Distributed acoustic sensing systems can obtain information about road vibration caused by vehicle driving vibration on highways. By characterizing the vehicle driving vibration data, a highway vehicle driving vibration detection scheme based on ridge-LASSO regression is proposed. Firstly, using the random forest's out-of-bag error criterion for vibration signal multi-feature selection, to prove the validity of the feature quantity used to characterize the highway vibration signal, and then the multi-feature quantity values of multiple measurement areas are composed into a data matrix, and then finally the ridge-LASSO regression algorithm is used to detect the vehicles travelling on the highway to obtain the vehicle's trajectory. The experiment proves that the method can effectively detect vehicles on the highway


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    Titel :

    Highway vehicle detection based on ridge-LASSO regression


    Beteiligte:
    Du, Kelin (Herausgeber:in) / Mohd Zain, Azlan bin (Herausgeber:in) / Kou, Xuewei (Autor:in) / Du, Qingguo (Autor:in) / Huang, Longting (Autor:in) / Wang, Honghai (Autor:in) / Li, Zhengying (Autor:in)

    Kongress:

    Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024) ; 2024 ; Kuala Lumpur, Malaysia


    Erschienen in:

    Proc. SPIE ; 13250


    Erscheinungsdatum :

    23.08.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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