Improved Models for Managed Lane Operations

Managed lanes (ML) are increasingly being considered as a tool to mitigate congestion on highways with limited areas for capacity expansion. Managed lanes are dynamically priced based on the congestion level, and can be set either with the objective of maximum utilization (e.g., a public operator) or profit maximization (e.g., a private operator). Optimization models for determining these pricing policies make restrictive assumptions about the layout of these corridors (often a single entrance and exit) or knowledge of traveler characteristics on behalf of the modeler (e.g., distribution of willingness to pay). Developing new models to address these issues would allow for better utilization of these facilities.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

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

    Bhat, Chandra

  • Performing Organizations:

    Data-Supported Transportation Operations and Planning Center

    University of Texas at Austin
    Austin, TX  United States  78701
  • Principal Investigators:

    Boyles, Stephen

  • Start Date: 20170901
  • Expected Completion Date: 20180831
  • Actual Completion Date: 0
  • Source Data: 140

Subject/Index Terms

Filing Info

  • Accession Number: 01634948
  • Record Type: Research project
  • Source Agency: Data-Supported Transportation Operations and Planning Center
  • Contract Numbers: DTRT13-G-UTC58
  • Files: UTC, RiP
  • Created Date: May 18 2017 7:41PM