NDLI: RoadRank: Traffic Diffusion and Influence Estimation in Dynamic Urban Road Networks

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RoadRank: Traffic Diffusion and Influence Estimation in Dynamic Urban Road Networks

Content Provider	ACM Digital Library
Author	Liu, Chengfei Anwar, Tarique Islam, Md. Saiful Vu, Hai L.
Abstract	With the rapidly growing population in urban areas, these days the urban road networks are expanding at a faster rate. The frequent movement of people on them leads to traffic congestions. These congestions originate from some crowded road segments, and diffuse towards other parts of the urban road networks 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 work, we propose RoadRank, an algorithm to compute the influence scores of each road segment in an urban road network, and rank them based on their overall influence. It is an incremental algorithm that keeps on updating the influence scores with time, by feeding with the latest traffic data at each time point. The method starts with constructing a directed graph called influence graph, which is then used to iteratively compute the influence scores using probabilistic diffusion theory. We show promising preliminary experimental results on real SCATS traffic data of Melbourne.
Starting Page	1671
Ending Page	1674
Page Count	4
File Format	PDF
ISBN	9781450337946
DOI	10.1145/2806416.2806588
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-17
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Traffic diffusion Road networks Influential roads
Content Type	Text
Resource Type	Article

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