Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60927
Title: A continuum modeling approach for network vulnerability analysis at regional scale
Authors: Ho, HW
Sumalee, A
Lam, WHK 
Szeto, WY
Keywords: Vulnerability analysis
Regional model
Continuum modeling approach
Issue Date: 2013
Publisher: Elsevier
Source: Procedia, social and behavioral sciences, 2013, v. 80, no. 7, p. 846-859 How to cite?
Journal: Procedia, social and behavioral sciences 
Abstract: Vulnerability analysis is crucial in strategic planning and highway maintenance to ensure a robust transportation system. Owing to the characteristics of network-modeling framework, traditional vulnerability analyses may not be able to realistically model the impacts of network degradations. This paper presents an application of the continuum traffic equilibrium model for network vulnerability analysis that aims to resolve the critical issues faced by the network-modeling framework. The continuum traffic equilibrium model treats the road system as a continuum over which the demands are continuously dispersed. In this study, a bi-level model is set up for finding the most vulnerable location(s) in the study region. At the lower-level model, a set of differential equations is constructed to describe the traffic equilibrium problem under capacity degradation. In the upper-level model, a constrained minimization problem is set up to find the most vulnerable location(s) that minimizes the accessibility index of the study region. A sensitivity-based solution algorithm that adopts the finite element method (FEM) is proposed to solve the bi-level model. Numerical examples are presented to demonstrate the characteristics of the proposed continuum vulnerability analysis and the efficiency of the proposed solution algorithm.
URI: http://hdl.handle.net/10397/60927
ISSN: 1877-0428
DOI: 10.1016/j.sbspro.2013.05.046
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

WEB OF SCIENCETM
Citations

6
Last Week
1
Last month
Citations as of Oct 10, 2017

Page view(s)

36
Last Week
4
Last month
Checked on Oct 16, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.