In recent years, the growth of the overall economy and the improvement of residents' consumption levels have led to rapid growth in demand for air passenger transport. Specially, large hub airports generate enormous passenger traffic, and the mobility of people exhibits traits of high dynamics, high density, varying time distribution, and significant service pressure. To address the issue of whether taxi drivers wait for passengers and return to the airport or not, the taxi passenger data observed by the taxi management of Beijing Capital International Airport is modelled and analyzed. Given the fluctuation in airport passenger numbers and taxi driver profit conditions, it is feasible to construct a hierarchical model through the implementation of the hierarchical analysis technique. This model will comprise a decision-making model that ensures the selection of the appropriate taxi drivers at the airport that predicts the profits of both long and short distance drivers, alongside simulation. Subsequently, and feasibility analyses are then conducted to refine decision making practices. The correlation between key factors, such as the taxi driver's duration of stay at the airport, is then analyzed to compare profits from both Options so that the driver can ultimately make the decision. Ultimately, this profit-driven system enhances profitability and labor efficiency, facilitating optimal decision-making for taxi drivers.


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    Title :

    Analysis of taxi drivers' decisions at the airport based on a profit-driven system


    Contributors:

    Conference:

    Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024) ; 2024 ; Kaifeng, China


    Published in:

    Proc. SPIE ; 13219


    Publication date :

    2024-07-21





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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