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Household travel data simulation: Application of spatial transferability of survey data.

机译:家庭旅行数据模拟:调查数据的空间可传递性的应用。

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摘要

Due to the high cost, low response rate and time-consuming data processing, few Metropolitan Planning Organizations can afford collecting household travel survey data as frequently as needed. This study tested the feasibility of the spatial transferability of the National Household Travel Survey (NHTS) data by transferring the distributions from national level to a local area after updating.;Households in the national sample from the 2001 NHTS were clustered into 11 homogeneous groups based on the factors representing those 33 explanatory variables which include potential contextual factors as well as traditional socio-economic attributes. Using an Artificial Neural Network model, clustering process was reproduced for the add-on data sets of the NHTS.;To improve the accuracy of the transferability model, Classification & Regression Tree method was employed to further split each cluster to homogeneous subgroups. Another way of improving the cluster model employed in this study was local updating, with which a small local sample had the great potential to improve the travel statistics of the base model resulted from the NHTS national sample. The parameters of the best-fitted distributions were updated using an advanced Bayesian updating method with a small sample randomly extracted from the application area.;Meanwhile, a population synthesis was used to generate the entire population for the application area with the same 33 variables which were the inputs to the transferability model. These variables were later used to assign the cluster membership to the synthetic households. Then, the updated distributions of the travel attributes were used as the sources for Monte-Carlo simulation to generate synthetic household travel survey. By linking the generated travel estimates to the synthetic population, simulated household travel data for the application context were created.;Finally, the simulated travel data were compared against the add-on sample of the NHTS in the application area. The results of the comparisons showed very good fit between the means of the simulated and the validation data. Traditionally, transportation planners believed trip rates are easier to be transferred than any other travel statistics. However, this study showed that transferability of other statistics including trip length is also very promising.
机译:由于成本高,响应率低和数据处理费时,因此几乎没有大都市规划组织能够负担得起所需的家庭旅行调查数据。这项研究通过更新更新后将分布从国家层面转移到本地区域,检验了国家家庭出行调查(NHTS)数据的空间可转移性的可行性; 2001年国家人口调查的全国样本中的住户分为11个同质组代表这33个解释变量的因素,包括潜在的背景因素以及传统的社会经济属性。使用人工神经网络模型,对NHTS的附加数据集进行了聚类过程。为了提高可传递性模型的准确性,使用分类和回归树方法将每个聚类进一步分为同质子组。改进本研究中使用的聚类模型的另一种方法是局部更新,通过这种方法,少量的本地样本具有很大的潜力来改善由NHTS国家样本产生的基本模型的出行统计。使用高级贝叶斯更新方法更新最佳拟合分布的参数,并从应用区域中随机抽取少量样本;同时,使用总体合成方法以相同的33个变量为应用区域生成整个总体,是可转移性模型的输入。这些变量后来被用来将集群成员分配给综合家庭。然后,将旅行属性的更新分布用作蒙特卡洛模拟的来源,以生成综合的家庭旅行调查。通过将生成的旅行估算值链接到综合人口,创建了针对应用程序上下文的模拟家庭旅行数据。最后,将模拟旅行数据与应用程序区域中NHTS的附加样本进行了比较。比较的结果表明,模拟方法和验证数据的均值非常吻合。传统上,运输计划人员认为旅行费率比任何其他旅行统计数据都更容易转移。但是,这项研究表明,包括行程长度在内的其他统计数据的可传递性也非常有前途。

著录项

  • 作者

    Zhang, Yong-Ping.;

  • 作者单位

    University of Illinois at Chicago.;

  • 授予单位 University of Illinois at Chicago.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 177 p.
  • 总页数 177
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;
  • 关键词

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