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。
A combined stochastic user equilibrium model for simultaneous prediction of trip distribution and trip assignment on large-scale networks is developed.
及时准确地进行交通流短时预测是智能交通系统，尤其是其先进的交通管理系统与先进的出行者信息系统研究的关键内容之一。
Accurate short-term traffic flow forecasting is becoming a crucial step in its research, especially, for its Advanced traffic Management System and Advanced Traveler Information System research.
表明此方法操作简单，在实际交通规划的出行分布预测阶段，具有一定参考价值。
The method is simple and it has some actual value in the stage of trip distribution forcast in transport planning.
出行生成模型：交通小区通达性和便利程度在很大程度上影响着居民的交通生成量，传统的出行生成预测模型无法反映这一特征。
This model demonstrates how the socioeconomic variable, traffic serving level and the socioeconomic variable around traffic zones contributes to the trip generations.
该修正方法可预测信息提供条件下的出行需求，对城市交通需求管理具有指导意义。
The modifyed approach could be used to forecast the travel demand with provided information and has significance for urban traffic demand.
交通方式选择是出行行为中最基本的选择行为，对它的分析和预测是交通规划的主要内容之一。
Trip mode choice is the most basic process of travelling, and its analysis and prediction is one of the main elements of traffic and transportation planning.
力图从居民出行特征的角度诊断现状交通问题、预测未来交通发展趋势以及提出相应的交通对策。
The actual traffic problems, forecast transportation trend and raise improving Suggestions from the Angle of person trip characteristics have been discussed.
根据土地利用、人口密度和公交站点覆盖率确定各交通区的公交分担率，得出交通区公交出行量，再应用最大熵原理进行公交出行分布预测。
According to the land use, population density and coverage percentage of the public transport station, the sharing of public transport among traffic zones and their travel demand can be determined.
利用模型预测出行量在各种交通方式中分配的比率，分析不同服务属性对出行者选择交通方式的影响。
By this model, one can predict a ratio of different kinds of transportation method assigned, and analyze what influence different properties of the services have on the executor.
合理的投资决策需要对未来中国交通拥挤的都市进行出行预测。
Wise investment decisions require forecasts of future urban travel in China's congested cities.
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。
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.
摘要：居民出行分布预测是城市交通需求分析中的一个重要环节，对城市交通需求分析起着承前启后的作用。
Absrtact: The forecast of inhabitant trip distribution is an important part, and play a connecting role, in analysis of city traffic demand.
摘要：居民出行分布预测是城市交通需求分析中的一个重要环节，对城市交通需求分析起着承前启后的作用。
Absrtact: The forecast of inhabitant trip distribution is an important part, and play a connecting role, in analysis of city traffic demand.
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