Complete vehicle coverage trajectory data is of fundamental importance to traffic signal control strategy and intelligent transport system (ITS). There are mainly two categories in traffic data collection: stationary and mobile sensing. However, neither can offer near-complete spatial and temporal coverage, especially at traffic signals. This study first proposes a full-scale automated and connected UAV (AC-UAV) system, which consists of transformable UAVs with automated landing and take-off capabilities, cooperative charging piles, and a fleet management center. Secondly, based on the developed AC-UAV system, we introduce a 3-step methodological framework: multiple vehicle detection algorithm (MVD) based on deep learning and multiple vehicle tracking (MVT) algorithm based on data feature association and trajectories reconstruction. The field experiments were conducted in Xi’an, China. The results show that the proposed framework based on the AC-UAV system is capable of conducting mobile complete traffic data analysis tasks and also feasible for large-scale automated city applications.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    AC-UAV System for Complete Vehicle Coverage Trajectory Reconstruction: Methodology Framework and Field Experiment


    Beteiligte:
    Wang, Kaiping (Autor:in) / Yang, Rong (Autor:in) / Shi, Dahu (Autor:in) / Li, Meng (Autor:in)

    Kongress:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Erschienen in:

    CICTP 2020 ; 1255-1266


    Erscheinungsdatum :

    09.12.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    SYSTEM AND METHOD FOR RECONSTRUCTION VEHICLE TRAJECTORY

    Europäisches Patentamt | 2025

    Freier Zugriff

    SYSTEM AND METHOD FOR RECONSTRUCTION VEHICLE TRAJECTORY

    LEE JIN SOO / CHANG HYUN HO / YOON BYOUNG JO et al. | Europäisches Patentamt | 2023

    Freier Zugriff

    Ares I-X Trajectory Reconstruction: Methodology and Results

    Karlgaard, Christopher D. / Beck, Roger E. / Derry, Stephen D. et al. | AIAA | 2013