This study evaluates the effectiveness of various detection-based object-tracking algorithms to optimize accuracy and efficiency in traffic flow monitoring. Due to its high accuracy in detecting objects, YOLOv8 was chosen as the vehicle detector for this research, where precise and rapid vehicle detection was critical. Regarding object tracking, our focus centered on the evaluation of five prominent Multiple Object Tracking (MOT) algorithms, including BoTSORT, ByteTrack, DeepOCSORT, OCSORT, and StrongSORT. We introduce a comprehensive traffic urban dataset collected from intricate street networks in Danang City. Our experimental results show that the system has practical applicability in urban traffic monitoring. Notably, the best model achieves a detection accuracy of 0.721 on mAP@0.5-0.95, and the High Overlap Tracking Accuracy (HOTA) surpasses 72% for tracking performance across diverse traffic scenarios. This shows the applicability of MOT algorithms and provides a detailed view of traffic flow monitoring, especially in Danang City, Vietnam.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Optimizing traffic management in Danang: a comparative study of multi-object tracking techniques for real-time vehicle flow monitoring


    Beteiligte:
    Hai T. Ton (Autor:in) / Hung V. Nguyen (Autor:in) / Hanh T. M. Tran (Autor:in) / Tien V. Thai (Autor:in) / Phong-Phu Le (Autor:in) / Tung T. Huynh (Autor:in) / Duy-Tuan Dao (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Estimating Traffic Density in Uncertain Environment: A Case Study of Danang, Vietnam

    Doan Phuoc Mien / Tran The Vu / Ngo Van Si | DOAJ | 2023

    Freier Zugriff


    Real-Time Traffic Monitoring and Status Detection with a Multi-vehicle Tracking System

    Wang, Lu / Lam, Chan Tong / Law, K. L. Eddie et al. | TIBKAT | 2022


    Real-Time Traffic Monitoring and Status Detection with a Multi-vehicle Tracking System

    Wang, Lu / Lam, Chan Tong / Law, K. L. Eddie et al. | Springer Verlag | 2022