A method for identifying urban road intersections considering the merging of parallel lanes
Year: 2025
Type: article
Abstract: Road intersections are crucial nodes in urban networks, where transportation lanes converge and socioeconomic activity is concentrated. Although methods to identify road intersections using raster maps, satellite images and trace data have been explored, challenges in accuracy and consistency remain. This paper proposes a method for identifying intersections based on OpenStreetMap data, which records networks at the lane level. Unlike geometric line intersections in OpenStreetMap, the identified intersections ‘summarize’ parallel lanes and incorporate branch information, such as counts and orientations. The proposed method uses a vector-raster fusion approach to initially locate intersections, followed by hierarchical geometric configuration to improve accuracy and extract branch data. Experimental results show that the method effectively handles complex road networks in various cities, accurately identifying intersections and their branches. Experiments conducted on OpenStreetMap data from 7 cities yielded over 97% precision and 99% recall, outperforming the state-of-the-art methods. Additionally, lane synthesis at intersections achieved 98.84% precision and 96.24% recall. Urban characteristics can be quantitatively analyzed based on the identified road intersections. For instance, the proportion of four-way road intersections in New York is 52.2%, whereas it is 8.9% in London, which may be attributed to the differing urban histories of these cities.
Source: Figshare
Authors: Tang, Zihao, Shu, Yucheng, Zhong, Yue, Wang, Dajiang, Chen, Renyu, Ren, Anxun, Yue, Songshan, Wen, Yongning
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6977395378
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