Pricing Mechanisms for Managed Lanes

Two common means of pricing Managed Lanes (MLs) are to vary tolls based on time of day, or to vary them dynamically based on real-time congestion measurements. Which of the two tolling options is more effective in regulating ML-usage is unclear. In this study, large datasets on toll prices, vehicle travel speeds, traffic volumes and densities will be utilized to assess the effects of the two different congestion pricing strategies on traffic conditions. Input data will come from freeway loop detectors and Automatic Vehicle Identification (AVI) readers. Both sources can provide a rich set of data that reveals lane choices made by drivers and the resulting traffic impacts over time and space. Changing toll rates will be correlated with traffic conditions on both the MLs and the general purpose lanes (GPLs). The goal is to evaluate the impact of the two pricing approaches on traffic conditions to assess if the traffic management benefits from dynamic pricing are commensurate to its more resource intensive implementation compared to variable pricing.

• Record URL:
  https://nicr.usf.edu/2020/12/11/4-1-pricing-mechanisms-for-managed-lanes/

Language

• English

Project

• Status: Active
• Funding: $262687
• Contract Numbers:

  69A3551947136

  79070-00-B

  79070-00-A

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

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

  Figueroa Medina, Alberto

• Start Date: 20200101
• Expected Completion Date: 20201231
• Actual Completion Date: 20210430
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Alternatives analysis; Automatic vehicle identification; Congestion pricing; Loop detectors; Managed lanes; Pricing; Tolls; Traffic density; Traffic speed; Traffic volume
• Subject Areas: Finance; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01751472
• Record Type: Research project
• Source Agency: National Institute for Congestion Reduction
• Contract Numbers: 69A3551947136, 79070-00-B, 79070-00-A
• Files: UTC, RIP
• Created Date: Sep 8 2020 6:31PM