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Multi-criteria assessment for supporting freeway operations and management systems.

机译:支持高速公路运营和管理系统的多标准评估。

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摘要

Freeway traffic congestion represents an increasing concern for urban areas throughout the United States. In addition, faced with limited roadway expansion alternatives, transportation agencies are considering investment in traffic management centers (TMCs) as a more viable way to operate and manage freeways effectively. The TMCs' responsibilities include monitoring roadway conditions using the various data collection strategies and determining performance measures for freeway operations. At the same time, traffic engineers at the TMCs may react to the traffic congestion problems by implementing operational strategies. In order to provide reliable decision support for TMC freeway operations and management systems, this dissertation aims to examine the factors influencing the TMCs' investment, the effective methods for persuading the public to support TMC deployment, and the legal issues involved with deciding to deploy a TMC. Second, this research presents an innovative approach, using a multi-criteria decision framework for selecting data collection strategies by considering the limitation of data collection strategies and candidate performance measures at the same time. The multi-criteria decision framework includes establishing a statement of purpose, identifying the alternatives and their criteria, developing a screening approach using the decision makers' priorities, and multi-criteria decision models. This research suggests both qualitative and quantitative criteria that affect the quality of operational performance measures and data collection strategies; these include understanding, measurability, availability, importance, time, cost, accuracy, and reliability. Then, multi-criteria models such as Simple Additive Weight (SAW) and ELECTRE III are used to select the best freeway data collection strategies. Third, this research examines the characteristics of good performance measures, constraints for data collection strategies, current and expected daily performance measures using a modified Delphi Method and stated preference surveys from TMCs in the United States. The same proposed framework is applied to develop the individual performance measures and integrate these performance measures to evaluate the overall impacts on daily freeway operations based on TMC goals. During the discussion and presentation of the proposed framework, this dissertation uses five minute aggregated traffic data from Lane 1 on SB Loop 12 at Irving Boulevard, Irving, Texas and four lanes on SB-I35W at Alta Mesa, Fort Worh, Texas to illustrate the application of the integrated performance measures.
机译:高速公路交通拥堵代表了整个美国城市地区日益关注的问题。此外,面对有限的道路扩展选择,运输机构正在考虑对交通管理中心(TMC)进行投资,将其作为有效运营和管理高速公路的更可行方法。 TMC的职责包括使用各种数据收集策略监控道路状况,并确定高速公路运营的绩效指标。同时,TMC的交通工程师可以通过实施运营策略来应对交通拥堵问题。为了为TMC高速公路运营和管理系统提供可靠的决策支持,本文旨在研究影响TMC投资的因素,说服公众支持TMC部署的有效方法以及决定部署TMC的法律问题。 TMC。其次,本研究提出了一种创新的方法,即使用多标准决策框架来选择数据收集策略,同时考虑数据收集策略的局限性和候选绩效指标。多标准决策框架包括建立目标声明,确定备选方案及其标准,使用决策者的优先级开发筛选方法以及多标准决策模型。这项研究提出了定性和定量标准,这些标准会影响运营绩效指标和数据收集策略的质量;其中包括理解,可测量性,可用性,重要性,时间,成本,准确性和可靠性。然后,使用多标准模型(例如简单加重(SAW)和ELECTRE III)来选择最佳高速公路数据收集策略。第三,本研究使用改进的德尔菲方法研究了良好绩效测度的特征,数据收集策略的约束,当前和预期的日常绩效测度以及美国TMC的陈述偏好调查。所采用的建议框架相同,可用于开发单个性能指标并整合这些性能指标,以基于TMC目标评估对高速公路日常运营的总体影响。在讨论和介绍拟议框架的过程中,本论文使用得克萨斯州欧文市Irving Boulevard SB环路12巷1巷和得克萨斯州沃思堡Alta Mesa SB-I35W的4条巷道的五分钟汇总交通数据来说明综合绩效指标的应用。

著录项

  • 作者

    Upayokin, Auttawit.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Engineering Civil.;Transportation.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 251 p.
  • 总页数 251
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;综合运输;
  • 关键词

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