01340095

Component

https://doi.org/10.3141/2263-01

http://scholar.google.com...arma&publication_year=2011

The vulnerability of a transportation network is strongly correlated with the ability of the network to withstand shocks and disruptions. A robust network with strategic redundancy allows traffic to be redistributed or reassigned without unduly compromising system performance. High-volume edges with limited alternative paths represent system vulnerabilities—a feature of transportation networks that has been exploited to identify critical components. A mixed-strategy, stochastic game-theoretic approach is presented for the measurement of network vulnerability. This method is designed to incorporate all origins and destinations in a network in a computationally efficient manner. The presented method differs from previous efforts in that it provides a many-to-many measure of vulnerability and edge-based disruptions that may not reside on a common path. A game that considers all possible origin–destination pairs is constructed between a router, which seeks minimum cost paths for travelers, and a network tester, which maximizes travel cost by disabling edges within the network. The method of successive averages is used for routing probabilities, and a weighted entropy function is employed to compute edge-disruption probabilities. The method is demonstrated on a small example network and then applied to the Sioux Falls, South Dakota, network. Results indicate good correspondence with a previous method that used equilibrium assignment and rapid solution convergence.

01365004

11-3675

English

pp 1-8

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309223034

Print

Figures (3) ; References (17) ; Tables (6)

Game theory; Origin and destination; Routing; Traffic assignment; Travel costs

Disruptions; Method of successive averages; System performance; Transportation networks; Vulnerability

Sioux Falls (South Dakota)

Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

TRIS, TRB

Feb 17 2011 6:36PM

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• Transit Stop-Level Origin–Destination Estimation Through Use of Transit Schedule and Automated Data Collection System
• Travel Speed Forecasting by Means of Continuous Conditional Random Fields
• Vulnerability Analysis of Transportation Network Under Scenarios of Sea Level Rise