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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJzdWJqZWN0aWQiIHZhbHVlPSIxNzk5IiAvPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSI3MzAiIC8+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>Statewide Multimodal Destination Access Methods and Demographic Analysis</title>
      <link>https://rip.trb.org/View/2725639</link>
      <description><![CDATA[The Oregon Department of Transportation (ODOT) does not currently have a consistent, statewide method to evaluate destination access—whether people can reliably and affordably reach essential destinations such as employment, education, health care, and key services. While agency performance measures and analyses focus primarily on infrastructure conditions and system mobility, they do not answer whether investments are improving people’s ability to access what they need for daily life. Without a standardized destination access methodology, ODOT lacks a clear, data-driven basis for monitoring progress, understanding structural access gaps, or using access outcomes to inform investment decisions. 
OBJECTIVES: (1) Establish a standardized, agency-wide methodology for multimodal destination access analysis. ODOT currently performs destination access analysis on an ad hoc basis and does not have a consistent, documented method for statewide or cross-program use. This project will develop and test a unified approach that can be used across business lines for performance reporting, planning, and investment decision-making. (2) Integrate user profile analysis to identify which populations face transportation access gaps—and to what extent. This research will move beyond single-variable demographic assumptions and instead use data-informed definitions of at-risk populations to better understand who experiences structural access barriers and why. (3) Develop a tool for viewing destination accessibility metrics. The tool can be used to view accessibility by mode and destination type by region. The combination of transportation and land use data will enable planners to understand existing accessibility conditions and needs in specific areas.  This tool would be usable for the ODOT Capital Investment Plan (CIP), local transportation system plans, and other programs where access measures offer utility. 
This research fulfills a need for a destination access methodology that supports ODOT policy, planning, and prioritization. With the results of this research, ODOT will be able to answer critical questions about how the transportation system is serving residents. Access metrics can play a critical role in vehicle miles of travel (VMT) per capita and emissions reduction strategies by informing staff on which areas have feasible multimodal access. ]]></description>
      <pubDate>Wed, 08 Jul 2026 16:48:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/2725639</guid>
    </item>
    <item>
      <title>How do perceptions of transportation challenges influence travel behavior for people with disabilities?</title>
      <link>https://rip.trb.org/View/2702517</link>
      <description><![CDATA[Although it has been over thirty years since the Americans with Disabilities Act (ADA) was enacted, people with disabilities—who represent approximately one-quarter of the U.S. population—continue to face significant barriers to mobility and access. They tend to make fewer trips and are more reliant on others, largely due to shortcomings in pedestrian infrastructure, transit, and for-hire vehicle services, and specialized paratransit options, as well as the negative attitude of drivers to them. While substantial research has documented the wide range of mobility and access challenges faced by people with disabilities, there has been limited investigation into how these challenges affect their mode choice decisions. This project will develop and administer a web-based survey, targeting a sample of California residents with disabilities, to explore how disability shapes mode choice, factoring in perceptions of the inaccessibility of transportation infrastructure, mode design-induced challenges, and ableism faced while travelling by different modes. This project will explore how these problems influence their willingness to use paratransit and trip frequency to activity centers. The research team will apply various analytical techniques, including descriptive statistics, basic comparative statistical tests, and multinomial logistic regression, to address the research questions. To ensure the survey is relevant and impactful, the team will collaborate with organizations serving people with disabilities, both to inform the survey design and to disseminate findings that support broader universal access goals shared by these organizations and public agencies.]]></description>
      <pubDate>Thu, 14 May 2026 16:54:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702517</guid>
    </item>
    <item>
      <title>Assessment of Litter Hot Spot Areas for Targeted Reduction in Prince George's County</title>
      <link>https://rip.trb.org/View/2701237</link>
      <description><![CDATA[The frequency and volume of litter and illegal dumping on state and county roadways in Prince George’s County are increasing, despite efforts like scheduled litter blitzes, which have shown limited long-term success. Over the past five years, the Maryland Department of Transportation State Highway Administration (MDOT SHA) spent approximately $42 million removing litter and debris, with last year’s costs alone reaching $15 million—the equivalent of 45 new dump trucks or nearly 60 miles of resurfaced roads (Source WBAL News: https://www.msn.com/en-us/news/us/drivers-watch-out-for-operation-clean-sweep-maryland/ar-BB1jY1rr). These expenditures are unsustainable, especially given recent fiscal shortfalls. This joint research proposal, submitted by District 3 and Prince George’s County Department of Public Works and Transportation (DPW&T), aims to evaluate litter hot spots at the census tract level, as current efforts have not addressed the root causes of the issue. Prince George’s County, a well-resourced and educated area, presents unique challenges, suggesting the problem extends beyond awareness or resource deficits. ]]></description>
      <pubDate>Wed, 13 May 2026 09:15:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2701237</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>Health-Aware Edge Computing for Durable Autonomous Transportation</title>
      <link>https://rip.trb.org/View/2696026</link>
      <description><![CDATA[Across global markets, transportation systems are rapidly evolving toward automation, pervasive sensing, and intelligent decision-making capabilities. These advancements are often designed primarily around traditional metrics, such as safety, throughput, and cost. Modern autonomous and semi-autonomous systems introduce new types of human exposures (e.g., fatigues, cognitive stress, motion discomfort) and new system constraints (e.g., battery degradation, vibration-induced wear, thermal loads). If left unmanaged, these exposures degrade long-term system performance, reduce user trust and adoption, and impose hidden lifecycle and health costs. This project proposes a new research paradigm for Health-Aware and Durable Transportation Systems, enabling through advanced technologies in autonomous driving, edge computing, and optimized machine learning. We envision that transportation systems can be engineered to actively sense, model, and mitigate human and mechanical exposures, turning transportation into a joint human-machine health ecosystem. The research objectives include: 1) develop joint occupant/vehicle exposure models that quantify health and mechanical burdens, 2) enable adaptive autonomy strategies that mitigate cognitive stress, fatigue, and mechanical wear, and 3) build edge computing framework for efficient inference and control.  ]]></description>
      <pubDate>Thu, 23 Apr 2026 17:32:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696026</guid>
    </item>
    <item>
      <title>Customizing Transportation Services and Technologies Based on Rural Patient Healthcare Needs</title>
      <link>https://rip.trb.org/View/2667211</link>
      <description><![CDATA[The purpose of this project is to build on previous research to better understand the various linkages between specific comorbidities, lifestyle habits and targeted public transportation-related services and technologies. In addition, the project will demonstrate how these services and technologies can be adapted specifically for rural populations to secure better health outcomes. The primary research methods for this project will be as follows: 1) obtain literature about risk factors for specific comorbidities and lifestyle habits and how they interact with healthcare system access ; 2) use data from the University of Kentucky’s Healthcare’s Center for Clinical and Translational Studies and other Southeastern health systems to create a panel analysis of health outcomes based on University of Kentucky’s patient surveys, lifestyle habits, known comorbidities and diagnoses, and patient histories; 3) review materials as needed to determine best practices and synthesize findings for transportation-based support for specific medical conditions for rural residents; and 4) work with technology transfer programs and other stakeholders to develop a tool and/or outreach materials based on project findings for technology transfer professionals to improve transportation efficiency, technology and system innovation in trainings for transit and healthcare providers. The goal is to help both health and transportation providers to implement customizable healthcare mobility strategies based on their logistical capacity and patient needs.]]></description>
      <pubDate>Mon, 23 Feb 2026 14:19:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2667211</guid>
    </item>
    <item>
      <title>Driver to Non-Driver Transitions: Related Health, Mobility and Safety Outcomes</title>
      <link>https://rip.trb.org/View/2671991</link>
      <description><![CDATA[This project involves analyzing the impacts of becoming a non-driver (suddenly or gradually) in Wisconsin and nationally and effects on health, mobility, and safety outcomes. The project will analyze health, quality of life and mobility outcomes for drivers who are no longer able to drive. The researchers will analyze the safety, mobility, and quality of life outcomes for those who have suddenly or gradually become non-drivers. Analysis should focus on adult non-drivers of all ages and demographics, with particular emphasis on adults aging in place and urban versus rural areas. Once the analyses are conducted and complete, the researchers will report findings and provide recommendations for policies that lead to improved outcomes—namely increases in mobility and safety benefits for the entire state. Recommendations will help Wisconsin Department of Transportation (WisDOT) understand how to best offset impacts to mobility for individuals suddenly or gradually transitioning from being drivers to non-drivers.]]></description>
      <pubDate>Wed, 18 Feb 2026 11:39:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2671991</guid>
    </item>
    <item>
      <title>Enabling Mobility for Older Adults in the US</title>
      <link>https://rip.trb.org/View/2669552</link>
      <description><![CDATA[Driving is essential for the preservation of functional independence for older adults, yet there is a growing number of older adult drivers with comorbid health conditions that might impair their ability to drive safely. Older adult drivers are overrepresented in motor vehicle crash deaths and injuries, which is a major public health concern. The purpose of this project is to (1) develop a comprehensive understanding of the mobility needs and challenges of older adults in the United States, and (2) develop an innovative tool to extend their safety while they drive.  

Aim 1: Develop a comprehensive understanding of the mobility needs and challenges of older adults  

To develop a comprehensive understanding of the mobility needs of older adults, the research team will analyze data from a nationally representative survey of U.S. adults aged 65 and older. The survey contains a comprehensive set of questions that explore driving behavior, transportation options, mobility limitations, and attitudes toward future transportation technologies and policies among adults aged 65 and older.   

Aim 2: Develop an innovative tool to extend their safety while they drive.  

The goal of this project is to understand older adults’ perceptions of an app (StreetCoach) that provides a driving score based on actual driving behavior. A number of apps exist for older adult drivers but the perceptions of older drivers towards their driving score is poorly understood. This study will use a sequential explanatory research design by asking 10 older adults to download and use the app for 60 days. Following this, the research team will conduct in-depth interviews with the participants to gain an understanding of their perception and interpretation of their telematics score, and what factors might motivate them to change their driving to improve the score.   ]]></description>
      <pubDate>Thu, 12 Feb 2026 15:16:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669552</guid>
    </item>
    <item>
      <title>Healthy Micromobility: Moving From Crisis to Opportunity</title>
      <link>https://rip.trb.org/View/2652680</link>
      <description><![CDATA[Micromobility, including e-scooters and e-bikes, is an emerging transportation mode with the potential to alleviate congestion and improve urban mobility. However, prior research has primarily focused on safety risks and injury rates, with less attention given to its potential benefits, such as improved accessibility, reduced vehicle miles traveled (VMT), and enhanced health through active transportation. This project aims to provide a more comprehensive assessment of both the risks and benefits of electric micromobility within the U.S. transportation system using a combination of literature review, survey research, and systems dynamic modeling. The study examines how electric micromobility reduces VMT while also evaluating the health trade-offs related to safety risks and active transportation benefits. The project consists of three main aims: (1) a targeted literature review to synthesize existing evidence on electrified micromobility’s health impacts, (2) a nationally representative survey to capture user behavior, trip substitution patterns, and safety concerns, and (3) the development of a system dynamics simulation model to quantify the net health effects across diverse urban settings.     ]]></description>
      <pubDate>Tue, 13 Jan 2026 16:27:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652680</guid>
    </item>
    <item>
      <title>Bridging Data Gaps with Modeled Data from Generative AI: Advancing Health in Transportation Research</title>
      <link>https://rip.trb.org/View/2652171</link>
      <description><![CDATA[Transportation-related factors, such as air quality changes and exposure disparities, have significant impact on health outcome. Communities near high-traffic corridors experience elevated exposure levels, yet efforts to assess these impacts are hindered by the lack of high-resolution health and socio-demographic datasets. Traditional air quality models, such as dispersion and interpolation techniques, estimate pollutant distributions but struggle to capture localized exposure variations and real-world uncertainties due to their reliance on static assumptions. These limitations reduce the precision of transportation health impact assessments. 

This project addresses data gaps in air quality and health outcomes by integrating AI-generated data with  traditional modeling techniques. Bridging the data gap is essential to improving exposure assessments and provide a more comprehensive understanding of transportation-related health effects. The research develops and trains generative AI models for data augmentation, using harmonized datasets to create high-fidelity modeled data that reflects real-world patterns. Furthermore, we integrate the trained AI models with air quality simulation models to estimated transportation-related air quality scenarios and assess potential health impacts.
 
The project produces a validated generative AI model for data augmentation, generating high-resolution datasets that enhance geographic and demographic granularity in transportation health research. The application of scenario-based health impact simulations provides new insights into the relationships between air quality and health outcomes, improving the ability to evaluate transportation-related interventions. By combining AI-driven data synthesis with traditional modeling approaches, this research advances methodologies for transportation and environmental health assessments, providing more reliable data for exposure studies and policy evaluations. 
]]></description>
      <pubDate>Tue, 13 Jan 2026 16:10:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652171</guid>
    </item>
    <item>
      <title>Health and Activity Impacts of Student Commute Modes</title>
      <link>https://rip.trb.org/View/2652176</link>
      <description><![CDATA[Active school transportation can profoundly influence children’s health, safety, and wellbeing. This project will investigate how different school commute modes – walking, bicycling, school bus, or private car – affect student physical activity and health, exposure to traffic-related air pollutants, safety, and travel disparity. Focusing on Texas school districts that currently or historically participate in Safe Routes to School (SRTS) programs, we will combine new data collection with existing evidence to evaluate the benefits and challenges of various commute modes. The study will also examine how shifting school trips to active modes may reduce vehicle emissions near schools and improve air quality. We will conduct surveys to quantify students’ physical activity during commutes, assess their exposure to emissions, and gauge perceptions of safety. Recent literature (2015–2025) will be synthesized to identify how school transportation choices affect student health (e.g. obesity, respiratory health, mental wellbeing) and safety outcomes, including disparities by socioeconomic status and geography. By evaluating SRTS interventions’ effectiveness in Texas communities, the project will fill critical gaps in understanding the multi-faceted impacts of commute mode on student wellbeing. Expected outcomes include practical recommendations for school districts and transportation agencies to design safer, healthier school travel environments. ]]></description>
      <pubDate>Tue, 13 Jan 2026 15:25:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652176</guid>
    </item>
    <item>
      <title>Transportation and Mental Health in Central Texas Using 211 Call Center Data – An Exploratory Analysis</title>
      <link>https://rip.trb.org/View/2652177</link>
      <description><![CDATA[Mental health is an important part of an individual’s well-being and has been included as a key topic by the U.S. Centers for Disease Control and Prevention. Lack of access to affordable and efficient transportation can isolate individuals, limiting their ability to maintain employment, attend healthcare appointments, or engage in social and recreational activities—all of which are vital for mental well-being.  Long commutes, traffic congestion, and unreliable transit can contribute to chronic stress, anxiety, and fatigue, especially in urban environments. Active transportation options like walking and cycling not only reduce stress but also promote physical activity, which can reduce symptoms of depression.  
The research project aims to understand the multifaceted relationships between transportation and mental health by conducting a literature review using Latent Dirichlet Allocation (LDA) in topic modeling to identify prevailing themes and research trends in transportation and mental health. Also, through collaboration with United Way for Greater Austin, this project will incorporate insights from 211 Call Center staff and volunteers to better understand transportation-related mental health concerns, from a frontline service perspective. The project will then analyze 211 Call Center data provided by the United Way for Greater Austin. This analysis will explore spatial and temporal variations in mental health-related issues and examine how transportation correlates with mental health concerns. Caller comments, when available, will complement the quantitative data by providing personal context and deepening the understanding of lived experiences. Ultimately, the findings will inform policy recommendations aimed at addressing transportation barriers as a means to improve mental health outcomes in communities.    
]]></description>
      <pubDate>Tue, 13 Jan 2026 15:19:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652177</guid>
    </item>
    <item>
      <title>Integrated Transportation and Health Impact Modeling Tool for U.S. Cities </title>
      <link>https://rip.trb.org/View/2652180</link>
      <description><![CDATA[The health of the American people is a national priority, and ensuring that transportation policies support strong communities, economic prosperity, and public well-being is a critical challenge that requires holistic solutions. This project will deliver groundbreaking research that directly informs transportation policies to improve traffic safety, air quality, and physical activity among transportation users in major American cities. These policies will help reduce preventable health burdens, cut healthcare costs, and enhance both community well-being and the cost-efficiency of our transportation systems. In the first stage of this project, we will review and update the underlying literature to refine and potentially extend the framework. We will develop updated visualizations to help transportation and public health agencies identify and communicate the various pathways linking transportation and health. By incorporating new evidence and addressing critical gaps, we will ensure the framework remains relevant for shaping future transportation policies at local, state, and national levels. During this stage, we will engage key stakeholders—such as transportation and public health agencies—by presenting our updated model, gathering their feedback, and enhancing our understanding of how transportation choices impact health outcomes. 
In the second stage, we will systematically collect, clean, quality-assess, harmonize, and integrate data from diverse sources to underpin subsequent quantitative modeling. This modeling exercise will examine pathways related to vehicle crashes/traffic safety, transportation-related air pollution, transportation-related physical activity, and any additional pathways deemed feasible for quantitative modeling based on data availability and strength of evidence. The data sources will include census population counts, geographic information system layers, transportation network layers and average vehicle speed data, household travel surveys, physical activity surveys, police crash records for fatal and non-fatal incidents, baseline health outcome rates, and associations between transportation factors and health outcomes as derived from systematic reviews and meta-analyses (i.e., dose- and exposure-response functions). This will allow us to construct a detailed and representative model of American mobility patterns, their health impacts through safety, air quality, and physical activity, and how targeted policies can mitigate risks and enhance benefits holistically across these pathways. We will focus on practical solutions that include policy instruments such as shifting a portion of trips to electric vehicles, electric buses, and electric bikes—while ensuring alignment with existing travel survey data for realism. 
]]></description>
      <pubDate>Tue, 13 Jan 2026 15:05:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652180</guid>
    </item>
    <item>
      <title>Real-Time Corridor Modeling using Dynamic Vehicle Fleet Composition Data</title>
      <link>https://rip.trb.org/View/2652183</link>
      <description><![CDATA[Urban transportation systems support personal mobility, but are also a significant source of air pollution, with disproportionate impacts on communities near high-traffic corridors.  If electric vehicle (EV) adoption continues to increase, pollutant concentration distributions will change, potentially requiring more detailed assessments of air quality and health impacts.  Traditional air quality impact assessment for transportation projects employs microscale modeling using the MOVES and AERMOD models.  These models rely heavily on fleet composition data (vehicle classes, ages, and fuel types), yet existing assumptions often fail to capture the spatial and temporal variability in vehicle usage.  For example, research in Atlanta has revealed that the on-road freeway fleet during the morning peak tends to be a lot younger (and cleaner) than the average vehicle fleet, likely because commuters take their best vehicles to work.  This research to be conducted in this proposed project will develop an integrated framework that combines real-time traffic simulation, air quality impact assessment, and health impact assessment to assess the effects of different vehicle fleets on air quality and public health.  Using the TransportSim model, MOVES model, and AERMOD dispersion model, this study will analyze vehicle fleet dynamics across multiple urban corridors in the Atlanta metro area for different fleet compositions.  The research results will also identify shifts in pollutant concentration hotspots and their implications in spatial health impact assessment across neighborhoods as EVs enter the fleet.  By improving the accuracy of corridor-level pollutant modeling, this study will support the identification of strategies designed to mitigate air pollution and protect public health.  ]]></description>
      <pubDate>Tue, 13 Jan 2026 14:20:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652183</guid>
    </item>
    <item>
      <title>Promoting Teachers' and Young Learners' Engagement of Transportation Issues</title>
      <link>https://rip.trb.org/View/2652184</link>
      <description><![CDATA[This project will develop, implement, and distribute standards-aligned curriculum that focuses on real-world transportation issues to include stormwater runoff and erosion mitigation and air quality issues. The curriculum will serve as educative curriculum materials (ECM) for teachers as they engage students with research-based instruction focused on Texas Transportation Institute (TTI) and transportation industry research and recommendations, science content ideas (e.g., water cycle, erosion), and non-science considerations (e.g., economic, ethical, social, legal). The curriculum will also profile the authentic work of TTI researchers, other science, technology, engineering, and mathematics (STEM)  professionals, and the characteristics of their work. Research will be conducted on how professional and curriculum development affects knowledge bases and practices, and how implemented curriculum impacts students’ knowledge of science and engagement of real-world societally important scientific issues.   ]]></description>
      <pubDate>Tue, 13 Jan 2026 14:13:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2652184</guid>
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