Community structure in traffic zones based on travel demand

Li Sun, Ximan Ling, Kun He and Qian Tan

Physica A: Statistical Mechanics and its Applications, 2016, vol. 457, issue C, 356-363

Abstract: Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin–destination pairs with large number of trips play a significant role in urban traffic network’s community division. The layout of traffic community in a city also depends on the residents’ trajectories.

Keywords: Urban traffic system; Traffic community division; Community detection; Spectral algorithm (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:457:y:2016:i:c:p:356-363

DOI: 10.1016/j.physa.2016.03.036

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