Robustness Quantification of Transit Infrastructure under Systemic Risks: A Hybrid Network–Analytics Approach for Resilience Planning

Abstract

Disruptions due to either natural or anthropogenic hazards can significantly impact the operation of critical infrastructure networks (e.g., transportation systems) as they may instigate network-level (cascade) systemic risks, thus impacting the overall city resilience. Recent relevant studies demonstrated the need to quantify the resilience of city infrastructure networks following failures of one/some of their main components, considering both topological and operational network measures. Subsequently, focusing on robustness (a key resilience attribute) and on transit (a major critical infrastructure network), the current study develops a related quantification tool employing a hybrid approach that integrates complex network theoretic measures with data analytics, and specifically clustering and genetic algorithms. To demonstrate the practical utility of the developed tool, the robustness of the City of Minneapolis bus transit network is quantified under possible cascade failures represented by node (i.e., bus stop), link (i.e., route segment), and route failure scenarios. The robustness quantification of this transit network is facilitated by analyzing 43 topological and operational measures using a coupled map lattice model integrated with a direction-based passenger flow redistribution model. Absorptive capacity thresholds are subsequently identified under different passenger flow-to-route capacity ratios. Finally, the routes are categorized based on their influences on the network robustness using genetic algorithms coupled with K-means clustering. The developed approach aims at providing a better understanding of transit systems pre-and postdisruptions by identifying key components that control the network robustness and subsequently devising reliable systemic risk management strategies and recovery plans. Such strategies and plans are expected to facilitate city resilience planning through management of cascade failure risks attributed to natural and anthropogenic hazard events.

Old Wine in New Bottles? Understanding Infrastructure Resilience: Foundations, Assessment, and Limitations

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Station Placement for Sustainable Urban Metro Freight Systems Using Complex Network Theory

“…Complex network theory, as an effective means of studying the structural properties [19,20] and dynamics of transportation networks [21,22], has been studied by many domestic and foreign scholars. Hu et al [23] used complex network theory to analyze the topological characteristics of traffic road networks and proposed a new graph spatiotemporal model for traffic flow prediction by combining topological features with graph neural networks.…”

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