Towards analyzing the robustness of the Integrated Global Transportation Network Abstraction (IGTNA)

The well-functioning of our transportation systems is essential for ensuring the mobility of people and goods. According to the Sustainable Developmental Goals (SDG) adopted by the United Nations General Assembly in 2015, it is of utmost importance to build and maintain a resilient infrastructure. In terms of transportation systems, a resilient infrastructure guarantees seamless connections and robustness against failures and targeted attacks. Existing studies on small-scale road, subway, or air transportation networks have revealed interesting patterns and phenomena for different parts of the world. These studies, however, are usually either spatially or modal-wise constrained. Most notably this holds for the worldwide airport network, which has frequently been analyzed in the literature. Transportation interactions on the ground are usually considered through aggregation of nodes into either cities or multiple airport regions. This conceptual simplification leaves room for the analysis of an Integrated Global Transportation Network Abstraction (IGTNA), covering aviation and ground transportation on our planet. We believe that it is crucial for planners and analysts to include all infrastructure, assets, networks, modes, and users as a single system. IGTNA enables to model all aspects of interconnectivity at a high-level of details, encoding points of interests as nodes and potential transitions between points of interests as links. Our aggregated network representation of the global transportation system consists of 5.3 million nodes and more than 8.6 million links. We propose scalable data extraction and network dismantling techniques. This study is, to the best of our knowledge, the first to report on the robustness of the IGTNA. We believe that our study enables decision-makers to achieve effective decision-making on future transportation investment through a holistic understanding of the impacts from negative shocks of disruptive events.