NETWORK ANALYSIS OF THE EVOLUTION OF TRAFFIC FLOW WITH SPEED INFORMATION

Xin-Gang Li (), Zi-You Gao, Jian-Feng Zheng and Bin Jia
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Xin-Gang Li: MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, P. R. China
Zi-You Gao: MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, P. R. China
Jian-Feng Zheng: MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, P. R. China
Bin Jia: MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, P. R. China

International Journal of Modern Physics C (IJMPC), 2010, vol. 21, issue 02, 177-188

Abstract: In the cellular automata traffic flow model, the traffic state can be represented by the discrete speed value of vehicles, thus the traffic flow can be deemed as a discrete dynamical system. In the evolution process of traffic flow, complex networks are constructed by representing the traffic state as node and the evolution relationship in timescale as link. The emerging times of link is defined as its weight, then the node strength is equal to the emerging times of the corresponding traffic state. As a result, a weighted network is obtained. The dynamics of stop-and-go traffic are studied by investigating the statistical properties of the network. Simulation results show that scale-free behavior commonly exists in the evolution process of stop-and-go traffic. The degree distribution, node strength distribution and link weight distribution have the power law form. The node with high degree also has large strength. The structure of the network is not influenced by the randomization probability and density as long as the stop-and-go traffic is reproduced.

Keywords: Traffic flow; complex network; cellular automata; 05.50.+q; 89.75.-k (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S012918311001504X

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