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Weighted ego network for forming hierarchical structure of road networks

机译:加权自我网络,用于形成道路网络的层次结构

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摘要

Studies on the structural properties of road network and its close relationship with the traffic flow distribution have received intensive interdisciplinary attention. However, most of these attempts were theoretical. It is also a challenge to understand the relationship between the structure and morphology of a road network and peoples' movement. We developed a new methodology to deal with this challenge in this study. The first attempt was to apply the ego network analysis (which is rooted in social science) to the formation of hierarchical road networks. Then, the ego network was improved to become weighted ego network by assigning a weight to each of the links in a network. A measure called weighted average centrality rank is developed to define the order of links in a complex network. The ego network and the weighted ego network are both evaluated with a notional network and two sets of real-life road networks. Traffic flow data were used as a benchmark for the evaluation of the two approaches. The results show that they both perform well. But the hierarchies formed by weighted ego network analysis are more consistent with the real-life traffic flow, and the improvement is clearly observable.
机译:道路网络的结构特性及其与交通流分布的密切关系的研究受到了跨学科的广泛关注。但是,这些尝试大多数都是理论上的。了解道路网络的结构和形态与人民运动之间的关系也是一项挑战。在本研究中,我们开发了一种新方法来应对这一挑战。最初的尝试是将自我网络分析(植根于社会科学领域)应用于分层道路网络的形成。然后,通过为网络中的每个链接分配权重,自我网络被改进为加权自我网络。开发了一种称为加权平均中心度等级的度量,以定义复杂网络中的链接顺序。自我网络和加权自我网络均通过概念网络和两组现实生活的道路网络进行评估。交通流数据被用作评估这两种方法的基准。结果表明它们都表现良好。但是,通过加权自我网络分析形成的层次结构与现实交通流更加一致,并且这种改进显然是可以观察到的。

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