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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>Use of Large Language Models to Improve Transportation Services</title>
      <link>https://rip.trb.org/View/2447009</link>
      <description><![CDATA[This project aims to leverage Large Language Models (LLMs) to enhance the analysis of public complaints and suggestions related to transportation systems. By processing feedback from multiple agencies, this study seeks to cluster and analyze common concerns, aiding agencies in aligning their services with public demands and safety needs. An open-source LLM model will be developed to safeguard privacy while enabling data-driven improvements in transportation services.]]></description>
      <pubDate>Wed, 30 Oct 2024 14:52:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2447009</guid>
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      <title>SPR-4916: Approaches to Enhance Pavement Condition Evaluation Based on Falling Weight Deflectometer (FWD) Data</title>
      <link>https://rip.trb.org/View/2422614</link>
      <description><![CDATA[The project involves upgrading FWD vans with cameras and sensors to capture comprehensive pavement data, including images. The project will develop an autonomous data analysis application using machine learning to assess pavement health, a custom Python-based back-calculation tool, and an interactive web-based dashboard for visualizing data and results. These deliverables aim to improve pavement evaluation accuracy, streamline analysis workflows, and facilitate timely maintenance, ultimately extending the lifespan of road infrastructures.]]></description>
      <pubDate>Tue, 27 Aug 2024 14:08:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422614</guid>
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    <item>
      <title>Incorporating Large Language Models (LLMs) into Transportation Safety Analytics</title>
      <link>https://rip.trb.org/View/2321641</link>
      <description><![CDATA[This project pioneers the integration of Large Language Models (LLMs) into transportation safety analytics to advance equity and improve data accessibility. Leveraging the Connecticut Crash Data Repository (CTCDR), the research team developed a novel system that enables users—regardless of technical background—to perform complex crash data analysis and generate visual reports using natural language queries. This LLM-powered interface streamlines data retrieval, reduces the need for specialized training, and facilitates the identification of safety disparities impacting vulnerable road users and underserved populations. By automating data cleaning, classification, and visualization, the system offers a cost-effective and scalable solution for state Departments of Transportation and policymakers seeking to meet federal safety and equity goals. The project demonstrates the transformative potential of AI in democratizing access to transportation data and shaping more informed safety interventions.]]></description>
      <pubDate>Fri, 12 Jan 2024 10:46:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2321641</guid>
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      <title>Improving the Mobility of Transportation Disadvantaged Older Adults: A Community-Based Intervention for the Hispanic/Latino Population</title>
      <link>https://rip.trb.org/View/1676643</link>
      <description><![CDATA[Driving  cessation  in  older  adults  can  present  a  significant  transportation  problem  and  public  health  dilemma. In particular, previously car-dependent older adults may struggle to access healthcare, attend social  activities,  and  conduct  errands  once  they  lose  the  ability  to  drive.  The  “Healthy  Buddy”  project  (https://www.hbuddy.org)  is  a  community-based  initiative  that  pairs  trained  college  students  with  transportation  disadvantaged  older  adults  to  help  them  identify  existing  transportation  and  health  resources in their communities. The Healthy Buddy Program was established out of the need to address health  equity  issues  associated  with  the  increasing  number  of  older  adults  who  experience  difficulties  accessing reliable and safe transportation.Given that the population of Hispanic/Latino older adults in the U.S. is projected to grow rapidly, making up 22% of all adults over age 65 by 2060 (HHS, 2015), the development of a Spanish-language accessible version  of  the  Healthy  Buddy  Program  is  crucial  and  timely.  Furthermore,  preliminary  qualitative  interviews  of  older  adults  in  Hillsborough  County,  Florida,  revealed  a  need  for  concerted  efforts  and  outreach to resolve equity issues that already exist for Hispanic/Latino populations. Pilot  research  for  the  Healthy  Buddy  Program  was  funded  through  the  Center  for  Transportation, Environment,  and  Community  Health  in 2018.  Preliminary  phases  included  program  development  and  pilot  testing  to  identify  barriers  and  opportunities  for  improving  older  adults’  access  to  community  transportation and health resources. This proposed study will build upon initial research by extending the outcomes of the program and adding a  Spanish-language version of the  Healthy Buddy Program for transportation  disadvantaged Hispanic/Latino older adults.  Through a multi-site implementation of  the Spanish-language version in Hillsborough County, Florida, and Dallas–Fort Worth,  Texas,  this project is expected to contribute to the development of a more equitable and inclusive transportation network at the national level.]]></description>
      <pubDate>Thu, 02 Jan 2020 15:23:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/1676643</guid>
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    <item>
      <title>WVDOH Web-Accessible Crash Database Deployment</title>
      <link>https://rip.trb.org/View/1300215</link>
      <description><![CDATA[Electronic crash reports that are completed by state, county, and local police officers in West Virginia are transmitted electronically to a central system provided by VS Visual Statement Incorporated.  The crash reports can be accessed using their ReportBeam collision reporting system.  Due to the limitations of the ReportBeam system for analyzing the crash data for safety applications, the West Virginia Division of Highways downloads the crash records from ReportBeam and utilizes Microsoft Access to generate various reports and conduct analysis.  As the amount of crash records in the database continue to increase, the ability of Microsoft Access to manage this data decreases.  In order to maximize the value and accessibility of the available crash data, the West Virginia Department of Highways (WVDOH) has initiated this project to deploy an online relational Structured Query Language (SQL) database.]]></description>
      <pubDate>Wed, 26 Feb 2014 01:00:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1300215</guid>
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      <title>HTML Preparation and 508 Compliance for Two Documents in the FHWA Office of Natural Environment</title>
      <link>https://rip.trb.org/View/1234782</link>
      <description><![CDATA[Federal Highway Administration's (FHWA) Office of Natural Environment has a requirement to convert two developed documents into HTML format and become compliant with Section 508 of the Rehabilitation Act (Section 508), so that they may be posted onto the organization's website. The contractor shall provide all material, equipment, labor, and items necessary to convert the two documents (when combined include 325 pages) into an HTML format and made 508 Compliant by including alternate text for all images, and headings and scopes for all table rows and columns.  Alternate text must be descriptive enough so that anyone unable to view the document gleans the same information as one would from reading the text]]></description>
      <pubDate>Thu, 03 Jan 2013 15:19:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/1234782</guid>
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