中文摘要：

为了减少传统模型的非相关选择方案相互独立特性引起的预测误差,按照交通方式服务对象的不同,将交通方式划分为公共交通和私人交通两类,具有类似性的出行方式归并为一个层次,采用分层Logit模型的形式,利用北京市实际调查数据对模型进行标定.通过计算得到对方式选择层次1和层次2有影响的离散变量分别为年龄、是否有私家车、支付方式以及年收入、出行目的;连续变量为时间和费用.结果显示模型具有较高的精度.

英文摘要：

In order to reduce the forecasting error caused by the independence form irrelevant alternatives of traditional model,traffic modals are divided into public traffic and private traffic according to the service objects.Traffic modals that have similar factors are classified into the same arrangement.The nested modal split model is demarcated by the investigational data in Beijing.According to the calculating results,discrete factors that affect arrangement 1and 2are in turn the age,have a car or not,pay mode and income,travel aim.Continuous factors are travel time and cost.According to the results,the precision of the model introduced in this paper is high.