A combined stochastic user equilibrium model for simultaneous prediction of trip distribution and trip assignment on large-scale networks is developed.
提出了适用于大规模网络的组合随机用户平衡模型，能够同时预测出行分布和交通分配。
The traditional travel demand model usually bases itself on the od study survey and employs a 4-step modeling process including trip generation, trip distribution, mode choice and assignment.
传统的交通需求4阶段分析模型大多基于各类出行的起讫点调查(OD调查)，建立出行生成、出行分布、出行方式选择和流量分配的4阶段预测模式。
Having established the mathematical model suitable to the distribution of the trip and the average trip distance of the residents in metropolises and determined the data-taking scope.
建立了适合我国特大城市居民出行分布和平均出行距离的数学模型，确定了参数的取值范围。
Generally speaking, a truck model includes three submodels of trip generation, trip distribution, and trip assignment.
卡车模型一般由出行发生、出行分布和出行分配这三个子模型组成。
For new urban distracts, the traditional 4-phase transportation demand forecasting model can not be used, because of the lack of the trip production and distribution phase data.
对于规划新城区，传统的四阶段交通需求预测方法难以使用，因为交通生成和分布预测所必需的条件无法满足。
For new urban distracts, the traditional 4-phase transportation demand forecasting model can not be used, because of the lack of the trip production and distribution phase data.
对于规划新城区，传统的四阶段交通需求预测方法难以使用，因为交通生成和分布预测所必需的条件无法满足。
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