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Title:

Identifying Network Representation Issues with the Network Trip Robustness
Cover of Identifying Network Representation Issues with the Network Trip Robustness

Accession Number:

01376100

Record Type:

Monograph

Abstract:

This study evaluates the effects of road-network representation on the application of the Network Robustness Index (NRI), using the Chittenden County Regional Transportation Model. The focus of this study was the tendency for minor and local roads to provide significant robustness gains as they offer critical alternative routes during disruption events. The overall conclusion of this report is that the application of the NRI and the Network Trip Robustness (NTR) can be used to identify these links, and test their significance. By examining the change in NTR that occurs when a previously omitted link is added to the network reveals its significance. In this study, a set of 23 links were identified qualitatively in Chittenden County which are currently not included in the region’s transportation model but may be significant. These 23 links were tested qualitatively and a total of 12 were found to be significant. Based on these findings, future applications of the regional model (CCMPO, 2008) should consider the influence of these links to overall network dynamics. If possible, these links should be included in the network representation for all analyses going forward. The results of this study also have general implications for travel demand models which are increasingly being used to help decision makers with a wide range of critical policy questions. Sophisticated models exist only for large urban areas, and often these models do not include secondary roads required to study relevant policy issues such as robustness and resiliency. Statewide models are often characterized by the use of very large Transportation Analysis Zones (TAZs) which can preclude effective evaluation of detailed road networks. The aggregation of links in a transportation network can have some unintended consequences. This study suggests it is timely to investigate ways of generating model networks that consider the full functional connectivity of the highway system.

Supplemental Notes:

This report was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.

Report Numbers:

UVM TRC Report # 12-004

Language:

English

Corporate Authors:

University of Vermont, Burlington

Transportation Research Center
210 Colchester Avenue
Burlington, VT 05405-1757 USA

Research and Innovative Technology Administration

1200 New Jersey Avenue, SE
Washington, DC 20590 USA

Authors:

Sullivan, James
Novak, David
Aultman-Hall, Lisa

Pagination:

18p

Publication Date:

2012-4-23

Media Type:

Web

Features:

Figures; Maps; References; Tables

Candidate Terms:

Identifier Terms:

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Geographic Terms:

Subject Areas:

Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Files:

UTC, NTL, TRIS, USDOT

Created Date:

Jul 1 2012 9:56PM