Research On Urban Arterial Roads Extraction Method Based On OpenStreetMap

Road network generalization is one of the hotspots and difficulties in the field of map generalization and cartography,which has important research value.Arterial roads is an important road type of urban road network,which reflect the structure of a city and the construction framework of the road network.Arterial roads recognition and extraction has become a key step in networks generalization.Arterial roads extraction has important significance in real-time updating of road data,multi-scale expression and modeling of road network,and intelligent transportation service.And it is also a difficult problem due to the complexity of urban road network.In large-scale urban road network,arterial roads are mainly composed of parallel roads.The road lines are parallel to each other and maintain a certain distance,and its structural characteristics are obviously different from other roads.Arterial roads extraction is also a problem in large-scale map generalization.OpenStreetMap is an open source map that everyone can use and edit.Because of its openness and sharing,it has become a popular map for people all over the world.In view of this,this paper studies the arterial roads extraction problem in large-scale OSM road network.Based on the analysis of existing algorithms,in this paper,we propose a novel algorithm for arterial roads extraction.We use Longest Common Subsequence(LCSS)algorithm that measures the similarity of trajectories to extract arterial roads.The traditional LCSS algorithm is mainly used to calculate the similarity of overlapping trajectories.To solve this problem,an improved LCSS method is proposed in this paper according to the geometric and morphological characteristics of arterial roads in large-scale road network.The candidate pairs are aligned before calculating the similarity of them.The method is based on the consideration that arterial roads extraction is essentially determining the similarity of the pairs constituting the arterial road.So we can determine whether the candidate pairs are sections of an arterial road by measuring the similarity of them.Firstly,we make a pre-processing for the road network.Secondly,the candidate road set of road element is filtered by using buffer analysis,and the method of Hausdorff distance is used to perform secondary screening on it to obtain candidate pairs.Then,the alignment strategy based on translation and resampling is used to align the two line elements of the candidate pairs.Next,we use Euclidean distance to measure the similarity between points,and the similarity of candidate pairs is calculated based on LCSS.We can determine whether the candidate pairs constitute an arterial road according to the threshold.Finally,arterial roads are extracted.In order to verify the validity of the proposed method,the experiments are performed on real OSM road network.Meanwhile,we compare our method with the method based on Project Distance.The experimental results show that the method of this paper can effectively extract the arterial roads of urban road network.