Citation

Hassan R, Yosri A, Ezzeldin M, El-Dakhakhni W. J. Transp. Eng. A: Systems 2022; 148(10): e04022089.

Copyright

(Copyright © 2022, American Society of Civil Engineers)

DOI

10.1061/JTEPBS.0000705

PMID

unavailable

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

Keywords

Absorptive capacity; Cascade failure; City networks; Cluster analysis; Complex network theory; Genetic algorithms; Network topology; Resilience; Robustness; Transit systems