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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" 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>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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      <title>Low-Frequency High-Impact Travel for Data Analysis</title>
      <link>https://trid.trb.org/View/2709248</link>
      <description><![CDATA[Low-incidence travel behavior is difficult to capture in a traditional household travel study, where typically one to seven days of travel are collected from a representative sample of households. These behaviors may include travel modes used frequently by a small number of people (bicycling, carshare/vanpool), emerging modes not yet widely adopted (e-bikes, scooters, automated vehicles), complex household travel interactions, or infrequent behaviors such as rideshare use, long-distance travel, and trip replacement behavior such as home delivery of goods and services.

Because these behaviors occur infrequently, traditional survey methods often fail to collect enough observations for accurate estimation in travel demand models. A sufficient number of surveys—approximately 1,000 observations per market segment—is needed to support reliable analysis and forecasting. Despite their low incidence, many of these behaviors have significant impacts on transportation systems.

More than 40 state departments of transportation (DOTs) maintain statewide travel models that require accurate long-distance travel data to support costly intercity highway and rail investments. Emerging travel modes are also becoming critical policy issues in regional and statewide planning efforts.

The objective of this research is to identify and analyze methods for sampling people, households, and incidences of rare or emerging travel behaviors and determine how these methods can be incorporated into household travel survey data collection.]]></description>
      <pubDate>Tue, 02 Jun 2026 13:56:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709248</guid>
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    <item>
      <title>Wayside Detector System Study</title>
      <link>https://trid.trb.org/View/2689420</link>
      <description><![CDATA[This report evaluates both existing and emerging wayside detector systems, assessing their effectiveness, life-cycle costs, and broader industry impacts, to satisfy Minnesota’s legislative mandate for a comprehensive analysis of these safety systems. By providing a data-driven assessment of safety benefits, operational impacts, and implementation pathways, the report will help public agencies, railroads, and technology vendors align on good practice. The report is organized as follows: (Chapter 2) introduces the types of wayside detectors currently in service in Minnesota; (Chapter 3) presents additional detector technologies implemented in North America and internationally to determine good practice and innovation trends; (Chapter 4) assesses accuracy, reliability, detection rates, siting considerations, data management, and maintenance requirements for wayside detectors; (Chapter 5) discusses safety benefits through statistical analysis of national and Minnesota-specific incident data; (Chapter 6) details capital, operating, and maintenance cost ranges and benefits of wayside detectors, discusses industry impacts of wayside detector installation scenarios, and outlines federal and state funding or financing options; and (Chapter 7) examines federal preemption and Federal Railroad Administration (FRA) guidance on statewide wayside detector system deployment.]]></description>
      <pubDate>Thu, 16 Apr 2026 16:54:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2689420</guid>
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    <item>
      <title>Evaluation of MDOT’s Methodologies for both Quantifying Pavement Distress and Modeling Pavement Performance for Life-Cycle Cost and Remaining Service Life Estimation Purposes</title>
      <link>https://trid.trb.org/View/2658082</link>
      <description><![CDATA[Michigan Department of Transportation (MDOT) has been using the Distress Index (DI) since the inception of its pavement management system (PMS) in the early 1990s. DI was developed to help MDOT engineers decide, allocate budgets, and prioritize future maintenance or reconstruction activities. However, the raw data requirements for the DI are complicated (and somewhat unique compared to the rest of the nation). Over the last three decades, the pavement industry has seen many advances in data collection, distress identification, performance modeling, and other processes fundamental to PMSs. Consequently, there was a need to revisit the DI used by MDOT and revise it according to modern pavement data collection standards and calculation methodology. This study aimed to develop an enhanced pavement condition score and associated PMS data collection methodology for use by MDOT. To meet this objective, 2081 flexible and 741 rigid pavement sections were selected from MDOT’s performance database. Then, five different condition indices used by other state agencies were computed using the MDOT's PMS data and compared against MDOT’s Distress Index (DI). Maintenance records were used to compare the magnitudes of different indices right before maintenance activities were performed. The new pavement condition parameter was selected to follow the current state of the practice in its rating scale and consider major distresses. Furthermore, various performance models were used to predict the new condition index and International Roughness Index (IRI) data, and pavement fix lives were estimated for both asphalt and rigid pavements. Building on these advancements, network-level modeling methods were developed to project the future condition of MDOT’s pavement network in terms of IRI, cracking, rutting, and faulting. Using Markovian Transition Probability Matrices (TPMs) and multinomial logistic regression, the study established a robust analytical framework to forecast pavement performance under various maintenance and rehabilitation scenarios. These models enable MDOT to evaluate the long-term effects of different funding strategies, set realistic performance targets in alignment with federal requirements, and support data-driven decision-making for statewide pavement management.]]></description>
      <pubDate>Mon, 02 Feb 2026 14:13:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658082</guid>
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    <item>
      <title>Ohio Department of Transportation’s Intersection Inventory</title>
      <link>https://trid.trb.org/View/2644530</link>
      <description><![CDATA[The Federal Highway Administration (FHWA) originally published the Model Inventory of Roadway Elements – MIRE 1.0 guidance on a set of recommended safety data elements for State departments of transportation (DOTs) in 2010. These elements could support a variety of network and site-specific safety analyses, as well as support the methods introduced in the First Edition of the American Association of State Highway and Transportation Officials’ Highway Safety Manual. In 2017, FHWA updated and expanded the MIRE guidance and introduced the concept of MIRE Fundamental Data Elements (FDEs). These MIRE FDEs include data elements for roadway segments, intersections, and interchange/ramps on non-local paved roads, as well as smaller subsets for local paved and unpaved roads. This case study presents an effort by the Ohio Department of Transportation (ODOT) to (1) develop a digital inventory of intersection locations on all public roads in the State, and (2) collect MIRE FDEs at those intersections to support statewide safety screening and analysis. The intersection inventory will serve several important purposes for ODOT, including meeting Federal data requirements and substantially improving data analysis capabilities. ODOT’s data integration with existing and future data analysis systems and work with FHWA’s Applications of Enterprise Geographic Information Systems for Transportation (AEGIST) pooled fund study will expand intersection safety analysis capabilities throughout the agency.]]></description>
      <pubDate>Wed, 21 Jan 2026 10:46:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2644530</guid>
    </item>
    <item>
      <title>Advancing a Statewide Model for Multimodal Transportation Planning and Asset Management Integration in Rural and Small Urban Contexts</title>
      <link>https://trid.trb.org/View/2606412</link>
      <description><![CDATA[This research addresses the critical need for integrating transportation asset management (TAM) with transportation planning practices in rural and small urban contexts. Building on federal guidance from the Moving Ahead for Progress in the 21st Century Act (MAP-21) and subsequent legislation, the project will develop a statewide framework that strengthens the relationship between asset management and multimodal transportation planning across state, regional, and local agencies. The research focuses on three foundational components: meaningful stakeholder collaboration, high-quality integrated asset data, and aligned performance measurement processes. Using West Virginia as a pilot context, the study will evaluate current integration practices, assess multimodal asset data gaps, develop a prototype infrastructure database, and create a practitioner-focused toolkit for co-prioritization and performance-based decision-making. The methodology encompasses assessment of current practices, evaluation of data opportunities, database development, framework creation, and pilot implementation with selected agencies to test real-world applications and gather user feedback for refinement.]]></description>
      <pubDate>Thu, 02 Oct 2025 15:27:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606412</guid>
    </item>
    <item>
      <title>Connecticut Integrated Transit Mobility Project (CT-ITMP): Data Management Plan</title>
      <link>https://trid.trb.org/View/2590857</link>
      <description><![CDATA[The Connecticut Integrated Transit Mobility Project (CT-ITMP) aims to develop a comprehensive strategy for establishing an interconnected, multimodal statewide public transit system. This initiative will enable customers to conveniently use their own contactless credit, debit, or prepaid card or a payment-enabled device to pay for fares. The Connecticut Department of Transportation (CTDOT) is proposing the CT-ITMP to:  (1) Develop a roadmap for unifying all transit information in the state under a mobile app solution including upgrading all of the state’s transit systems with the hardware and software needed to provide reliable real-time information. (2) Create a phased implementation plan for an integrated, open fare payment system with a focus on financial inclusion of the unbanked and underbanked. (3) Establish an efficient and user-friendly system for implementing statewide fare discount programs and digital eligibility verification. The CT-ITMP initiative aims to digitally connect the entire public transportation system in Connecticut, resulting in an enhanced customer experience and fostering access to transportation.  To boost ridership, improve customer satisfaction, and utilize transit as a means to promote financial inclusion, CTDOT will study the prerequisites for implementing open payment options. This encompasses contactless payment methods such as bank cards, credit cards, and mobile wallets (e.g., Apple Pay) statewide. This exploration will be conducted as part of the initial phase of the SMART grant, undertaken in collaboration with the California Integrated Travel Project (Cal-ITP). A primary focus of this research will be to comprehend the needs of underbanked and unbanked customers. CTDOT will examine the feasibility of digitally verifying discounted fares on bank cards, drawing inspiration from the Cal-ITP benefits tool—a novel program dedicated to simplifying and cost-effectively enhancing travel for all.  The project is set to go a pilot/proof of concept demonstration lasting six (6) months within designated service areas involving the key stakeholders. This trial aims to evaluate the effectiveness and make necessary adjustments to the overarching plan for implementing an integrated payment system across the State of Connecticut.]]></description>
      <pubDate>Mon, 08 Sep 2025 14:53:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2590857</guid>
    </item>
    <item>
      <title>Monitoring and Speciation of Particulate Matter Under 2.5 Microns (PM2.5) Composition across Texas Counties</title>
      <link>https://trid.trb.org/View/2593191</link>
      <description><![CDATA[Texas needs a detailed understanding of statewide particulate matter under 2.5 microns (PM2.5) sources, as current regulatory monitoring lacks the granularity for source apportionment. Since speciated PM2.5 data is limited, the research team will collect and analyze samples from multiple regions nearing or exceeding the 9.0 µg/m3 threshold set by the Environmental Protection Agency (EPA). The research team will conduct source apportionment analysis and highlight the prominent sources of PM2.5 emissions by region. This will support future research and regulatory efforts, such as developing and implementation appropriate emission reduction strategies. The research team will collaborate with state and local governments, academia and other stakeholders, to acquire any existing data and ensure local regulations and best practices are met. The research team will collaborate with the Texas Department of Transportation (TxDOT) project 0-7257, "The Effects of Road Types and Construction Activities on Particulate Matter and Development of Best Practices for PM2.5 Reduction" by sharing data, resources, and coordinating efforts to enhance data collection and analysis.]]></description>
      <pubDate>Tue, 26 Aug 2025 12:42:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2593191</guid>
    </item>
    <item>
      <title>Extending the Wisconsin Work Zone Data Exchange (WZDx) to Local Roads Using Smart Work Zone ITS Devices</title>
      <link>https://trid.trb.org/View/2569672</link>
      <description><![CDATA[Improving overall work zone safety will require a comprehensive approach, improving access to work zone data that incorporates real-time, field verified information using smart work zone technology. Recognizing this need, the USDOT launched the Work Zone Data Exchange (WZDx) specification and in 2021 awarded $2.4M in demonstration grants to thirteen (13) states to develop public facing, WZDx compliant data feeds. The Wisconsin Department of Transportation (WisDOT), as one of the thirteen demonstration grant recipients, has developed a new WZDx feed that conveys up-to-date, detailed information for all highway lane and road closures statewide, representing approximately 12,000 scheduled work zone events annually. However, the success of the Wisconsin WZDx effort is tempered by the fact that the data feed does not include work zones on the local road network. This project proposed the use of connected work zone devices to incorporate real-time local road closure details into the Wisconsin WZDx and the Wisconsin 511 Traveler Information Systems.]]></description>
      <pubDate>Mon, 30 Jun 2025 09:17:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569672</guid>
    </item>
    <item>
      <title>Synthesis of VDOT Historic Bridge Survey, Review, and Management Information</title>
      <link>https://trid.trb.org/View/2561782</link>
      <description><![CDATA[Since the 1970s, the Virginia Department of Transportation (VDOT), through the Virginia Transportation Research Council (VTRC) has conducted studies to manage its historically significant bridges as well as developing (and updating periodically) a statewide historic bridge management plan and conducting studies on rehabilitating and moving historic truss bridges, truss bridge eye bar deterioration, and feasibility of alternative uses.  Further, specific projects relating to individual bridges are covered by separate guidance documents, cultural resource reviews, Memoranda of Agreement (MOA), or by Programmatic Agreement (PA) documents.  These surveys, projects, and agreements are documented by various VTRC survey files, reports, and memos, as well as documents filed in VDOT district Environmental offices and VDOT Environmental Division files in VDOT's Central Office.  However, there is no one document containing this information.

In the late 2010s, VDOT’s Central Office cultural resource staff identified a need for a synthesis document that would consolidate information regarding historic bridges.  The lack of such a synthesis resulted in gaps in the cultural resource records regarding these bridges, which is problematic for newer VDOT personnel who periodically must put together information on the previous projects that have involved these bridges.  Phase I of this synthesis, collecting information from the initial and early VDOT/VTRC historic bridge projects (covering 1972-1993), was completed in 2022.  This Phase 2 will continue the collection of this information from 1993 to the present, such that this report will be a final synthesis report covering 1972 to the present.  This report will contain data on the cultural resource surveys, reviews, studies, management plans, published reports and agreements, including MOAs and PAs.  Because a VDOT-specific synthesis like this has not been published before, this report could be a model for future updates based on additional historic bridge surveys, reviews, and management projects. 
]]></description>
      <pubDate>Thu, 05 Jun 2025 10:34:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2561782</guid>
    </item>
    <item>
      <title>Tapping into Autonomous Trucking Data: An Intelligent Routine Maintenance Framework for Texas</title>
      <link>https://trid.trb.org/View/2434218</link>
      <description><![CDATA[Texas has become a major hub for autonomous trucking activity, with companies operating routes daily and continuing to expand operations onto new roadways. Equipped with high-definition cameras and sensor suites, autonomous trucks present a new data opportunity for the Texas Department of Transportation (TxDOT) to improve its routine maintenance operations. Partnering with two autonomous trucking companies and three TxDOT Districts, the University of Texas at Austin Center for Transportation Research (CTR) developed an intelligent routine maintenance framework (IRMF) and prototype. The IRMF establishes workflows for detecting, assigning, and resolving routine maintenance events. Based on public- and private-stakeholder input, the research team prioritized six routine maintenance events for inclusion in the prototype: potholes, striping and pavement markers, guardrails and cable barriers, debris, and work zones. The prototype leveraged TxDOT’s Nighttime Inspection Suite to enable participating Districts to access 411 autonomous trucking events and compare with traditional TxDOT inspections. Additionally, the research team created a dashboard for mapping and visualizing the routine maintenance events by type, roadway, and District. Finally, the research team formulated a growth and sustainability plan that includes complementary artificial intelligence (AI) solutions, a cost-benefit analysis, and procurement pathways. Overall, the project establishes a proof of concept upon which TxDOT can build, automate, and ultimately scale statewide. By integrating data from autonomous trucks and other third-party data sources, TxDOT can improve the coverage, resolution, and timeliness of its routine maintenance data; reduce response times; and increase the safety of its roadways for automated and traditional vehicles alike.]]></description>
      <pubDate>Wed, 09 Oct 2024 16:01:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2434218</guid>
    </item>
    <item>
      <title>Fast Detection and Prediction of Slippery Roadway Conditions for Enhanced Safety</title>
      <link>https://trid.trb.org/View/2291287</link>
      <description><![CDATA[Black ice, a nearly invisible hazard, contributes to over 10% of weather-related crashes in the U.S., causing 200,000 annual accidents, 700 fatalities, and 65,000 injuries. Traditional methods for detecting black ice involve fixed sensors and signs, but new vehicle-based technology offers cost-effective real-time data. However, obtaining comprehensive road condition data during inclement weather remains expensive and risky. State agencies must collect pavement surface data for asset management, yet the relationships between surface characteristics, weather conditions, and ice formation are not adequately understood. Research is needed to predict slippery conditions using existing data. Prediction of slippery conditions can be potentially more critical than detecting slippery conditions due to changing weather patterns and weather extremes.
This project aims to develop predictive models for slippery road conditions by collecting data with Mobile Advanced Road Weather Information Sensors (MARWIS) sensors and Pave3D 8K on roadway segments before, during, and after inclement weather. The collected data will be used to create predictive models for different weather scenarios. The primary goal is to develop predictive models that can anticipate slippery road conditions under different weather scenarios. These prediction models can then be applied to identify potentially slippery areas across Oklahoma, using the annually collected PMS datasets by ODOT. The primary goal of this project is to enhance highway safety.
The aforementioned goals will be achieved through four tasks: Task 1: Data Collection: Use MARWIS technology to measure road conditions, including temperature, humidity, and road state. This data will be collected on selected testing sites based on weather forecasts and in collaboration with ODOT; Task 2: Surface Characteristics: Assess field friction values and collect pavement surface characteristics data using the Grip Tester and Pave3D 8K technology to understand their impact on road slipperiness; Task 3: Slippery Road Prediction Models: Leverage data from MARWIS and surface characteristics and create predictive models using statistical and machine learning methods for forecasting road conditions during rainy or icy days; Task 4: Implementation: Incorporate statewide surface characteristics data from ODOT into the predictive models, presenting results in a Geographic Information System (GIS) database for better situational awareness and road maintenance support.
]]></description>
      <pubDate>Wed, 15 Nov 2023 21:40:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2291287</guid>
    </item>
    <item>
      <title>Summary of ITS Best Management Practices and Technologies for the State of Ohio</title>
      <link>https://trid.trb.org/View/2149146</link>
      <description><![CDATA[In conducting a "best practices and technologies" study for the deployment of ITS technologies in Ohio, the Ohio DOT determined that the study should focus on the macro corridor system in the state. This paper focuses on a summary report of a major research report submitted to the Ohio DOT in mid-2001 that explored the causes of delay on these macro corridor highways and suggested those management practices and ITS technologies that would be most effective for Ohio's ITS program. In terms of congestion on highways in the three largest metropolitan areas in Ohio, the percentage of congestion caused by incidents was approximately 55 percent in the most recent Texas Transportation Institute rating. The ITS program recommended for further deployment to the Ohio DOT included (1) non-technical freeway operations improvements, (2) synergistic collection and analysis of traffic data, (3) multi-agency traffic management with DOTs at the state and local level, police and fire, (4) incident detection, (5) video surveillance, (6) traffic control during incidents, and (7) traveler information dissemination. A detailed assessment of various technologies in each of these seven functional areas was made with an array of state-of-the-practice technologies, but no one specific technology was recommended for statewide application. In this way the ITS partnerships that are formed by the various ODOT districts would have information to guide them in their choices of technologies. In terms of management practices, it was noted that Ohio's highway and multimodal transportation program is subject to the oversight and policy guidance of a Transportation Review and Advisory Committee (TRAC). It was recommended that ITS projects be eliminated from the TRAC review process, or that ODOT develop criteria for ranking and selecting ITS projects based on their value in improving operations on Ohio's macro highway system.]]></description>
      <pubDate>Wed, 25 Oct 2023 16:58:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2149146</guid>
    </item>
    <item>
      <title>Evaluation of the Monroe Expressway Wrong Way Vehicle Detection Program</title>
      <link>https://trid.trb.org/View/2218960</link>
      <description><![CDATA[In North Carolina, wrong way driving (WWD) crashes are one of the most severe traffic crashes that often result in a fatality or serious injury since they involve head-on or opposite direction sideswipe crashes at high speeds. To minimize the occurrence of WWD crashes, the North Carolina Turnpike Authority (NCTA), which is a unit of the North Carolina Department of Transportation (NCDOT), deployed a wrong way vehicle detection system along the Monroe Expressway in 2018. The system can automatically detect wrong way vehicles at mainline stations and inform traffic management center operators. This project evaluated the effectiveness of wrong-way traffic control devices installed at the ramp and mainline locations along the Monroe Expressway. A comprehensive literature search was conducted to summarize the state-of-the-practice of WWD crash modeling, detection, and prevention. Real-world traffic data including traffic volume, traffic control devices present, geometry and configuration of interchanges were employed for identifying the relationship between the frequencies of wrong way incidents and facility characteristics. During the study period of approximately 1.5 years of data collection, there were 13 actual WWD events, of which five wrong way movements originated from the roundabout parclo interchanges on the Monroe Expressway. In addition, this project collected statewide data on partial cloverleaf interchanges to assess the risk for wrong way movements. It was found that the partial cloverleaf interchange configuration was associated with the highest number of WWD activities, and factors that affect the risk of WWD mainly include: entrance and exit ramp traffic volume and control type, divided or undivided exit ramp, median cut turn access, left-turn perpendicular turning distance, skew angle, and distance between ramp terminals.]]></description>
      <pubDate>Wed, 02 Aug 2023 09:00:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2218960</guid>
    </item>
    <item>
      <title>Digitizing Bicycle and Pedestrian Treatments for Promoting Active Transportation Safety 





</title>
      <link>https://trid.trb.org/View/2195112</link>
      <description><![CDATA[Users of active transportation are facing an increasing disparity in traffic-related incidents. However, the implementation of data-driven safety and planning tools is hindered by the lack of high-quality inventories for bicycle and pedestrian facilities and treatments.

There are data management and organizational challenges to maintaining statewide inventories for active transportation treatments. High-quality, contiguous active transportation networks cross many jurisdictional boundaries. Data federated from local authorities are highly variable and often incomplete. Auditing and mapping pedestrian and bicycle treatments are crucial tasks within a geographic information systems framework. There are also emerging geographic data sources (e.g., crowdsourced and remotely sensed data), which can introduce new challenges and opportunities. 

Research is needed for developing a spatial framework for working across jurisdictional boundaries and data sources to digitize, maintain, and share active transportation-related assets while minimizing costs and risks associated with poorly governed data.

OBJECTIVE: The objective of this research is to develop a guide that will assist state departments of transportation (DOTs) and local agencies in digitizing bike and pedestrian treatments and provide examples of how organizations have used digitized data to better fulfill their safety goals. 

At a minimum the study shall (1) examine existing best practices; (2) explore the potential and benefits of using emerging geographic data sources; and (3) develop a standardized framework for data collection, maintenance, and sharing of the active transportation facilities and treatment inventory data.]]></description>
      <pubDate>Mon, 12 Jun 2023 19:56:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2195112</guid>
    </item>
    <item>
      <title>	Developing Data Sources and Standards for Supporting Arterial TSM&amp;O Implementation of the Statewide Arterial Management Program (STAMP)</title>
      <link>https://trid.trb.org/View/2108094</link>
      <description><![CDATA[The purpose of this project is the following: 
(1)  Evaluate existing data management platform procurements, activities, specifications, and usages at each district and nationally.  
(2) Determine best practices and develop recommendations for a platform for data collection and utilization to apply to and provide value to all districts. 
(3) Assist districts in evaluating the appropriate strategy that they could consider implementing. 
(4) Help FDOT plan accordingly based on priorities and available resources. 
(5) Help achieve uniformity in data collection and utilization among the Districts, which will help in implementation and efficiency in future projects.]]></description>
      <pubDate>Thu, 02 Feb 2023 08:18:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2108094</guid>
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