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基于AVC最小的交通行为特征研究方法

任挺,  陈林,  杨飞,  晏启鹏

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文章导航 > 西南交通大学学报  > 2014 >  27(5): 824-830.
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引用本文: 任挺, 陈林, 杨飞, 晏启鹏. 基于AVC最小的交通行为特征研究方法[J]. 西南交通大学学报, 2014, 27(5): 824-830. doi: 10.3969/j.issn.0258-2724.2014.05.013
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Citation: REN Ting, CHEN Lin, YANG Fei, YAN Qipeng. Method for Analyzing Characteristics of Travel Behavior Based on Minimum Determinant of Asymptotic Variance-Covariance[J]. Journal of Southwest Jiaotong University, 2014, 27(5): 824-830. doi: 10.3969/j.issn.0258-2724.2014.05.013
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基于AVC最小的交通行为特征研究方法

doi: 10.3969/j.issn.0258-2724.2014.05.013
基金项目: 

国家自然科学基金资助项目（50908195，51178403）

教育部新世纪优秀人才支持计划资助项目（NCET-13-0977）

中央高校基本科研业务费专项资金资助项目（SWJTU11CX080，2682014CX130）

高等学校博士学科点专项科研基金资助项目（20130184110020）

详细信息
    通讯作者:

    杨飞（1980-），男，教授，博士生导师，研究方向为智能交通、交通行为，E-mail：yangfei_traffic@163.com

Method for Analyzing Characteristics of Travel Behavior Based on Minimum Determinant of Asymptotic Variance-Covariance

摘要

    摘要
  • 摘要: 为克服现有意愿调查（stated preference，SP）实验设计方法标定结果精度低的缺点，以Logit模型的渐进协方差矩阵行列式最小为目标，对选择枝属性水平组合进行迭代计算，得到相应的选择枝属性水平组合方案，设计了一种新的出行意愿调查实验设计方法.以某城市中心城区到卫星城新增地铁交通方式为例，通过分析拟合优度、参数估计标准差，对比了新方法与正交设计法的模型标定结果精度.算例结果表明，与正交设计法相比，采用本文方法得到的参数估计标准差最小，拟合优度达到0.15，提高了0.05，提高了Logit模型参数标定精度，且具有选择枝属性组合数量弹性选择的优点.

     

    Abstract: In order to overcome the low precision of the model estimation results in the existing stated preference (SP) experimental designs, a new experimental design method for SP survey was proposed. This method aims to minimize the determinant of asymptotic variance-covariance (AVC) matrix to compute iteratively the alternative attribute level combinations and then obtain the corresponding alternative attribute level combinations. A new metro connecting a city and its satellite cities was taken as the research case. Comparisons between the new design and the orthogonal design are made about the precision of model results by the goodness of fit and standard deviation of parameter estimations. The results indicate that based on the new design, the standard deviation of parameter estimations is less and the goodness of fit is 0.145, which is improved about 0.05 compared to the orthogonal design. In addition, the new design improves the precision of Logit model parameter estimation and has the advantage of the flexibility in choosing the number of combinations.

     

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    • 参考文献(16)
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出版历程
  • 收稿日期:  2014-04-09
  • 刊出日期:  2014-10-25

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