In order to predict the traffic parking demand in the city, a prediction model based on partial least squares method is proposed. With the relationship between land use and traffic generation and attraction, this paper studies land use factors, such as the type of land use, land area, population and employment, land use intensity, the relevance between the generation and attraction of transportation. With the data of the traffic district of Binjiang New Area in Changsha, the capital of Hunan Province of China, the partial least squares regression model is used to predict the traffic parking generation and attraction of each traffic area in the future year, and the fitting results of the model are analyzed in depth by using R software. The results show that the model can be utilized to forecast the traffic parking volume of the traffic district in the future year, and it is verified that there is a close relationship between the traffic parking volume and urban land use.


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    Titel :

    Traffic Parking Forecast of Traffic Area Based on Partial Least Squares Method


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qian, Zhihong (Herausgeber:in) / Jabbar, M.A. (Herausgeber:in) / Cheung, Simon K. S. (Herausgeber:in) / Li, Xiaolong (Herausgeber:in) / Song, Rui (Autor:in) / Qin, Wanen (Autor:in) / Shi, Wen (Autor:in) / Xue, Xinjian (Autor:in)

    Kongress:

    INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND APPLICATIONS ; 2022 ; Wuhan, China December 16, 2022 - December 18, 2022



    Erscheinungsdatum :

    27.07.2023


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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