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GPS trajectory clustering method for decision making on intelligent transportation systems

  • Identification data

    Identifier: imarina:6494762
    Authors:
    Reyes GLanzarini LHasperué WBariviera AF
    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.
  • Others:

    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
  • Keywords:

    Artificial Intelligence,Computer Science, Artificial Intelligence,Engineering (Miscellaneous),Statistics and Probability
    Segmentation
    Perspective
    Intelligent transportation systems
    Gps trajectories
    Distance
    Clustering
    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
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