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Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach

机译:通过隔离链接识别关键路段并测量交通网络中全系统的稳健性:基于链接的减少容量方法

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摘要

A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled.rnIn this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.rnOur approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess' Paradox.
机译:每天在运输网络上都会发生各种相对短期的破坏性事件,例如部分洪水,能见度降低,由于天气引起的牵引危险以及人行道老化。尽管与灾难相比相对较小,但这些事件仍对交通流量产生深远的影响。迄今为止,在不同类型的网络中断研究之间以及在这些研究中所使用的方法学方法根据特定的研究目标和所建模的中断方案而有所不同的情况之间,几乎没有什么区别。rn在本文中,我们提出了一种方法学方法它采用不同的基于链路的容量破坏值来识别和排序最关键的链路,并量化运输网络中的网络健壮性。我们将演示如何客观地确定特定网络的理想容量中断范围,并介绍一种可扩展的系统范围内的性能指标,称为网络行程稳健性(NTR),可用于直接比较不同规模,拓扑和网络的网络。连接级别。我们的方法得出的结果与连接程度无关,可用于评估具有隔离链接的网络的鲁棒性。我们显示,基于容量中断级别和网络的整体连通性,系统范围内的旅行时间和网络中最关键的链接的排名可能会发生巨大变化。我们进一步表明,网络健壮性,用于建模的容量中断级别和网络连接之间的关系是非线性的,不一定直观。我们讨论关于Braess悖论的发现。

著录项

  • 来源
    《Transportation Research》 |2010年第5期|p.323-336|共14页
  • 作者单位

    Transportation Research Center, University of Vermont, 210 Colchester Avenue, Farrell Hall, Burlington, VT 05405, United States;

    School of Business Administration, University of Vermont, 55 Colchester Avenue, 310 Kalkin Hall, Burlington, VT 05405, United States;

    Transportation Research Center, University of Vermont, 210 Colchester Avenue, Farrell Hall, Burlington, VT 05405, United States;

    TransLAB (Transportation Research Lab), School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada L8S 4K1;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    network-disruption; network modeling; network Robustness Index (NRI); isolating links; link capacity reduction;

    机译:网络中断;网络建模;网络稳健性指数(NRI);隔离链接;链路容量减少;

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