Surveying traffic congestion based on the concept of community structure of complex networks

Lili Ma, Zhanli Zhang () and Meng Li ()
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Lili Ma: School of Statistics, Capital University of Economics and Business, Beijing 100070, China
Zhanli Zhang: School of Statistics and Mathematics, Central University of Finance and Economics, Beijing 100081, China
Meng Li: Key Laboratory of Mathematics, Informatics and Behavioral, Semantics of Ministry of Education, Beijing 100191, China

International Journal of Modern Physics C (IJMPC), 2016, vol. 27, issue 12, 1-16

Abstract: In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.

Keywords: Complex networks; community structure; traffic congestion; floating car data (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0129183116501497

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