自组织自然道路预测交通流的灵敏度研究
Self-organized Natural Roads for Predicting Traffic Flow: A Sensitivity Study
摘要：
在本文中，我们扩展了基于道路的拓扑分析，以全国和城市的道路网络，并集中在一个敏感性研究与形成的自组织自然道路的基础上良好的连续性的完形原则。年平均日流量（AADT）和全球定位系统（GPS）数据被用来与一系列的排名指标，包括五个基于中心的指标和两个PageRank指标。结果发现，存在一个临界点，从基于段的网络拓扑结构，以道路为基础的排名指标和它们的流量之间的相关性。令我们惊讶的是，（1）如果在形成自组织自然道路时采用自私而不是乌托邦的策略，这种相关性会得到显着改善，（2）通过求和分配到各个道路的基于点的度量往往比基于线的度量与交通流量有更好的相关性。这些违反直觉的惊人发现构成了自组织自然道路的涌现特性，这些自然道路具有足够的智能来预测交通流量，从而从复杂网络的角度对道路网络及其交通的理解提供了实质性的见解。关键词：拓扑分析，交通流，相变，小世界，无标度，临界点
英文摘要：
In this paper, we extended road-based topological analysis to both nationwide and urban road networks, and concentrated on a sensitivity study with respect to the formation of self-organized natural roads based on the Gestalt principle of good continuity. Both Annual Average Daily Traffic (AADT) and Global Positioning System (GPS) data were used to correlate with a series of ranking metrics including five centrality-based metrics and two PageRank metrics. It was found that there exists a tipping point from segment-based to road-based network topology in terms of correlation between ranking metrics and their traffic. To our big surprise, (1) this correlation is significantly improved if a selfish rather than utopian strategy is adopted in forming the self-organized natural roads, and (2) point-based metrics assigned by summation into individual roads tend to have a much better correlation with traffic flow than line-based metrics. These counter-intuitive surprising findings constitute emergent properties of self-organized natural roads, which are intelligent enough for predicting traffic flow, thus shedding substantial insights into the understanding of road networks and their traffic from the perspective of complex networks. Keywords: topological analysis, traffic flow, phase transition, small world, scale free, tipping point
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