{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T16:21:10Z","timestamp":1762273270170,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T00:00:00Z","timestamp":1709078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Persistently, urban regions grapple with the ongoing challenge of vehicular traffic, a predicament fueled by the incessant expansion of the population and the rise in the number of vehicles on the roads. The recurring challenge of vehicular congestion casts a negative influence on urban mobility, thereby diminishing the overall quality of life of residents. It is hypothesized that a dynamic clustering method of vehicle trajectory data can provide an accurate and up-to-date representation of real-time traffic behavior. To evaluate this hypothesis, data were collected from three different cities: San Francisco, Rome, and Guayaquil. A dynamic clustering algorithm was applied to identify traffic congestion patterns, and an indicator was applied to identify and evaluate the congestion conditions of the areas. The findings indicate a heightened level of precision and recall in congestion classification when contrasted with an approach relying on static cells.<\/jats:p>","DOI":"10.3390\/ijgi13030073","type":"journal-article","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T07:56:02Z","timestamp":1709106962000},"page":"73","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Method for the Identification and Classification of Zones with Vehicular Congestion"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3711-1906","authenticated-orcid":false,"given":"Gary","family":"Reyes","sequence":"first","affiliation":[{"name":"Carrera de Sistemas Inteligentes, Universidad Bolivariana del Ecuador, Campus Dur\u00e1n Km 5.5 v\u00eda Dur\u00e1n Yaguachi, Dur\u00e1n 092405, Ecuador"},{"name":"Facultad de Ciencias Matem\u00e1ticas y F\u00edsicas, Universidad de Guayaquil, Cdla. Universitaria Salvador Allende, Guayaquil 090514, Ecuador"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4164-5839","authenticated-orcid":false,"given":"Roberto","family":"Tolozano-Benites","sequence":"additional","affiliation":[{"name":"Carrera de Sistemas Inteligentes, Universidad Bolivariana del Ecuador, Campus Dur\u00e1n Km 5.5 v\u00eda Dur\u00e1n Yaguachi, Dur\u00e1n 092405, Ecuador"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7027-7564","authenticated-orcid":false,"given":"Laura","family":"Lanzarini","sequence":"additional","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica LIDI (Centro CICPBA), Facultad de Inform\u00e1tica, Universidad Nacional de La Plata, Buenos Aires CP 1900, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5926-8827","authenticated-orcid":false,"given":"C\u00e9sar","family":"Estrebou","sequence":"additional","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica LIDI (Centro CICPBA), Facultad de Inform\u00e1tica, Universidad Nacional de La Plata, Buenos Aires CP 1900, Argentina"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1014-1010","authenticated-orcid":false,"given":"Aurelio F.","family":"Bariviera","sequence":"additional","affiliation":[{"name":"Department of Business & ECO-SOS, Universitat Rovira i Virgili, Av. 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