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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJzdWJqZWN0aWQiIHZhbHVlPSIxODA4IiAvPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSI3MzAiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnMgLz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Putting a Price on Regional Rail Quality: Evaluating the Value Potential Riders Place on Regional Rail Service Attributes</title>
      <link>https://rip.trb.org/View/2702083</link>
      <description><![CDATA[Public transit has suffered from chronic disinvestment despite its community-wide benefits. Post-pandemic, drastic changes in travel demand have left agencies grappling with financial stress. California’s transit ridership has generally tracked alongside national ridership trends with a substantial dip in ridership and then slow recovery, but commuter rail mode share has remained substantially lower than pre-pandemic shares. Most rail services are geared towards serving commuters; higher frequency is offered during weekdays and peak hours, ticket pricing is tailored to favor people making the same kind of trip on a regular basis, and service hours align with commuter needs. The five days-a-week commuting to work lifestyle is no more, and rail agencies serving commuters are experiencing decimated ridership that is showing no signs of bouncing back. This project uses survey research targeted towards understanding how to tailor rail services to gain new markets for regional rail services. The research team developed a stated preference (SP) experiment to understand evolving needs of commuters and non-commuters, as well as riders and potential riders. The service attributes under study include train schedule, ticket cost, station access, reliability, station amenities, and how the potential user base views rail services. Although the study will focus on the area defined by its research partner, Capitol Corridor, it is widely applicable across the country in locations with intercity, suburban, and small urban regional rail services.]]></description>
      <pubDate>Wed, 13 May 2026 16:58:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702083</guid>
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    <item>
      <title>Transit-Oriented Development Ridership Calculator - Phase 1</title>
      <link>https://rip.trb.org/View/2697837</link>
      <description><![CDATA[Transit-Oriented Development (TOD) is the creation of compact, walkable, pedestrian-oriented, mixed-use communities centered around stations along transit priority corridors (rail, bus rapid transit). The State of California has established several policies to support TOD, as have local jurisdictions and the Federal Transit Administration (FTA). There is a need for research on the quantifiable impacts of TOD on transit ridership to guide policy and investments in TOD for future transit plans. There is good literature on the impacts of various factors (fares, gas prices, service levels, TNCs, etc.) on ridership levels. There is also literature on the impact of land use generally (employment/population density, land use types) on transit ridership. TOD impacts on ridership, however, are not well researched to date because data on TODs and the residents that move into them is not available at a consistent level. Agencies and municipalities applying for state grants provide estimates of ridership impacts and new development catalyzed by the project, but producing well-supported, reliable numbers in their applications remains a challenge. Some regions have regional ridership models they use in service planning, but these models are generally not designed to forecast changes associated with a single building or neighborhood. Other regions do not have ridership models at all and must rely on ad-hoc approaches to estimate ridership impacts. There is also a need to provide consistent, transparent transit ridership estimates so that more-resourced agencies applying for grants do not out-compete less-resourced agencies that don't have their own regional ridership models. Different local or regional transit ridership model methodologies may not be transparent to audiences, including grant application evaluators. One way to standardize the process and level the playing field between agencies is through the creation of an easy-to-use calculator for estimating the ridership impacts of TOD projects. Through this tool, ridership estimates for applicants seeking funding or zoning variances for TOD projects will be able to document how the projects will impact ridership. These estimates will be comparable across projects thanks to using a standardized methodology. This project will lay the groundwork for creating such a calculator, by reviewing the existing literature on the topic and identifying an actionable plan and concrete model structure to implement the calculator.]]></description>
      <pubDate>Thu, 30 Apr 2026 12:20:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697837</guid>
    </item>
    <item>
      <title>Zero- and Reduced-Fare Transit Policy and Post-Pandemic Recovery: A Multi-Agency Analysis of Ridership, Service Supply, and Access</title>
      <link>https://rip.trb.org/View/2697838</link>
      <description><![CDATA[Despite growing interest in fare reduction as a policy lever, rigorous comparative evidence on its effects, particularly in the post-pandemic context, remains limited. In Virginia some 40 transit agencies eliminated fares for some period of time during the COVID pandemic, leading the Department of Rail and Public Transportation to ask how fare reduction or fare elimination have affected ridership, operations, and access for system users. This research addresses that question by developing a structured analytical framework and applying it to a sample of transit agencies in which Virginia properties are heavily represented. Using longitudinal data spanning years before and after the pandemic “lockdown”, the research compares agencies that adopted zero- and reduced-fare policies or means-tested fare-free programs against matched fare-collecting agencies. The analysis addresses three interrelated outcomes: ridership recovery trajectories, changes in service supply and scheduled speeds and headways, and shifts in access to employment and key destinations. For a representative subset of agencies, the study also conducts a network-level analysis of access to employment using Remix, a transit planning and scheduling software tool, for a selected set of agencies that represent a range of system sizes. Findings are intended to provide evidence-based guidance for Virginia transit agencies and other stakeholders considering fare policy as a tool for ridership recovery and service quality and performance.]]></description>
      <pubDate>Thu, 30 Apr 2026 08:37:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697838</guid>
    </item>
    <item>
      <title>Accounting for fare evasion in estimates of transit ridership</title>
      <link>https://rip.trb.org/View/2697836</link>
      <description><![CDATA[Fare evasion has been a problem for transit agencies since the days of horse-drawn omnibuses. However, over the past few years fare evasion rates have been up across the country. In New York City, the Metropolitan Transit Authority estimated that 48% of bus riders did not pay, compared to 18% pre-COVID. Similar trends have been observed in other parts of the country, including in California. Fare evasion can have many impacts for the transit agency and its riders. First and foremost, it results in a loss of revenue at a time when agencies are fighting to maintain operations funding at acceptable levels. For this reason, agencies regularly attempt to combat fare evasion and have many techniques to do so both in practice and from the literature. However, fare evasion may also impact the ability of an agency to estimate their ridership. It is vital to understand ridership trends in general and specifically ridership recovery. If increasing fare evasion rates are not accounted for, the data used to gauge transit’s recovery in terms of ridership may be systematically wrong. While transit agencies must report their transit ridership data to the National Transit Database in the form of Unlinked Passenger Trips (UPT) and Passenger Miles Traveled (PMT), no information is systematically available about how the data are collected. The main objective of this research is to assess and document methods used to determine UPT and PMT at transit agencies across California, including sources of potential error such as fare evasion. The predominant source of this data will be a statewide transit agency survey. To reduce respondent burden, the second objective of this research is to develop a new initiative across the state to coordinate research involving surveys or other large outreach efforts across multiple transit agencies in partnership with Caltrans, state agencies, advocacy organizations, and research organizations. It supports a key area of responsibility with regard to tracking and reporting transit performance measures and assessment of the suitability of new transit investments.]]></description>
      <pubDate>Wed, 29 Apr 2026 17:26:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697836</guid>
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    <item>
      <title>Lessons Learned on Mobility as a Service (MaaS): Exploring Opportunities and Barriers for the U.S. Context</title>
      <link>https://rip.trb.org/View/2696846</link>
      <description><![CDATA[Mobility as a Service (MaaS) packages can increase the popularity of alternatives to owning (and using) a personal vehicle, through the integration of multiple transportation services and options on the same platform. Several MaaS solutions have been proposed in Europe and other regions of the world. However, there is a dearth of research on MaaS in the US context. This study will be a starting point to fill that gap. In this study, the researchers will review MaaS experience from abroad and investigate the lessons learned on the way MaaS works, the various levels of integration possible on the MaaS platform, the type of transportation services that are offered, and the way (bundle) payments and fare integration are handled. The study will then build US-specific knowledge on the potential attractiveness of MaaS-type mobility packages through hosting focus group discussions with groups of travelers, to identify their potential openness to adopt MaaS services, the perceived benefits that would be derived from their use, and the characteristics that MaaS solutions should have to (eventually) be attractive among selected groups of US travelers. The findings from this study will help understand what realistic paths may exist to integrate public transit and shared mobility solutions to expand travel options in the US, and how effectively these options might encourage travelers to increase travel multimodality and reduce their reliance on the use of private vehicles. This study will serve as a starting point for developing future larger studies on MaaS in the US context.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:03:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696846</guid>
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    <item>
      <title>Passenger Evacuation Experience</title>
      <link>https://rip.trb.org/View/2694524</link>
      <description><![CDATA[Data and information on passenger perspectives from recent aircraft evacuations are required to identify areas of success and needs for improvements. During the normal investigation of these incidents, the response rate to the office inquiry is low, and the National Transportation Safety Board (NTSB) does not collect these data points unless it is classified as an accident. These data are needed to evaluate passenger behavior, passenger flow,  experience with passengers with disabilities and children, and evaluate decision making on passengers choosing to take personal items with them. Alternate means of reaching out to passengers will be investigated to gather these data. Ensuring to document any challenges the passengers faced, points of confusion, injuries sustained, or aspects which made the process operate efficiently. Special focus will be on parents/caregivers traveling with children, passengers who have special accessibility needs or physical limitations, those traveling with animals, and those who evacuated with personal items. Research team will collect similar responses from cabin crew members, such as flight attendants, to gain their perspective on the evacuation event and areas for possible improvement. These data collections were recommended as part of the Emergency Evacuation Aviation Rulemaking Committee (ARC). ]]></description>
      <pubDate>Wed, 22 Apr 2026 10:30:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2694524</guid>
    </item>
    <item>
      <title>Reducing empty miles of shared mobility on highway corridors</title>
      <link>https://rip.trb.org/View/2691661</link>
      <description><![CDATA[Smartphone-app-based technology has provided business opportunities to various demand-responsive urban transportation services, including e-hailing taxis, ride-pooling, and microtransit. These shared mobility services exhibit great potential for enhancing transportation services in rural communities. A common side effect, however, is a substantial portion of empty vehicle miles traveled (VMT) on highway corridors, which induces further congestion to highway traffic in peak hours. A quantitative analysis tool is necessary for planning agencies and policymakers to assess the impact of shared mobility on highway traffic. The researcher's recent work investigating ride-pooling systems serving uniformly distributed demands in a single community shows that their efficiency is highly sensitive to online matching schemes. This impact is expected to be even more significant in spatially imbalanced demand patterns, such as those between suburban/rural communities. This project will develop a traffic assignment model to allocate vehicular trips to corridor networks linking suburban and rural communities, which will assist policymakers in (1) understanding the relations between the spatial distribution of inter-community travel demands and excessive VMT; (2) identifying the most vulnerable corridors affected by shared mobility services; and (3) evaluating the potentials of various regulatory policies and public surcharges in reducing empty vehicle mileage. Ultimately, the analysis tool will enable planning agencies to explore practical measures to improve the accessibility of suburban and rural communities with shared mobility services.]]></description>
      <pubDate>Sun, 12 Apr 2026 23:16:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2691661</guid>
    </item>
    <item>
      <title>Scaling Shared Autonomous Vehicle Services: Adoption, Demand, and System Implications</title>
      <link>https://rip.trb.org/View/2691658</link>
      <description><![CDATA[Autonomous vehicle (AV) operations are expanding across major U.S. cities, prompting public agencies and industry stakeholders to consider how shared AV services should be deployed, scaled, and integrated into existing transportation systems. Shared AVs have the potential to serve a wide range of travelers, including individuals who currently drive but may choose to use AVs occasionally, those seeking alternative travel options that allow more productive use of travel time, and travelers who may not consistently rely on a private vehicle for day-to-day transportation. Despite growing deployment, empirical evidence remains limited on how shared AV services will be adopted across regions, travel needs, and service contexts, and how their expansion can be guided to align with observed demand and system performance goals. Most prior AV studies were conducted before widespread deployment and relied on respondents with little to no direct exposure to AV services. As AV operations expand, more individuals are encountering these vehicles firsthand as passengers, road users, or through broader media exposure, creating a timely opportunity to reassess their implications for travel behavior and system-level outcomes. This transition from limited testing to sustained operations highlights the need for updated evidence that reflects current deployment conditions and real-world exposure. This study will generate policy-relevant evidence to support informed shared AV deployment by examining adoption expectations, anticipated use by trip purpose, and geographic variation across urban, suburban, and rural areas. Using data from the UC Davis Mobility Panel Survey and a targeted convenience sample from regions with active AV operations, researchers will analyze anticipated shared AV use for commuting, shopping, escorting, and healthcare travel. The project will also assess how service attributes such as pricing, wait times, and availability influence adoption and demand across various geographic contexts. By identifying where shared AV services are most likely to complement existing transportation services, the study will provide actionable guidance on deployment strategies, service design, and policy considerations, supporting policymakers and industry stakeholders in evaluating scaling pathways and system impacts as services expand.]]></description>
      <pubDate>Sun, 12 Apr 2026 23:06:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2691658</guid>
    </item>
    <item>
      <title>Naïve Subject Testing – Suite Emergency Passage Features</title>
      <link>https://rip.trb.org/View/2686617</link>
      <description><![CDATA[Applicants for type design approval are working to support their airline customers by installing passenger suites that include doors between the passenger and exit.  To install these doors, an exemption to 25.813(e) is required in which one of the conditions of the exemption is that the applicant must show the emergency passage feature (EPF) is simple and obvious to open.  Applicants achieve this showing by completing a naïve subject test.  The test method currently being used combines test parameters from the naïve subject test for evacuation specified in Part 25 Appendix J, the naïve subject test for life vest donning specified in TSO-C13, and the naïve subject test for floor proximity markings outlined in AC 25.812-1 and AC 25.812-2a.  The test method has several variables involved that are debated amongst regulators and applicants on how they should be controlled.  As a result, the test is run inconsistently, and variations in how the test is performed has led to an unlevel playing field amongst applicants, delays in certification testing by seat suppliers, and conflicting design approvals.   ]]></description>
      <pubDate>Wed, 01 Apr 2026 10:17:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2686617</guid>
    </item>
    <item>
      <title>Identifying Gaps in Transit Infrastructure and Potential Solutions</title>
      <link>https://rip.trb.org/View/2677556</link>
      <description><![CDATA[A lack of access to transit stops (due to safety concerns, poor first and last mile connections, a lack of shelter to protect from weather elements while waiting, etc.) often presents a significant barrier to using transit services, even when the service itself is well designed. However, for most bus transit projects, the feasibility study at the project planning stage only focuses on a buffer zone of 250 feet around any bus stop, as mandated and required by National Environmental Policy Act (NEPA). Such feasibility studies suffer from two drawbacks: (i) because of the limited spatial extent, they fail to capture the infrastructure gaps that may prevent people from utilizing the services; and (ii) because of limited interaction with current and potential users of the system, they fail to identify user-focused solutions to these gaps. Thus, such feasibility studies may overestimate the potential ridership while also lacking support from the local communities. As Colorado DOT (CDOT) starts implementing its planned bus rapid transit (BRT) services along some of the most heavily traveled corridors within the Denver Metro area, it is important to understand the infrastructure gaps and identify potential solutions to deliver the most benefit possible from transit infrastructure dollars.

The aim of the proposed project is to identify how and what infrastructure gaps need to be considered before evaluating the success of a transit-related investment. It also aims to create a set of potential solutions for those gaps, through user input of preferences and cost considerations. The research team uses one of the five proposed bus rapid transit projects within Denver Metro area as case study for this proposed project, complementing CDOT's ongoing work towards the BRT projects. Federal Boulevard BRT, the proposed case study BRT, is planned along one of the most heavily used travel corridors in Denver. The objectives of the project are: (i) to understand the current infrastructure needs to facilitate transit use, such as a lack of bus stop infrastructure, safety concerns, first and last-mile connectivity issues, etc.; and (ii) to identify solutions that best address the needs of the current and potential users. The proposed project will address these objectives through targeted data collection using surveys and app-based travel diary for the BRT catchment area larger than the required feasibility study (using a half-mile buffer around the bus stops instead of 250 feet as done in the NEPA study).]]></description>
      <pubDate>Wed, 04 Mar 2026 13:33:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2677556</guid>
    </item>
    <item>
      <title>UAM-enabled Multimodal Analysis of Transportation Systems for LA28 and beyond</title>
      <link>https://rip.trb.org/View/2676008</link>
      <description><![CDATA[The Los Angeles region has long been projected as a testing ground for urban air mobility (UAM), comprised of air taxis and drone delivery, given the region’s favorable climate, traffic problems, and tech-savvy ecosystem. The LA28 Olympic and Paralympic Games present an opportunity to make such a testing ground a reality. This project will model the potential for mode shifts, from ground to air taxi modes, with the LA28 Games as an initial case study. Modeling mode shift requires modeling the operation of an air taxi system. For that reason, this project will develop algorithms for optimal dispatch operation of a network of air taxis during LA28 and thereafter, and use those results to study the resulting mode shift from other ground-based modes of transportation. The results of this research can inform the work of the White House Task Force on the 2028 Summer Olympics (Established by Executive Order 14328), which includes the Secretary of Transportation. The results will also be relevant to both the public and private sector entities planning Olympic Games travel. By developing improved dispatch operation models for air taxis in a major urban area, and then predicting mode shifts from/to other ground modes, this research will also develop knowledge that will be helpful throughout Region 9 and the U.S. and which can help accelerate the maturing of the air taxi sector.]]></description>
      <pubDate>Tue, 03 Mar 2026 16:34:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/2676008</guid>
    </item>
    <item>
      <title>Potential Impact of Autonomous Vehicles on Reducing Congestion</title>
      <link>https://rip.trb.org/View/2676004</link>
      <description><![CDATA[Traffic congestion is a major problem in large metropolitan areas in the United States. In 2022, on average, a commuter lost about $1,259 in monetary terms annually due to congestion nationwide, which amounts to 8.7 billion lost hours in total. The lack of coordination among individual users, who make routing decisions independently based on current traffic information without anticipating that others may follow similar decision-making patterns, contributes significantly to the high cost of congestion.

The behavior of drivers optimizing their individual routes leads to a state known as the User Equilibrium (UE), leading to travel times that can be significantly higher than travel times from the System Optimal (SO), particularly in congested urban networks where the effects of individual decisions cascade throughout the system. With the future emergence of autonomous vehicles, it is possible that organizations may now own more of the fleet of vehicles and control their routing, providing the organization more options for balancing route selections and thus making it possible to find routing solutions closer to the system optimal. Driverless ride-hailing companies such as Waymo have already begun their service in five major cities across the United States and Tesla has started to test their Robotaxi service in Austin, Texas. The centralized routing capabilities of these autonomous services have the potential to reduce congestion. This first phase of this research project will develop centralized optimization models to quantify the impact of using autonomous vehicles on ride-hailing platforms in reducing congestion.]]></description>
      <pubDate>Tue, 03 Mar 2026 16:17:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2676004</guid>
    </item>
    <item>
      <title>Using Artificial Intelligence to Uncover How Safety Perception Influences Travel Behavior Shifts: Comparative &amp; Longitudinal Analysis for the Future of Autonomous Vehicle, Transit and Ride-hailing Services</title>
      <link>https://rip.trb.org/View/2655700</link>
      <description><![CDATA[Transit agencies and cities are increasingly overwhelmed by large volumes of unstructured data; yet they lack methodical, validated tools to turn safety narratives into operational indicators. This project addresses that gap by measuring and comparing public safety perception for autonomous-vehicle services (robotaxis), public transit, and ride-hailing services. It will assess how these perceptions relate to traveler profiles and mode choice in San Francisco and San Jose over a six-month period. San Francisco as a mature setting where robotaxis may compete with ride-hailing and transit, and San Jose as a newer coming deployment that provides a baseline for comparison and forward-looking extrapolation.
The research team will use artificial intelligence with human-audited classification to analyze public discourse drawn from news-comment threads and social-media posts, for example, discussions of disengagements, curb conflicts, yielding behavior, and interpersonal harm such as unwanted contact, theft, or assault. Validation will include human audit with inter-rater reliability (aiming for Cohen’s kappa of at least 0.60), time- and city-based cross-validation, and an error taxonomy with documented adjustments. The project will deliver (1) a transparent safety-perception taxonomy, (2) traveler-persona profiles linked to safety perceptions, (3) a lightweight dashboard for agencies and cities to explore time, place, and topic trends, and (4) operational and policy frameworks for improvements across all modes, organized into vehicle-level safety measures, station and hub operating practices, reporting and response mechanisms, and rider communication standards. The approach and workflow are replicable and can be extended to additional cities. The innovation lies in a reusable tool bridging research and practice providing concrete, methodical steps to turn qualitative narratives into consistent indicators they can trust. Agencies can adopt it to sort and prioritize incoming signals, rerun it with new data, and compare results across time and places to support day-to-day decisions and longer-term planning.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:09:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655700</guid>
    </item>
    <item>
      <title>Synthesizing Microtransit and Fixed Route Transit via Rider Hand Off to Improve Transit Efficiency</title>
      <link>https://rip.trb.org/View/2640190</link>
      <description><![CDATA[Microtransit programs can improve local mobility, but they often operate separately from fixed route bus networks. This separation can create gaps in connectivity and reduce the potential efficiency of both systems. This project will study how rider hand off strategies, where microtransit vehicles bring passengers directly to fixed route transit, can strengthen system performance. Using data from CTtransit, microtransit logs, and synthetic demand models, the research will simulate multimodal operations and evaluate how pickup schedules and transfer points influence wait times, travel times, and network utilization.

The project will develop an optimization framework to identify operating strategies that improve rider transfers and increase the efficiency of both modes. Scenario testing will measure the effects of integration on cost, ridership patterns, and service quality. The results will provide agencies with practical guidance on how to coordinate microtransit and fixed route services in ways that improve reliability and expand access to transit. These findings can support broader efforts to enhance mobility in Connecticut and inform similar initiatives in other regions.]]></description>
      <pubDate>Thu, 11 Dec 2025 13:47:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640190</guid>
    </item>
    <item>
      <title>Quick-Response Research on Long-Term Strategic Issues. Task 56. Student Fare Programs to Increase Ridership</title>
      <link>https://rip.trb.org/View/2636148</link>
      <description><![CDATA[Public transportation agencies across the U.S. have implemented student fare and pass programs in order to broaden their ridership base and provide new agency revenue streams. There exist a wide variety of programs and fare offerings for both university and secondary students, with different goals and funding sources.  Research suggests that exposure to high-quality transit in one’s 20s and 30s increases the likelihood of using transit later in life. Encouraging transit use by students can have positive long-term ridership impacts for the entire transit industry. 
TCRP Synthesis 131 examined university pass programs in a limited way in 2018. Since then, many more agencies have adopted these programs. Student fare programs vary widely depending on transit market, regional operating structure, fare systems, and types of institutions served.
Public transit agencies seeking to adopt new student fare programs or expand an existing program face uncertainty regarding costs, program feasibility, impacts on ridership and operations, and overall benefits. Research into the wide variety of student fare programs would assist in these evaluations.
The objective of this research is to provide information to assist transit agencies and policymakers in adopting and expanding student fare programs. The study should: Examine student fare programs at agencies and in regions of varying sizes, serving a range of student populations (secondary, community college, university, etc.); Examine funding mechanisms for student fare programs; Identify successful partnership models between transit agencies, and between agencies, schools and higher education; Evaluate program successes in terms of ridership impacts and travel behavior changes; Evaluate the operational impacts and challenges of student fare programs; Investigate transit operator/other worker perspectives; Assess opportunities and challenges for scaling student fare programs in different types of communities (urban, suburban, rural).]]></description>
      <pubDate>Mon, 08 Dec 2025 20:08:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2636148</guid>
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