Traffic Flow and Road User Impacts of the Collapse of the I-35W Bridge over the Mississippi River

Principal Investigator:

David Levinson, Professor, Civil, Environmental and Geo-Engineering

Co-Investigators:

  • Kathleen Harder, Senior Research Associate, College of Design
  • Henry Liu, Associate Professor, Civil, Environmental and Geo-Engineering

Project Summary:

Major network disruptions have significant impacts on local travelers. A good understanding of behavioral reactions to such incidents is crucial for traffic mitigation, management, and planning, yet existing research on such topics is limited. The collapse of the I-35W Mississippi River Bridge (August 1, 2007) abruptly disrupted habitual routes of about 14,000 daily trips and forced even more travelers to adapt their travel pattern to evolving network conditions. The opening of the replacement bridge on November 18, 2008 generated another disturbance (this time predictable) on the network. Such "natural" experiments provide unique opportunities for behavioral studies. This project focuses on the traffic and behavioral reactions to both bridge collapse and bridge reopening, and contributes to general knowledge by identifying unique patterns following different events. Three types of data collection efforts were conducted during the appropriate frame of reference (i.e. before vs. after bridge reconstruction): 1) GPS tracking data and associated user surveys; 2) paper and internet-based survey data gauging travel behavior in the post-bridge reconstruction phase; and 3) aggregate data relating to freeway and arterial traffic flows, traffic control, and transit ridership. Differences in reactions to planned versus unplanned events were revealed. Changes in travel cost were evaluated and their temporal and spatial patterns were analyzed. This project inclcudes thorough discussions of findings from this study and policy implications.

Sponsor:

Project Details:

  • Start date: 06/2008
  • Project Status: Completed
  • Research Area: Transportation Safety and Traffic Flow
  • Topics: Traffic Modeling and Data