摘要
基于出行链理论,对居民日出行情况进行建模与仿真.将出行者分为3类,分别建立学生出行次数logistic回归模型、老年人出行次数泊松分布模型及就业者NL(数状分对数)出行选择模型.结合城市宏观社会经济数据,对模型进行仿真求解,得到不同类别出行者的出行次数.以中国中部城市郑州市为例,对模型的实用性和准确性进行验证.结果表明,通过计算机建模仿真得到的居民日平均出行次数和现状调查结果基本一致.
The number of trips is an essential part of travel characteristics of urban traffic. Based on the theory of trip chain, modeling and stimulation are used to predict the future number of trips made by urban residents. By dividing the travelers into three types, three respective models were built in the study： the logistic regression model for students, the Poisson model for the elderly and the nested-logit （NL） model for employees. Then through combining the economic data of the macro-society, the number of trips by travelers of different types and the de- tailed daily trip chain of a single person could be obtained by simulation. A real-life case of the city of Zhengzhou was used to verify the simulation and the result shows the number of trips obtained by simulation is almost in accordance with survey result, indicating that the model can provide scientific and constructive suggestions for traffic planners to make transportation predictions.
出处
《深圳大学学报（理工版）》
EI
CAS
北大核心
2012年第3期264-269,共6页
Journal of Shenzhen University(Science and Engineering)
基金
交通运输部科技项目(2008353341260)~~
