Articles producció científica> Gestió d'Empreses

Proposal for a Pivot-Based Vehicle Trajectory Clustering Method

  • Identification data

    Identifier: imarina:9241751
    Authors:
    Reyes, GaryLanzarini, LauraHasperue, WaldoBariviera, Aurelio F.
    Abstract:
    Given the large volume of georeferenced information generated and stored by many types of devices, the study and improvement of techniques capable of operating with these data is an area of great interest. The analysis of vehicular trajectories with the aim of forming clusters and identifying emerging patterns is very useful for characterizing and analyzing transportation flows in cities. This paper presents a new trajectory clustering method capable of identifying clusters of vehicular sub-trajectories in various sectors of a city. The proposed method is based on the use of an auxiliary structure to determine the correct location of the centroid of each group or set of sub-trajectories along the adaptive process. The proposed method was applied on three real databases, as well as being compared with other relevant methods, achieving satisfactory results and showing good cluster quality according to the Silhouette index.
  • Others:

    Author, as appears in the article.: Reyes, Gary; Lanzarini, Laura; Hasperue, Waldo; Bariviera, Aurelio F.;
    Department: Gestió d'Empreses
    URV's Author/s: Fernández Bariviera, Aurelio
    Keywords: Time Similarity Perspective Patterns Pattern recognition Machine learning (artificial intelligence) Gps data Geographic information science Distance Data and data science Artificial intelligence and advanced computing applications
    Abstract: Given the large volume of georeferenced information generated and stored by many types of devices, the study and improvement of techniques capable of operating with these data is an area of great interest. The analysis of vehicular trajectories with the aim of forming clusters and identifying emerging patterns is very useful for characterizing and analyzing transportation flows in cities. This paper presents a new trajectory clustering method capable of identifying clusters of vehicular sub-trajectories in various sectors of a city. The proposed method is based on the use of an auxiliary structure to determine the correct location of the centroid of each group or set of sub-trajectories along the adaptive process. The proposed method was applied on three real databases, as well as being compared with other relevant methods, achieving satisfactory results and showing good cluster quality according to the Silhouette index.
    Thematic Areas: Transportation science & technology Transportation Mechanical engineering Engineering, civil Engenharias iii Engenharias ii Engenharias i Civil and structural engineering
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: aurelio.fernandez@urv.cat
    Author identifier: 0000-0003-1014-1010
    Record's date: 2024-09-07
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://journals.sagepub.com/doi/abs/10.1177/03611981211058429?journalCode=trra
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Transportation Research Record. 2676 (4): 281-295
    APA: Reyes, Gary; Lanzarini, Laura; Hasperue, Waldo; Bariviera, Aurelio F.; (2022). Proposal for a Pivot-Based Vehicle Trajectory Clustering Method. Transportation Research Record, 2676(4), 281-295. DOI: 10.1177/03611981211058429
    Article's DOI: 10.1177/03611981211058429
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2022
    Publication Type: Journal Publications
  • Keywords:

    Civil and Structural Engineering,Engineering, Civil,Mechanical Engineering,Transportation,Transportation Science & Technology
    Time
    Similarity
    Perspective
    Patterns
    Pattern recognition
    Machine learning (artificial intelligence)
    Gps data
    Geographic information science
    Distance
    Data and data science
    Artificial intelligence and advanced computing applications
    Transportation science & technology
    Transportation
    Mechanical engineering
    Engineering, civil
    Engenharias iii
    Engenharias ii
    Engenharias i
    Civil and structural engineering
  • Documents:

  • Cerca a google

    Search to google scholar