A Multiobjective Reinforcement Learning Framework for Equitable Toll Design for Express Lanes

Express lanes are commonly used to migrate traffic congestion by providing reliable travel time in exchange for tolls. However, there is a lack of guidance on designing equitable discounts for low-income travelers, creating barriers to equitable transportation systems. The PI's past study on "Equitable Dynamic Pricing for Express Lanes" addressed some of these gaps by providing guidance for differential tolls and analyzing unintended traffic patterns. However, the framework was limited for single-objective optimization of equity. Furthermore, limitations on open-source algorithms for equity optimization hinder accessibility for researchers and practitioners. The goal of this implementation-focused research is to develop a multi-objective reinforcement-learning-based optimization of express lane discounts and create an open-source tool for making previous research findings more accessible. In this research, the team will (a) design open-source platform that integrates advances in multi-objective reinforcement learning literature for designing discounts for express lanes, (b) test the transferability and usefulness of the designed tools across multiple datasets and development platforms, and (c) conduct a technology transfer to make the tool more accessible for future researchers, practitioners, and policy makers. The research findings will enable more effective design and optimization of express lane discounts for equitable transportation systems.

Language

• English

Project

• Status: Active
• Funding: $86970
• Contract Numbers:

  69A3551747125

• Sponsor Organizations:

  Center for Advanced Transportation Mobility

  North Carolina Agricultural and Technical State University
  Greensboro, NC  United States  27411

  Office of the Assistant Secretary for Research and Technology

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

  North Carolina A&T State University

  1601 E. Market Street
  Greensboro, NC  United States  27411
• Project Managers:

  Pandey, Venktesh

• Performing Organizations:

  North Carolina A&T State University

  1601 E. Market Street
  Greensboro, NC  United States  27411
• Principal Investigators:

  Pandey, Venktesh

• Start Date: 20230601
• Expected Completion Date: 20231231
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Discount; Equity; Express lanes; Machine learning; Technology transfer; Tolls
• Subject Areas: Economics; Highways; Operations and Traffic Management; Research; Society;

Filing Info

• Accession Number: 01893168
• Record Type: Research project
• Source Agency: Center for Advanced Transportation Mobility
• Contract Numbers: 69A3551747125
• Files: UTC, RIP
• Created Date: Sep 13 2023 1:26PM