Analysis of Vulnerability of Road Networks on the Basis of Graph Topology and Related Attribute Information

The safety of people and the security of the vital functions of society are among the core tasks of governments. Various networks, especially transportation networks, are important for human life. Much research has been done to analyse the vulnerability of road networks and most of the methods were based on analysing the topological structure of the network using graph theory. For instance, Demšar et al. presented a mathematical method for modelling the vulnerability of the elements of the network, which can be used for the identification of critical locations in a spatial network. The vertices of the line graph that correspond to critical locations have one or more of the following three properties: they are cut vertices and they have a high betweenness value or a low clustering coefficient. The risk value estimation method produced results with low accuracy because the risk value of a cut edge road is estimated on the basis of its cut edge attribute value only (Demšar et al., 2008). However, it is not always sufficient to base network vulnerability analysis only on the topological structure for crisis management. For instance, in a road network, if a bridge to an island can be considered as a cut edge, what if there is only one summer house on the island? Is this bridge more important than a minor road located inside a residential area with a high population density? If edge A has a higher betweenness centrality value than cut edge B, is edge A more vulnerable than edge B? Obviously, some non-topological attributes should also be added into consideration when analyzing the vulnerability of road network for the preparedness of crisis management. This paper introduces a multi-attribute value theory that could be used to extend the graph theory approach towards a more complementary method.