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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>A Multiobjective Reinforcement Learning Framework for Equitable Toll Design for Express Lanes
</title>
      <link>https://rip.trb.org/View/2244372</link>
      <description><![CDATA[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.
]]></description>
      <pubDate>Wed, 13 Sep 2023 13:26:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2244372</guid>
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      <title>Synthesis of Information Related to Transit Practices. Topic SB-40. Low-Income Transit Discount Provision at Public Transit Agencies in the United States

</title>
      <link>https://rip.trb.org/View/2190463</link>
      <description><![CDATA[Over the past decade, public transit agencies across the United States and Canada have increasingly adopted low-income fare discount programs to improve transit affordability and accessibility. The COVID-19 pandemic accelerated this trend, prompting agencies to reevaluate services and expand affordable transit choices. These programs typically use a means-based eligibility approach and offer various benefits such as fare discounts, free rides, or discounted passes. While previous research documents the positive outcomes of low-income fare discount programs, including increased mobility for low-income riders, there is limited insight into how low-income fare programs are administered.

This synthesis documents the current state of the practice of low-income fare discount programs offered by North American transit agencies. The synthesis begins with a literature review of existing research on low-income discount programs. Then, findings from a survey examine the key program elements of 26 agencies and their partner organizations. Also presented are case examples of seven agencies with low-income fare discount programs. The synthesis concludes with identifying 10 key findings of the study and four areas for future research.

The study was led by Dr. Candace Brakewood of the University of Tennessee, Knoxville, with support from graduate student Matthew Davis. The study team conducted the literature review, collected and synthesized the data, and prepared the report. This synthesis serves as an immediately valuable resource for transit professionals, documenting current practices and laying a foundation for future research and innovation in transit fare policies.]]></description>
      <pubDate>Fri, 09 Jun 2023 19:15:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2190463</guid>
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      <title>Full Evaluation of a Low-Income Transit Fare Pilot Program in DC</title>
      <link>https://rip.trb.org/View/1878016</link>
      <description><![CDATA[Low-income households are the most likely to be burdened by the costs of using public transit, the most likely to forego using transit due to cost, and the least likely to have alternative travel options. The cost burden of transit has a number of possible negative effects on low-income Washingtonians, including inhibiting their ability to get and maintain employment, use social services, obtain healthcare, and complete educational programs. Preliminary results from a low-income fare pilot in Boston showed a 30% boost in transit use by low-income households, including trips for health-care/social services visits. In addition, a 2011 experiment in DC found that even small transit subsidies offered to the unemployed increased job search activity by 19%, especially among those living far from employment opportunities.
To learn whether and to what extent cost is a key barrier to transit equity, the District Department of Transportation (DDOT) is partnering with The Lab @ DC, the Washington Metropolitan Area Transit Authority (WMATA), the DC Department of Energy and the Environment (DOEE), and the World Bank to conduct a randomized evaluation of a fully and partially subsidized Metro transit program. WMATA will create a discounted fare product that could be added to a SmarTrip card for eligible low-income individuals. DOEE will enroll participants from public utility assistance programs that already verify income and distribute income-based benefits as part of their standard business process.
In the study, participants will be randomly assigned to one of three conditions: no transit subsidy, a partially subsidized fare, and a fully subsidized fare, i.e. free unlimited trips. The project will rely partly on administrative data, which will capture the high-level impacts on the number of trips taken, jobs applied to, job trainings completed, and employment status. ]]></description>
      <pubDate>Mon, 13 Sep 2021 14:50:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1878016</guid>
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