Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events

Abstract

Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist.

Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System

“…Multiple event resilience is quite different from resilience that only considers a single disruption (Zhou, Sheu, & Wang, ). According to the description and model of multiple hazards impacts on infrastructures, the existing research is classified into two groups: scenario‐based and distribution‐based methods.…”

“…Zhou et al. () define multiple hazards as simultaneous disruptions of several roads under multiple events. Damage of each road is described by a binomial distribution, and multiple hazards are described by Poisson distribution.…”

“…Infrastructure components located in the same area may be subject to a specific disturbance/disaster, and the location of infrastructures (and distance between them) has an important effect on topological properties and, consequently, on infrastructure functioning processes (Zhou et al., ). The spatial attributes of nodes and edges are included in a realistic infrastructure network model with geographical coordinates defined in a two‐dimensional Euclidean coordinate system.…”

Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure

“…These two kinds of attacks are carried out by removing the nodes (e.g., metro stations) and all the edges linked to the nodes. The malicious attack aims at destroying the most important nodes so as to paralyze the functionality of the whole network (e.g., a metro system) to the greatest extent [11,15,17]. The random failure is specified as the dysfunction which results from the failure on some nodes with a random probability [15].…”

Advances in Risk Analysis with Big Data

“…This special issue also features an article studying risk associated with urban road networks. To be specific, Zhou et al (19) study the urban road network with the consideration of hazard events. The authors propose a two-layer robustness assessment framework for an urban road network; particularly, the impact of multiple simultaneous hazard events is considered.…”