Author, as appears in the article.: Reyes G; Lanzarini L; Hasperué W; Bariviera AF
Department: Gestió d'Empreses
URV's Author/s: Fernández Bariviera, Aurelio
Keywords: Segmentation Perspective Intelligent transportation systems Gps trajectories Distance Clustering
Abstract: © 2020 - IOS Press and the authors. All rights reserved. Technological progress facilitates recording and collecting information on vehicles' GPS trajectories on public roads. The intelligent analysis of this data leads to the identification of extremely useful patterns when making decisions in situations related to urbanism, traffic and road congestion, among others. This article presents a GPS trajectory clustering method that uses angular information to segment the trajectories and a similarity function guided by a pivot. In order to initialize the process, it is proposed to segment the region to be analyzed in a uniform way forming a grid. The obtained results after applying the proposed method on a real trajectories database are satisfactory and show significant improvement in comparison with the methods published in the bibliography.
Thematic Areas: Statistics and probability Interdisciplinar General engineering Ensino Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Economia Computer science, artificial intelligence Ciências ambientais Ciência da computação Biotecnología Artificial intelligence Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 10641246
Author's mail: aurelio.fernandez@urv.cat
Author identifier: 0000-0003-1014-1010
Record's date: 2024-04-27
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs179644
Papper original source: Journal Of Intelligent & Fuzzy Systems. 38 (5): 5529-5535
APA: Reyes G; Lanzarini L; Hasperué W; Bariviera AF (2020). GPS trajectory clustering method for decision making on intelligent transportation systems. Journal Of Intelligent & Fuzzy Systems, 38(5), 5529-5535. DOI: 10.3233/JIFS-179644
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Article's DOI: 10.3233/JIFS-179644
Entity: Universitat Rovira i Virgili
Journal publication year: 2020
Publication Type: Journal Publications