Error and Attack Tolerance of Public Transportation Networks: A Temporal Networks Approach

The behaviour of complex networks under attack provides insight into their internal structure. Furthermore, advances in methods for analysing temporal networks have enabled us to perform more detailed modelling of a certain subset of dynamic complex systems specially since frequency of events and temporal correlations play a role in dynamics of the system. In this report, the temporal network approach for study of robustness is applied to public transportation networks. The focus is on providing a set of tools to model different scenarios of attack and random failure, and processing the results with or without taking into account the origin-destination demand matrix frequently used in transportation network studies.

The results of the robustness analysis on temporal representation of public transport networks illustrate the distribution of accessibility and travel time after an attack or error and how it changes when more routes are removed. Furthermore we see that two methods of attack, one based on temporal betweenness centrality and one based on nominal capacity of routes, have a higher effect on increasing delays while attack methods based on centrality of routes in a static aggregated network do not perform any better than randomly removing routes.