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Search, information, learning, and knowledge in travel decision-making: A positive approach for travel behavior and demand analysis.

机译:出行决策中的搜索,信息,学习和知识:出行行为和需求分析的积极方法。

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摘要

Travel demand models provide a foundation for transportation systems analysis, transportation planning, and policy studies. They are based on theories of travel behavior that describe individuals' travel decision-making processes, which are complex, constrained, multidimensional, and dynamic. The normative theorization of travel behavior, seen in a long thread of research that assumes perfection information and rationality, does not meet the emerging needs of developing advanced travel demand models both for its lack of behavioral realism in complex decision situations and for computational difficulties as choice dimensions increase.; This dissertation addresses this fundamental issue and aims to develop a coherent positive approach for travel behavior and demand analysis. First, a positive theory of travel behavior is developed, which avoids assumptions of complete information and perfect rationality. Instead, the proposed SILK theory defines and illustrates subjective factors related to the travel decision-making process, including spatial knowledge, belief, information acquisition, learning, perception, and heuristics, and explains how travel behavior is formed and adjusted as the result of interactions among these factors. In addition, the SILK theory combines quantified spatial knowledge, behavioral search rules, and Bayesian learning principles to provide a quantitative framework for developing positive travel demand models.; This research also identifies modeling methods and data needs for the proposed positive approach. A behavioral route choice model is specified, estimated, and validated with positive principles. Modeling methods employed include knowledge representation and acquisition for empirically deriving individual search and decision rules, and agent-based simulation for linking individual behavior to system-level demand. Two empirical studies collect process data, defined as observations of the decision-making process, for the model development using survey and experimental techniques. This modeling work demonstrates that the SILK theoretical framework is able to produce fully operational models of travel decisions. It also shows what and how process data can be collected for constructing positive travel demand models.; The behavioral model developed is also applied to two typical planning and policy analysis scenarios, so that some practical conclusions can be drawn. (Abstract shortened by UMI.)
机译:出行需求模型为运输系统分析,运输计划和政策研究提供了基础。它们基于描述个人旅行决策过程的旅行行为理论,这些过程是复杂的,受约束的,多维的和动态的。长期旅行研究中的行为规范化理论假设完美的信息和合理性,不能满足发展高级旅行需求模型的新兴需求,这既是由于其在复杂决策情况下缺乏行为现实性,又是因为计算困难作为选择尺寸增加。本文致力于解决这一基本问题,旨在为旅行行为和需求分析开发一种连贯的积极方法。首先,发展了一种积极的旅行行为理论,该理论避免了对完整信息和完美理性的假设。相反,提出的SILK理论定义并说明了与旅行决策过程相关的主观因素,包括空间知识,信念,信息获取,学习,感知和启发式,并解释了交互作用如何形成和调整旅行行为这些因素之中。此外,SILK理论结合了量化的空间知识,行为搜索规则和贝叶斯学习原理,为开发积极的旅行需求模型提供了定量框架。这项研究还确定了所提出的积极方法的建模方法和数据需求。行为路线选择模型是根据积极原则指定,估算和验证的。所采用的建模方法包括:知识表示和获取,以经验方式得出个人搜索和决策规则;以及基于代理的仿真,以将个人行为与系统级需求联系起来。两项实证研究收集过程数据(定义为对决策过程的观察),以使用调查和实验技术进行模型开发。这项建模工作表明,SILK理论框架能够产生出行决策的完整运营模型。它还显示了什么以及如何收集过程数据以构建积极的旅行需求模型。开发的行为模型还应用于两个典型的计划和策略分析方案,因此可以得出一些实际的结论。 (摘要由UMI缩短。)

著录项

  • 作者

    Zhang, Lei.;

  • 作者单位

    University of Minnesota.;

  • 授予单位 University of Minnesota.;
  • 学科 Engineering Civil.; Transportation.; Urban and Regional Planning.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 241 p.
  • 总页数 241
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;综合运输;区域规划、城乡规划;
  • 关键词

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