In response to the problem that the analysis of highway congestion in hourly units fails to accurately reflect real-time service levels, this study investigates a method for real-time grading of traffic congestion levels on highways based on video surveillance. The research employs YOLOv5 and the Deep SORT algorithm to extract vehicle trajectories and compute short-term traffic flow macro parameters (including flow rate, density, and speed) and micro parameters such as headway intervals on a one-minute basis. Using the entropy method, weights are assigned to indicators that characterize congestion states to construct a comprehensive congestion measurement index. This index is then used for real-time congestion level classification through Fuzzy C-Means (FCM) clustering, with validation performed using K-means algorithm. The results indicate that the proposed comprehensive congestion measurement index outperforms congestion indicators constructed solely from macro and micro parameters, providing a real-time assessment of traffic flow congestion status for different time periods.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Real-Time Classification of Freeway Traffic Congestion Levels Based on Surveillance Video


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Liu, Jun (editor) / Wang, Yongcai (editor) / Wu, Bin (editor) / Jiang, Zehao (editor) / Xiao, Yao (editor) / Fu, Chuanyun (author) / Liu, Jinzhao (author) / Lu, Zhaoyou (author) / Bai, Wei (author)

    Conference:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Publication date :

    2025-03-16


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Renaissance: a real-time freeway network traffic surveillance tool

    Yibing Wang, / Papageorgiou, M. / Messmer, A. | IEEE | 2006


    IMM/EKF filter based classification of real-time freeway video traffic without learning

    Ouessai, Asmâa / Keche, Mokhtar | Taylor & Francis Verlag | 2022


    A study of freeway traffic congestion

    Drew, Donald Richard | TIBKAT | 1964


    Freeway traffic surveillance and control

    Isaksen, L. / Payne, H.J. | Tema Archive | 1973


    Analyzing Freeway Traffic under Congestion: Traffic Dynamics Approach

    Nam, D. H. / Drew, D. R. | British Library Online Contents | 1998