Predicting Travel and Congestion in a Post-Pandemic America

COVID-19 has affected travel behavior in many ways. Changes include a predictable reduction in overall travel, and even larger reductions in transit travel, carpooling, and travel on toll facilities. What happens to travel and congestion once we return to a ‘new normal’? There is concern that transit ridership will not fully rebound causing additional congestion in dense urban areas that rely on ransit and escalate equity issues for underserved sectors and populations. Also toll road and managed lane traffic may not rebound causing both inefficient use of that road space and revenue shortfalls. This project will examine recent trends and attempt to predict travel in a ‘new normal’ (post-pandemic) environment utilizing behavioral economics, psychology, big data, and transportation expertise. Phase 1 focuses on identifying the changes in travel and the potential recovery rates for the travel modes while Phase 2 integrates these changes in planning models to predict future traffic projections using real world scenarios. Phase 1 includes a series of behavioral economics laboratory-based experiments, involving the latest methodologies such as tracking eye movements and using sensors to track brain activity as respondents make travel choices in an experimental environment that will be based on realistic travel situations. These studies will be combined with detailed traffic and transit data from several urban areas along with expert opinions from transit operators and toll road authorities to predict a ‘new normal’. In Phase 2, researchers will use available data from large-scale origin-destination data sets along with findings from Phase 1 to better predict travel, congestion, farebox revenues and toll revenues in a ‘new normal’ along with impacts on travelers of different income levels and ethnicities.

• Record URL:
  https://nicr.usf.edu/2021/05/18/1-6-predicting-travel-and-congestion-in-a-post-pandemic-america/

Language

• English

Project

• Status: Active
• Funding: $221698
• Contract Numbers:

  69A3551947136

  79075-00-B

  79075-00-A

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  National Institute for Congestion Reduction

  University of South Florida
  Tampa, FL  United States  33620
• Managing Organizations:

  National Institute for Congestion Reduction

  University of South Florida
  Tampa, FL  United States  33620
• Project Managers:

  Li, Xiaopeng

• Performing Organizations:

  Texas A&M Transportation Institute (TTI)

  400 Harvey Mitchell Parkway South
  Suite 300
  College Station, TX  United States  77845-4375

  University of Puerto Rico at Mayaguez

  259, Avenida Alfonso Valdés Cobián, ,
  Mayagüez, Puerto Rico  United States  00681
• Principal Investigators:

  Burris, Mark

  Brown, Alex

  Wallis, Jason

  Figueroa Medina, Alberto

• Start Date: 20210601
• Expected Completion Date: 20220831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: COVID-19; Eye movements; Forecasting; Origin and destination; Traffic congestion; Travel behavior
• Subject Areas: Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01784707
• Record Type: Research project
• Source Agency: National Institute for Congestion Reduction
• Contract Numbers: 69A3551947136, 79075-00-B, 79075-00-A
• Files: UTC, RIP
• Created Date: Oct 14 2021 12:33PM