基于意向调查数据的非集计运量预测模型估计的研究

Forecast of traffic volume on estimation of disaggregating model by stated preference data SP

如何利用假设意向调查数据 SP(Stated Preference data)构造非集计模型 ,是运量预测研究中的一个重要课题。本文以新运输方式的运量转换率预测模型为研究对象 ,通过引入假设意向调查误差项构造了新的效用函数模型 ,并对基于 SP与 RP(Revealed Preference data)组合数据的模型参数估计方法进行了深入探讨 ,最后利用日本关于磁悬浮列车新交通规划的 RP和

For appraisal of new transportation modes, passengers' stated intensions for this new mode are indispensable. However, stated intension preference data (SP data) has large bias, and a modal disaggregating model estimated by SP data only is dangerous for practical use. In this paper, bias and errors included in SP data are introduced explicitly, and the estimation procedure for these errors has successfully been developed by using questionnaire survey data. Based on the combination data of SP and RP(Revealed Preference data) for the estimated errors, an unbiased modal disaggregating (switching) model has been established. Finally, the author analyzes practically the building of Japan's MAGLEV.