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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJzdWJqZWN0aWQiIHZhbHVlPSIxNzc4IiAvPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSI3MzAiIC8+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>
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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>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Evaluation of Transit Signal Display Options</title>
      <link>https://rip.trb.org/View/2716608</link>
      <description><![CDATA[There is a need to assess the operational and safety impacts of alternative transit signal
displays and inform recommendations to be incorporated in state and national transit signal
design guidelines. OBJECTIVES: 1. Understand the current state of practice on the implementation of transit signal displays through a thorough review of the literature and outreach to transit agencies and other relevant stakeholders. 2. Explore transit operator preferences regarding positioning and display of transit signals through a survey to transit operators. 3. Investigate correlations between crashes and transit signal displays, through crash report analyses. 4. Understand driver behavior when encountering transit signals through field observations, static evaluation surveys, and driving simulation. 5. Develop recommendations for consideration in the next version of the Manual on Uniform Traffic Control Devices (MUTCD) regarding positioning and display design of transit signals.]]></description>
      <pubDate>Thu, 18 Jun 2026 10:03:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2716608</guid>
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    <item>
      <title>Identifying, Assessing, and Managing Events for Critical Infrastructure Resilience in Surface Transportation</title>
      <link>https://rip.trb.org/View/2712209</link>
      <description><![CDATA[State departments of transportation (DOTs) play an important role in protecting critical transportation infrastructure from natural hazards, human-caused events, and emerging threats. However, there is currently no consistent methodology for identifying and assessing critical infrastructure within surface transportation systems. Definitions of “criticality” vary across agencies, and existing approaches often lack integration with broader resilience, security, and emergency management frameworks.

Previous research has focused on specific threats, such as terrorism or cybersecurity, or on resilience to natural hazards, but gaps remain in developing proactive, risk-based approaches that address the full range of threats and system interdependencies. Transportation systems are closely linked with other infrastructure sectors, such as power and water systems, and disruptions can have cascading impacts across regions.

Research is needed to help state DOTs better define their role in coordinating with law enforcement, emergency responders, and other planning partners and system owners to enhance preparedness, response capabilities, proactive resilience planning, stakeholder coordination, and implementation of national infrastructure protection frameworks.

The objectives of this research are to (1) identify and assess surface transportation system interdependencies and develop a risk-based approach to managing a wide range of threats; and (2) develop an infrastructure resilience guide with case studies, a list of stakeholder roles and responsibilities, and decision-making tools to help state DOTs identify, assess, and manage risks to critical infrastructure within surface transportation systems.]]></description>
      <pubDate>Wed, 10 Jun 2026 11:41:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712209</guid>
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    <item>
      <title>Assessing the Reliability and Usability of Mobile Ticketing App Data for Transit Analytics: A Case Study of Unitrans in Davis, California</title>
      <link>https://rip.trb.org/View/2702581</link>
      <description><![CDATA[Mobile ticketing apps have become increasingly popular among transit agencies due to their cost efficiency and ability to streamline payments. Beyond operational efficiencies, these apps also generate vast travel data with the potential to support transit agencies in decision-making. However, this data contains incomplete trip information and suffers from representation bias. Several questions remain unanswered: Is this data representative of all transit riders? If so, what are the potential applications? 

This project will address this gap by evaluating the potential applications and representativeness of app data. The research will focus on ZipPass, a mobile ticketing app used by Unitrans in Davis, California. To date, ZipPass has already generated over one million spatial activation records. The project team devised a strategy to integrate ZipPass data with the onboard transit survey and the UC Davis campus travel survey. The team will also conduct a targeted survey of active ZipPass users to supplement rider-specific and trip-level information. The project will explore how ZipPass data, along with support from supplementary data sources, can be used for two potential applications to support the agency: (1) estimating transit ridership and (2) understanding riders' origin-destinations. 

The research will provide valuable insights to transit agencies looking to harness mobile ticketing data for operational purposes. Since periodic onboard transit surveys are required for federal funding, both mobile ticketing data and transit survey data are available to agencies at no extra expense. Small agencies can leverage our findings to integrate at least these two datasets and effectively utilize them for operational improvement.]]></description>
      <pubDate>Thu, 14 May 2026 16:51:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702581</guid>
    </item>
    <item>
      <title>Evaluating Behavioral Responses to Mobility Credits and Ridehailing Integration in a Digital Mobility System</title>
      <link>https://rip.trb.org/View/2702725</link>
      <description><![CDATA[Digital mobility platforms are increasingly adopted by public agencies to coordinate multimodal travel, streamline fare payment, and improve efficiency. However, there is limited empirical evidence on how users respond to platform-based incentives and integrated services in real-world settings, as most studies rely on stated preference data or simulations. This project analyzes user behavior on Vamos-EZHub, a public digital mobility platform that integrates trip planning, fare payment, and access to services including local transit and ridehailing. It evaluates behavioral responses to two sequential interventions on Vamos-EZHub: (1) the introduction of prepaid mobility credits and (2) the integration of a transit-triggered ridehailing credit. 

Using longitudinal platform telemetry, ridehailing trip records, transit fare activation data, and General Transit Feed Specification (GTFS) data, the project examines how mobility and ridehailing credits affect platform engagement, transit and ridehailing use, first/last-mile connectivity, and spatial and temporal patterns of linked travel. Two-way fixed effects and event-study models are used to identify behavioral changes associated with each intervention. A geospatial-temporal algorithm classifies ridehailing trips connecting to transit, and stop- level regression models identify transit service and network characteristics associated with demand for linked trips. 

Expected outcomes include quantitative estimates of the influence of mobility credits and ridehailing integration on multimodal coordination, identification of service characteristics associated with higher demand for linked trips, and a reproducible analytical framework. The results will inform data-driven platform design, operational planning, and integration strategies for public agencies managing digital mobility platforms, while providing evidence to guide coordination with private ridehailing partners to improve system efficiency and reliability.]]></description>
      <pubDate>Thu, 14 May 2026 16:36:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702725</guid>
    </item>
    <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>
    </item>
    <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>
    </item>
    <item>
      <title>How Do People Receive Information About Public Transit?</title>
      <link>https://rip.trb.org/View/2696850</link>
      <description><![CDATA[Providing transit information helps passengers adapt when service is unreliable and has been shown to decrease wait times, reduce overall travel time, increase ridership, increase satisfaction with transit, and increase perceptions of personal security. However, to date, there is limited evidence for how riders prefer to access and use transit information. A variety of methods are available, including websites, apps, signage, and transit ambassadors or drivers, but which methods of information are most used by riders and how does it differ by the type of rider and type of trip? Riders need real time information to be accurate, but how does inaccurate information impact their trip? In addition, how do riders plan their travel pre-trip, such as understanding hours and frequency of service, finding the stop, and understanding payment mechanism? This research aims to explore how both transit riders and non-riders access public transit information for the purpose of planning and taking trips on transit to answer these questions. This work will improve understanding of customer perspective to aid agencies in providing better transit rider information in a cost-effective manner, thus improving the long-term viability of the transportation system by increasing demand for transit.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:12:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696850</guid>
    </item>
    <item>
      <title>Car or Public Transit? Exploring Factors Affecting Mode Choice in the Mobility of Care</title>
      <link>https://rip.trb.org/View/2696849</link>
      <description><![CDATA[This project explores the factors affecting mode choice decisions in the mobility of care. By applying the discrete choice modeling of Nested Logit (NL) and the Multiple Discrete Continuous Extreme Value (MDCEV) to the 2022 National Household Travel Survey (2022 NHTS), this study explores factors regarding where transit service may better accommodate travel needs in serving care trips. Also, it highlights how public transit contributes to reducing household travel generated by care trips. The researchers expect to obtain distinct characteristics of care trips and the socio-demographics of those who travel for care to inform the California Department of Transportation (Caltrans) which transit-related manuals, guidelines, and policies are critical to accommodate travel and their mobility of care. Results are also useful for transit agencies when considering aspects to improve their service in care trips.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:10:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696849</guid>
    </item>
    <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>
    </item>
    <item>
      <title>Which Way Forward? Learning from Global Informal Transport Networks to Inform Microtransit Services in California</title>
      <link>https://rip.trb.org/View/2695811</link>
      <description><![CDATA[This proposed 12-month study seeks to draw upon lessons learned from informal transit systems, particularly from the developing world, to inform the development and implementation of demand-responsive transit (often referred to microtransit) strategies in California. Through a comprehensive review of existing literature, case studies (n= up to 5), and expert interviews (n=15-20), this study aims to identify lessons learned, challenges, and opportunities associated with informal transit operations. Leveraging this understanding, the research will assess how such lessons can be applied to the design, deployment, and evaluation of microtransit and other demand-responsive services in California communities, including transportation network companies (TNC) and taxi models. Key areas of focus include business and operational models, fare affordability and financial sustainability (including operational costs), and potential policy frameworks. By synthesizing insights from informal transit experiences internationally, this proposed study seeks to contribute to the development of efficient and sustainable microtransit and demand-responsive strategies tailored to the diverse needs of all travelers.]]></description>
      <pubDate>Thu, 23 Apr 2026 18:05:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2695811</guid>
    </item>
    <item>
      <title>Disability, Mode Perceptions, and Travel Behavior</title>
      <link>https://rip.trb.org/View/2695812</link>
      <description><![CDATA[Despite the more than three decades since the passage of the Americans with Disabilities Act (ADA), people with disabilities, which comprise roughly one quarter of the US population, still face considerable challenges to their mobility and access. They make fewer trips and are more dependent on others because of deficiencies in pedestrian infrastructure, transit and for-hire vehicles, and specialized paratransit services. While there is a considerable amount of research that identifies the breadth of mobility challenges and access barriers, limited research has addressed how these mobility challenges influence mode choice for people with disabilities. This project will develop and administer a web-based survey by oversampling California residents with disabilities to understand how disability influences mode choice, accounting for perceptions of the built environment and mode-specific challenges. The research team anticipates using several analytical methods to answer the research questions, including descriptive statistics, basic statistical tests of comparison, and multinomial logistic regression. The research team aims to engage with disability-serving organizations to ensure that the survey reflects real concerns and will provide meaningful data, and to share results in support of universal access goals that the organizations and public agencies are pursuing.]]></description>
      <pubDate>Thu, 23 Apr 2026 17:58:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/2695812</guid>
    </item>
    <item>
      <title>Continuous approximation models for rural transit network design</title>
      <link>https://rip.trb.org/View/2691671</link>
      <description><![CDATA[The purpose of this project is to discover new continuous approximation models for public transit network design, with a specific focus on rural areas where access to transit and coverage present significant challenges. Rural transit systems face unique constraints in connecting dispersed population centers while maintaining economic viability, which necessitates a modelling approach that addresses multiple competing objectives simultaneously. The continuous approximation paradigm is a quantitative method for solving logistics problems using a small set of parameters to model a complex system, which results in simple algebraic expressions that are easier to manage than (for example) large‐scale optimization models. As a further benefit, one often obtains insights from these simpler formulations that determine what affects the outcome most significantly. Although continuous approximation models have been used for over 60 years in logistics systems analysis, there has been very little research conducted on their application to problems in rural transit networks, likely due to their distinctive spatial characteristics and coverage requirements. Recent research demonstrates that limited flexibility yields disproportionate benefits in logistics systems. This project will combine tools from geospatial optimization, computational geometry, and geometric probability theory to formulate new models that will solve these problems. Furthermore, these models will identify which complementary infrastructure investments would most effectively increase transit availability and ridership in rural counties. The research outcomes include both theoretical advances in continuous approximation methodology and practical planning tools for rural transit agencies with limited computational resources.]]></description>
      <pubDate>Sun, 12 Apr 2026 23:45:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2691671</guid>
    </item>
    <item>
      <title>Efficient Mobility for Rural Communities</title>
      <link>https://rip.trb.org/View/2683240</link>
      <description><![CDATA[Rural communities face unique transportation challenges due to low population density, dispersed destinations, and limited resources. Efficient mobility requires strategies that both optimize existing transit systems and embrace innovative service models. This project integrates two lines of research that can support efficient mobility and access to active modes and destinations in rural areas. The first focuses on right-sizing rural transit fleets and the second, on analyzing modal shifts from shared-use mobility services.  

On the vehicle procurement side, rural agencies must balance capital and operating costs, service quality, and reliability while meeting the capacity needs of their riders. When procuring vehicles, rural transit operators choose between transit buses, cutaways, vans, and minivans of various sizes. Each has its own advantages and disadvantages regarding capital costs, operating costs, performance, service quality, and ability to meet the needs of their users. This study builds upon previous research to develop spreadsheet-based user tools that can help rural agencies and state departments of transportation (DOTs) make these decisions. This research improves upon the decision tools developed in a previous study by incorporating new models for the capacity needs of rural transit. Previous decision tools provide guidance on the types and sizes of vehicles to procure but they lack the ability to estimate capacity needs for individual agencies. This study develops a vehicle procurement decision model that incorporates a more sophisticated capacity needs analysis. The result will be a tool that estimates capacity needs of an agency and provides guidance on the number, types, and sizes of vehicles that can best meet that capacity need while improving efficiency and meeting the unique needs of the transit agency.  

A second tool to be developed by the study is an optimization tool. The study will improve upon a previously developed optimization model by incorporating more detailed estimates for lifecycle costs of different types and sizes of vehicles. The study will consider transit buses, cutaways, vans, and minivans of different sizes and seating capacities and include more detailed analysis of the operating costs for each vehicle type and the overall lifecycle costs. This will be incorporated into an optimization model that will minimize total costs, including capital and operating costs, for an agency while meeting capacity needs and service requirements and considering the impact of the fleet configuration on service quality.  

At the same time, emerging technology-enabled shared-use services—such as ridesourcing, microtransit, bikesharing, and carsharing—are transforming mobility in rural areas. By analyzing National Household Travel Survey data and documenting real-world deployments, the study will evaluate adoption patterns, service models, and performance outcomes of rural shared-use systems. This analysis will identify factors contributing to the success or failure of shared-use mobility initiatives and provide actionable strategies for rural agencies and policymakers . ]]></description>
      <pubDate>Tue, 24 Mar 2026 14:22:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/2683240</guid>
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