With the increase in urban population and the number of car users, traffic congestion has become a stubborn problem that is difficult to completely cure in major cities. It has brought significant pressure to urban transportation, leading to an increase in traffic accidents and exacerbation of social conflicts. In order to alleviate the adverse effects of traffic congestion, it is necessary to make reasonable use of trajectory data developed under the background of information technology, the Internet of Things, and positioning technology. This article first elaborates on the classification and advantages and disadvantages of trajectory data, then analyzes the application scenarios of trajectory data, and finally studies methods for mining trajectory data information, which can effectively identify traffic congestion points and congested road areas, help drivers quickly change their driving routes, and enable relevant departments to respond quickly.


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    Titel :

    Research on Urban Intelligent Transportation System Based on Track Big Data


    Weitere Titelangaben:

    Lect. Notes on Data Eng. and Comms.Technol.


    Beteiligte:
    Jansen, Bernard J. (Herausgeber:in) / Zhou, Qingyuan (Herausgeber:in) / Ye, Jun (Herausgeber:in) / Zhang, Yili (Autor:in)

    Kongress:

    International Conference on Cognitive based Information Processing and Applications ; 2023 ; Changzhou, China November 02, 2023 - November 03, 2023



    Erscheinungsdatum :

    31.05.2024


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Track-Sharing for Urban Transportation

    R. Rechel / F. Graves / J. Garcia et al. | NTIS | 1970


    Track-Sharing for Urban Transportation

    R. Rechel / F. Graves | NTIS | 1970



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