An Urban Traffic Network Analysis Method Based on EPs

Gen Lang Chen; Li Feng An; Xiao Gang Jin

doi:10.4028/www.scientific.net/KEM.460-461.142

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HomeKey Engineering MaterialsKey Engineering Materials Vols. 460-461An Urban Traffic Network Analysis Method Based on...

An Urban Traffic Network Analysis Method Based on EPs

Abstract:

Urban traffic networks (UT-Nets) and cellular metabolic networks (C-Nets) have many common functional characteristics and internal mechanisms. Based on the similarity and traffic conservation, we use extreme pathways (EPs) to analysis the state of UT-Nets. Experiments showed the EPs method for cell metabolism also can be used in urban traffic network analysis after defining some indicators.

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Periodical:

Key Engineering Materials (Volumes 460-461)

Pages:

142-147

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.460-461.142

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Online since:

January 2011

Authors:

Gen Lang Chen, Li Feng An, Xiao Gang Jin

Keywords:

Cellular Metabolic Network, Extreme Pathway, Traffic Flow, Urban Traffic Network

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References

[1] Marc Barthelemy, Alessandro Flammini: Modeling Urban Street Patterns, in: Physical Review Letters, (2008), 100(138702).

Google Scholar

[2] Merchant D K, Nemhause G L: Optimality conditions for a dynamic traffic assignment model, in: Transportation Science, 1978, pp.200-207.

DOI: 10.1287/trsc.12.3.200

Google Scholar

[3] Drissi-Kaitouni O, Hamede-Benchekroun A: A Dynamic Traffic Assignment Model and a Solution Algorithm, in: Transpn Sci, (1992), 26(2).

Google Scholar

[4] Sharon J. Wiback and Bernhard O. Palsson: Extreme Pathway Analysis of Human Red Blood Cell Metabolism, in Biophysical Journal, (2002). P. 808-818.

DOI: 10.1016/s0006-3495(02)75210-7

Google Scholar

[5] Reka Albert, Albert-Laszlo Barabasi: Statistical mechanics of complex networks, in: REVIEWS OF MODERN PHYSICS, (2002), p.74.

Google Scholar

[6] Newman M. E. J: The Structure and Function of Complex Networks, in: SIAM REVIEW, (2003), 45(2) pp.167-256.

Google Scholar

[7] Christophe H, Schilling, David Letscher, Bernhard, Palsson: Theory for the Systemic Definition of Metabolic Pathways and their use in Interpreting Metabolic Function from a Pathway-Oriented Perspective, in: J theor Biol. (2000), 203, pp.229-248.

DOI: 10.1006/jtbi.2000.1073

Google Scholar

[8] Albert R., Barabási A. L: Statistical mechanics of complex networks, in: Rev Mod Phys, (2002), 74, pp.47-97.

DOI: 10.1103/revmodphys.74.47

Google Scholar

[9] Martin Treiber, Ansgar Hennecke, Dirk Helbing: Congested Traffic States in Empirical Observations and Microscopic imulations, in: Phys．Rev．E. (2000), 62, pp.1805-1824.

DOI: 10.1103/physreve.62.1805

Google Scholar