基于Box-Cox Dogit模型的公共交通分担率预测

Public Transportation Share Ratio Forecasting Based on Box-Cox Dogit Model

通过分析影响交通方式选择的外部因素和内部因素,基于最大随机效用理论,提出了城市公共交通分担率预测的非集计Box-Cox Dogit模型。针对模型的建立、参数标定以及计算过程进行了推导。最后结合杭州市的实际调查数据,进行了公共交通分担率的预测实验,独立样本检验结果表明,模型预测准确率较高。

In order to analyze the passenger flow distribution in urban area accurately,the disaggregate Box-Cox Dogit model is presented to predict the public transportation share ratio in urban area.It is carried out by analyzing the outer and inner factors that affect the choice of transportation modes and considering the random utility theory.Model building,parameter calibration and calculation process are described.Finally,the proposed model and algorithm for forecasting the public transportation share ratio are tested by using the field survey data from Hangzhou City.The results of independent sample test indicate that the model has a finer precision and stability.