With the rapid economic growth and urbanization in China, the demand for urban residents to travel continues to grow, and most cities in China have started to give priority to the development of urban public transportation. More complex residents’ travel makes a series of problems such as congestion in stations and carriages, and unbalanced passenger flow between stations, which gradually become prominent. To fully grasp the travel characteristics of passengers is an inevitable requirement to understand the passenger flow. Therefore, this research starts from the travel chain of passengers, explores the travel pattern of rail transit passengers at collective and individual levels by mining the smart card data of subway passengers, then defines and portrays the passenger portrait indexes, calculates and analyzes the correlation between the spatial and temporal elements of passenger travel, including travel date, time periods, travel OD and so on, and finally compares the travel characteristics of commuters and non-commuters.


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    Title :

    Rail Transit Passenger Trip Correlation Analysis Based on Travel Chain—Taking Guangzhou as an Example


    Additional title:

    Mechan. Machine Science


    Contributors:
    Li, Shaofan (editor) / Yu, Zhitian (author) / Zou, Liang (author) / He, Minhui (author)

    Conference:

    International Conference on Computational & Experimental Engineering and Sciences ; 2023 ; Shenzhen, China May 26, 2023 - May 29, 2023



    Publication date :

    2024-01-25


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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