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A simulation of the cascading failure of a complex network model by considering the characteristics of road traffic conditions

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Abstract

Using the dual method, we start with a traditional road traffic network with a constructed logic network with small-world characteristics and construct the complex network of road traffic. After analyzing and comparing with other complex networks, the time delay, restorative, and other characteristics are presented for the complex network of road traffic, and then, the cascading failure model of the complex network is simulated. The simulation results show that using different time delays, an incident dissipation factor and load capacity can reasonably avoid a cascading failure, and they can remove its effects. In addition, our results provide value and guidance for building a road traffic network that prevents and removes the cascading failure of a road network.

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Acknowledgments

This work is supported by the National Social Science Foundation of China (Grant Nos. 11CJY067, 14CJY052, 14XGL011) and the Humanities and Social Sciences Programming Project of the Ministry of Education, China (Grant Nos. 12YJC630200, 12YJC630100) and the Natural Science Foundation of Gansu Province, China (Grant Nos. 1208RJZA164, 1308RJYA042, 145RJZA190) and the Construction of Science and Technology Key Project in Gansu Province (Grant No. JK2013-21) and the Social Sciences planning project in Gansu Province, China (Grant No. 13YD066) and the Young Scholars Science Foundation of Lanzhou Jiao tong University (Grant No. 2012056).

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Authors and Affiliations

  1. School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou, 730070, Gansu Province, China

    Yongsheng Qian, Bingbing Wang, Yuan Xue, Junwei Zeng & Neng Wang

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  1. Yongsheng Qian
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  2. Bingbing Wang
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  3. Yuan Xue
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  4. Junwei Zeng
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  5. Neng Wang
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Correspondence to Yongsheng Qian.

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Qian, Y., Wang, B., Xue, Y. et al. A simulation of the cascading failure of a complex network model by considering the characteristics of road traffic conditions. Nonlinear Dyn 80, 413–420 (2015). https://doi.org/10.1007/s11071-014-1878-z

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  • DOI: https://doi.org/10.1007/s11071-014-1878-z

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