NDLI: Effects of traffic network dynamics on hierarchical community-based representations of large road networks

Content Provider	IEEE Xplore Digital Library
Author	Nejad, M.M. Mashayekhy, L. Chinnam, R.B.
Copyright Year	2012
Description	Author affiliation: Industrial and Systems Engineering Department, Wayne State University, Detroit, MI 48202 USA (Nejad, M.M.; Chinnam, R.B.) \|\| Computer Science Department, Wayne State University, Detroit, MI 48202 USA (Mashayekhy, L.)
Abstract	Efficient representation of traffic networks, including congestion states, plays an important role in the effectiveness of routing algorithms incorporating Intelligent Transportation Systems (ITS) data. We employ an emerging concept in analyzing complex networks called “community structure detection” to capture traffic network dynamics in the form of hierarchical community-based representations of road networks. A key strength of these community (structure) detection methods is their computational efficiency. We investigate the impact of traffic dynamics on the hierarchical community-based representations of large road networks. The resulting hierarchical community representations and their evolution over varying traffic conditions with time can aid the computational performance of real-time routing algorithms. We analyze the performance of hierarchical community detection methods on the metropolitan road networks of New York City, Detroit, and San Francisco Bay area.
Starting Page	1900
Ending Page	1905
File Size	507489
Page Count	6
File Format	PDF
ISBN	9781467330640
ISSN	21530009
e-ISBN	9781467330633
e-ISBN	9781467330626
DOI	10.1109/ITSC.2012.6338845
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Communities Roads Routing Heuristic algorithms Algorithm design and analysis Vehicle dynamics Real-time systems
Content Type	Text
Resource Type	Article

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