Principal Investigator: Dr. David Novak (School of Business Administration and School of Engineering)
Co-Investigators: James Sullivan (TRC), Dr. Lisa Aultman-Hall (TRC), Dr. Darren M. Scott (McMaster University)
Partners: RSG, CCMPO, CCRPC, and McMaster University
Funding Agency: US DOT
This project investigates the robustness, redundancy and resiliency of the transportation network under current and future conditions. Transportation planning efforts, especially those involving highway capacity expansions, have traditionally relied on the Volume/Capacity (V/C) ratio to identify congested or critical links, resulting in localized solutions that do not consider system-wide impacts related to congestion, security and emergency response. Members of the research team recently developed the Network Robustness Index (NRI): a new, comprehensive, system-wide approach for identifying critical links and evaluating transportation network performance. It relies on readily available sources of data from travel demand forecasting models. Analysis of three hypothetical networks has demonstrated that NRI-based solutions yield far greater system-wide benefits than traditional (V/C) solutions, as measured by travel-time savings (Scott et al. 2006).
While the NRI has been tested on hypothetical networks, it has not yet been applied to a real world road network. As part of the current project, it is proposed to utilize actual road networks and origin/destination (O/D) pairs as input data to assess which network links are considered the most vulnerable in Chittenden County, Vermont. The integrated UrbanSim/TRANSIMS model will provide the inputs needed to calculate the NRI for Chittenden County. This will include information about specific road networks, traffic volumes and link capacities, and origin-destination flows. Researchers will use the NRI to identify specific road links that are the most critical or valuable with respect to maintaining the robustness of the overall road network system within Chittenden County based on average peak period traffic conditions. The most critical links identified by the NRI will be compared for overlap with those identified by other more traditional measures.