{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T15:59:34Z","timestamp":1783180774877,"version":"3.54.6"},"reference-count":41,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T00:00:00Z","timestamp":1663113600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41871320"],"award-info":[{"award-number":["41871320"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["19A172"],"award-info":[{"award-number":["19A172"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021JJ30276"],"award-info":[{"award-number":["2021JJ30276"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["CX20211000"],"award-info":[{"award-number":["CX20211000"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Project of Hunan Provincial Education Department","award":["41871320"],"award-info":[{"award-number":["41871320"]}]},{"name":"Key Project of Hunan Provincial Education Department","award":["19A172"],"award-info":[{"award-number":["19A172"]}]},{"name":"Key Project of Hunan Provincial Education Department","award":["2021JJ30276"],"award-info":[{"award-number":["2021JJ30276"]}]},{"name":"Key Project of Hunan Provincial Education Department","award":["CX20211000"],"award-info":[{"award-number":["CX20211000"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["41871320"],"award-info":[{"award-number":["41871320"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["19A172"],"award-info":[{"award-number":["19A172"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["2021JJ30276"],"award-info":[{"award-number":["2021JJ30276"]}]},{"name":"Hunan Provincial Natural Science Foundation of China","award":["CX20211000"],"award-info":[{"award-number":["CX20211000"]}]},{"name":"Postgraduate Scientific Research Innovation Project of Hunan Province","award":["41871320"],"award-info":[{"award-number":["41871320"]}]},{"name":"Postgraduate Scientific Research Innovation Project of Hunan Province","award":["19A172"],"award-info":[{"award-number":["19A172"]}]},{"name":"Postgraduate Scientific Research Innovation Project of Hunan Province","award":["2021JJ30276"],"award-info":[{"award-number":["2021JJ30276"]}]},{"name":"Postgraduate Scientific Research Innovation Project of Hunan Province","award":["CX20211000"],"award-info":[{"award-number":["CX20211000"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Road intersections are essential to road networks. How to precisely recognize road intersections based on GPS data is still challenging in intelligent transportation systems. Road intersection recognition involves detecting intersections and recognizing its scope. There are few works on intersections\u2019 scope recognition. The existing methods always focus on road intersection detection. It includes two parts: one is selecting turning points from GPS data and extracting their geometric features, another is clustering them into center coordinates of road intersections. However, the accuracy of road intersection detection still has improvement room due to two drawbacks: (1) Besides geometric features, spatial features explored from GPS data and the interactions among all features are also important to represent intersections\u2019 semantics more accurately, and (2) How to capture the points around intersections for clustering has great impact on the accuracy of intersection detection. To solve the preceding problems, we propose a novel approach for road intersection recognition via combining a classification model and clustering algorithm based on GPS data, which involves detecting the center coordinate and computing the radius of the intersection. Firstly, we distil geometric features and spatial features from historical GPS points. These features are inputted into the Extreme Deep Factorization Machine (xDeepFM) model which is applied for capturing the GPS points nearby road intersections. Secondly, the preceding points are clustered into center coordinates of road intersections by the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN). Thirdly, we present a new method of radius computing by integrating Delaunay triangulation with circle shape structure. Experiments are carried out on the GPS data of Chengdu, China. Compared with some state-of-the-art methods, our approach achieves higher accuracy on road intersection recognition based on GPS data. The precision, recall, and f-measure of our proposed center coordinates detection method are respectively 99.0%, 92.7%, and 95.8% when the matching area\u2019s radius is 30 m. Moreover, the error of the proposed radius calculation method is less than 26.5%.<\/jats:p>","DOI":"10.3390\/ijgi11090487","type":"journal-article","created":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T20:50:45Z","timestamp":1663188645000},"page":"487","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Road Intersection Recognition via Combining Classification Model and Clustering Algorithm Based on GPS Data"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5052-2582","authenticated-orcid":false,"given":"Yizhi","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"},{"name":"Hunan Key Laboratory for Service Computing and Novel Software Technology, Xiangtan 411201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rutian","family":"Qing","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"},{"name":"Hunan Key Laboratory for Service Computing and Novel Software Technology, Xiangtan 411201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"},{"name":"Hunan Key Laboratory for Service Computing and Novel Software Technology, Xiangtan 411201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuhua","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"},{"name":"Hunan Key Laboratory for Service Computing and Novel Software Technology, Xiangtan 411201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,14]]},"reference":[{"key":"ref_1","first-page":"1845","article-title":"Extraction of urban road network intersections based on low-frequency taxi trajectory data","volume":"21","author":"Li","year":"2019","journal-title":"J. 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