Traffic congestions in urban road traffic networks originate from some crowded road segments with crucial locations, and diffuse towards other parts of the urban road network creating further congestions. This behavior of road networks motivates the need to understand the influence of individual road segments on others in terms of congestion. In this paper, we investigate the problems of global influence ranking and local influence ranking of road segments. We propose an algorithm called RoadRank to compute the global influence scores of each road segment from their traffic measures, and rank them based on their overall influence. To identify the locally influential road segments, we also propose an extension called distributed RoadRank, based on road network partitions. We perform extensive experiments on real SCATS datasets of Melbourne. We found that the segments of Batman Avenue, Footscray Road, Punt Road, La Trobe Street, and Victoria Street, are highly influential in the early morning times, which are well known as congestion hotspots for both the network operators and the commuters. Our promising results and detailed insights demonstrate the efficacy of our method.

中文翻译：

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城市道路交通网络路段影响力排序

城市道路交通网络中的交通拥堵起源于一些具有关键位置的拥挤路段，然后向城市道路网络的其他部分扩散，造成进一步的拥堵。道路网络的这种行为促使人们需要了解各个路段在拥堵方面对其他路段的影响。在本文中，我们研究了路段的全局影响力排名和局部影响力排名问题。我们提出了一种称为 RoadRank 的算法，用于根据每个路段的交通量度计算每个路段的全局影响力分数，并根据它们的整体影响力对它们进行排名。为了识别当地有影响的路段，我们还提出了一种基于道路网络分区的称为分布式 RoadRank 的扩展。我们对墨尔本的真实 SCATS 数据集进行了大量实验。我们发现 Batman Avenue、Footscray Road、Punt Road、La Trobe Street 和 Victoria Street 的路段在清晨时段具有很高的影响力，这些路段是众所周知的网络运营商和通勤者的拥堵热点。我们有希望的结果和详细的见解证明了我们方法的有效性。