TIAN Jing, FANG Huaqiang, LIU Jiajia, ZHAO Feng, REN Chang. Robustness Analysis of Urban Street Networks Using Complex Network Method[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 771-777. DOI: 10.13203/j.whugis20150334
Citation: TIAN Jing, FANG Huaqiang, LIU Jiajia, ZHAO Feng, REN Chang. Robustness Analysis of Urban Street Networks Using Complex Network Method[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 771-777. DOI: 10.13203/j.whugis20150334

Robustness Analysis of Urban Street Networks Using Complex Network Method

  • Robustness analysis of street network can contribute to the precaution and loss reduction of terrorism attacks, natural disasters and traffic congestion. We have obtained 50 urban road networks around the world from OpenStreetMap. On the basis of complex network robustness analysis method, we utilize the successive removal model and the cascade model to analyze the urban road network represented by the intersecting relationship of patterns, and discuss the relationship between the robustness of the road network and its topological patterns. It is found that the robustness varies when the network is under different attack model; it also differentiates when the attach strategy is targeting high-degree or high-betweenness nodes. The robustness of urban street networks is sensitive to the attach model and strategy. The road networks show less robustness under consecutive attack, while they vary considerably under cascade attack. In terms of the attack strategies, the betweenness strategy is more destructive than degree strategy under successive removal and the cascade models, which signifies that the high-betweenness nodes play a more im-portant role. The assortativity of street network is significantly positively correlated with its robustness against successive removal of nodes while significant difference observed for the robustness of scale-free and non-scale-free networks under the same model. The robustness under cascade attack shows no correlation with network assortativity and does not differ significantly between groups of different scale-free properties.
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