Trip distribution is an important step of the four-phase method in transportation demand forecasting. It is affected by many factors. First, factors influencing vehicle trip distribution are analyzed and the results show that location potential, traffic impedance, trip production, and trip attraction play an important role. Second, an aggregation scale factor of the traffic zone is evaluated by fuzzy algorithm and the zone accessibility is calculated, and then, the location potential that is determined by the aggregation scale factor and zone accessibility is obtained. Third, traffic impedance based on travel time is determined based on analyzing the influences of traffic flow discontinuation, bicycles, pedestrians, and width of lanes. Finally, the trip distribution forecasting model based on the BP neural network which takes location potential, traffic impedance, trip production, and trip attraction as input parameters and the result of trip distribution as output parameters is established. The test shows that the forecasting result fits well with the survey data. Thus, the BP neural network model can be used for trip distribution forecasting with high prediction accuracy.


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    Title :

    A Study on Vehicle Trip Distribution Forecasting Based on BP Neural Network


    Contributors:
    Meng, Xiang-hai (author) / Liu, Qing (author) / Du, Ying-chun (author) / Lu, Jian (author)

    Conference:

    Ninth International Conference of Chinese Transportation Professionals (ICCTP) ; 2009 ; Harbin, China


    Published in:

    Publication date :

    2009-07-23




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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