A robustness assessment approach for transportation networks with cyber-physical interdependencies

Abstract

While in the past the robustness of transportation networks was studied considering the cyber and physical space as isolated environments this is no longer the case. Integrating the Internet of Things devices in the sensing area of transportation infrastructure has resulted in ubiquitous cyber-physical systems and increasing interdependencies between the physical and cyber networks. As a result, the robustness of transportation networks relies on the uninterrupted serviceability of physical and cyber networks. Current studies on interdependent networks overlook the civil engineering aspect of cyber-physical systems. Firstly, they rely on the assumption of a uniform and strong level of interdependency. That is, once a node within a network fails its counterpart fails immediately. Current studies overlook the impact of earthquake and other natural hazards on the operation of modern transportation infrastructure, that now serve as a cyber-physical system. The last is responsible not only for the physical operation (e.g., flow of vehicles) but also for the continuous data transmission and subsequently the cyber operation of the entire transportation network. Therefore, the robustness of modern transportation networks should be modelled from a new cyber-physical perspective that includes civil engineering aspects. In this paper, we propose a new robustness assessment approach for modern transportation networks and their underlying interdependent physical and cyber network, subjected to earthquake events. The novelty relies on the modelling of interdependent networks, in the form of a graph, based on their interdependency levels. We associate the serviceability level of the coupled physical and cyber network with the damage states induced by earthquake events. Robustness is then measured as a degradation of the cyber-physical serviceability level. The application of the approach is demonstrated by studying an illustrative transportation network using seismic data from real-world transportation infrastructure. Furthermore, we propose the integration of a robustness improvement indicator based on physical and cyber attributes to enhance the cyber-physical serviceability level. Results indicate an improvement in robustness level (i.e., 41 %) by adopting the proposed robustness improvement indicator. The usefulness of our approach is highlighted by comparing it with other methods that consider strong interdependencies and key node protection strategies. The approach is of interest to stakeholders who are attempting to incorporate cyber-physical systems into civil engineering systems.