| 基于AVC最小的交通行为特征研究方法 |
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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. |
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| 作者姓名： | 任挺 陈林 杨飞 晏启鹏 |
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| 作者单位： | 1. 西南交通大学交通运输与物流学院,四川成都,610031
2. 西南交通大学交通运输与物流学院，四川成都 610031; 现代城市交通技术江苏高校协同创新中心，江苏南京210096 |
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| 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 |
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| 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.
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| 关 键 词： | 渐进协方差矩阵 正交设计 随机因子设计法 意愿调查 拟合优度 |
| 收稿时间： | 2014-04-09 |
Method for Analyzing Characteristics of Travel Behavior Based on Minimum Determinant of Asymptotic Variance-Covariance |
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| 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. |
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| Authors: | REN Ting CHEN Lin YANG Fei YAN Qipeng |
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| 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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| Keywords: | asymptotic variance-covariance matrix orthogonal design random factorial design stated preference questionnaires goodness of fit |
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