叉路口中的主干道;最后通过紧凑度和距离关系识别匝道获取复杂交叉路口中的辅路。以南京OSM城市路网为例的试验表明,本文方法能够准确识别出复杂交叉路口的主干道和辅助路段,识别精度分别达到93.60%和89.43%。

Indentification of main and auxiliary roads at complex intersections under multiple feature constraints

Accurate identification of main roads and auxiliary roads is essential for the automatic synthesis of complex intersections. Traditional methods mostly rely on the straightness and curvature of road sections to describe the main roads and auxiliary roads at intersections. However, complex intersections have intricate structures and various morphological changes. Reliance on these two features for the identification of main and auxiliary roads is limited, and some forms Similar main branches cannot be identified. Therefore, this paper proposes a method for identifying main and auxiliary roads at complex intersections with multiple feature constraints. First extract feature points of complex intersections, interrupt arc segments based on feature points, identify parallel arc segments based on the straightness of the road segments, and then identify parallel clusters based on road ductility, angle, distance and other features to obtain complex intersections. Arterial roads, followed by identifying ramps on compactness and distance relationships to obtain auxiliary roads at complex intersections. Taking Nanjing OSM urban road network as an example, experiments show that the method in this paper can accurately identify the main road and auxiliary road sections of complex intersections, and the recognition accuracy is 93.60% and 89.43%, respectively.