<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
    </image>
    <item>
      <title>Developing an Automated Framework for Aggregating Right-of-Way Data through GIS and Computer Vision Methods</title>
      <link>https://trid.trb.org/View/2714448</link>
      <description><![CDATA[Ohio Revised Code 125.16 requires current and accurate records of tangible personal property and real property be maintained. The Ohio Department of Transportation (ODOT) can obtain records of state-owned right-of-way (ROW) by specific locations and/or project, however there is no simple repository or mechanism to obtain information in a wholistic, statewide manner. ODOT's Office of Real Estate has an online Arcis application, OhROW, that lets people click on a map and get direct access to ROW plans. However, OhROW does not have any data aggregation capabilities, data is not queryable, and not all areas are available in the application. ODOT's Office of Data Governance is working on an initiative to obtain ROW line data from new 3D plan sets. This process is tremendously slow and dependent on the availability of 3D plan sets that include some kind of ROW lines. It is estimated that it could take up to 50 years to cover all of ODOT's road network using this process. Other state DOTS, such as Texas and Nevada, have attempted to address this issue by manually reviewing every plan set of their road network and manually inputting the legal descriptions to make polygons of their ROW. This process is very labor intensive, time consuming, and is expected to take several years to complete. An innovative approach to obtain ROW data, in granular details (such as acreage, type, access parcels, nature of control, etc.), and create maps is needed. OBJECTIVE: Develop an innovative approach to identify ODOT owned property, propose methods for storing datasets, and utilize the data to pilot the approach by generating property maps of a specific county, city, township or State Route. The approach should be repeatable, reliable, and streamlined and findings should include recommendations for statewide implementation of the innovative approach.]]></description>
      <pubDate>Tue, 16 Jun 2026 15:19:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714448</guid>
    </item>
    <item>
      <title>Evaluate the Safety Effects of Multiple Vehicle Synchronized Warning Lights in ODOT Work Zones
</title>
      <link>https://trid.trb.org/View/2701274</link>
      <description><![CDATA[In 2024, 56 Ohio Department of Transportation (ODOT) crews were struck while working on the highway system. As of March 2025, 43 ODOT crews have been struck. With safety being of the upmost importance to ODOT's Executive Leadership, protecting road crews and individuals working on ODOT jobsites remains a common theme when investigating new technologies and techniques to help reduce and minimize these accidents. Currently ODOT has a variety of light-emitting diode (LED) warning light systems in use on its fleet of maintenance vehicles. When these vehicles are concentrated in a work zone, there has been concern that these lights, while flashing independently, can lead to confusion among the motoring public as they enter the work zone. Added to this, ODOT operates work zones during all times of the day and in all weather conditions further exacerbates the situation.  This can result in unsafe driving practices and increased accidents. 

There is a growing opinion among transportation professionals that synchronizing warning lights and/or customizing patterns to evolve situationally could alleviate, if not resolve, these dangerous work zone crashes. ODOT is looking to evaluate the effectiveness of a system that synchronizes the warning systems of all vehicles present in a work zone.   A system that could increase driver awareness and reduce safety related incidents would be useful not only to ODOT but to local public agencies, emergency responders, and other state departments of transportation (DOTs).

OBJECTIVES: The goal of this research is to identify the effectiveness of using synchronized warning light systems versus non-synchronized warning light systems on work zone vehicles.
             ]]></description>
      <pubDate>Tue, 12 May 2026 10:43:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701274</guid>
    </item>
    <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>Improving Large Litter Collection from Paved Surfaces
</title>
      <link>https://trid.trb.org/View/2646925</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) has over 730 miles of concrete barrier wall with the majority of that being median barrier. The paved shoulders that require litter and sweeping process is over 1,300 miles. ODOT continues to build Ohio's highway system, closing in unpaved medians and adding Smart Lanes which allows for periodic use of paved shoulders as traffic lanes. These projects add more miles of paved shoulder that will require more frequent cleaning and debris removal.

When street sweepers are run along barrier walls to clean shoulders, a road crew typically runs in front of them to gather the large debris (e.g., tire treads, lumber, car parts, etc.). Normally it takes at least 2-3 workers in a truck picking up this large litter, then a street sweeper follows. The workers in the lead truck have to constantly stop, get out of the vehicle, pick up the debris, place it in the truck bed, get back into the truck, and then pull forward to the next large piece of debris. All of this is followed by a crash attenuator truck for safety purposes. Altogether, this process utilizes 4-5 workers and 3 pieces of equipment starting and stopping on busy freeways. When not doing a full street sweeping operation, there is still the crew of 2 to 3 staff in a pickup truck that have to constantly stop, get out, pick up, get back in and repeat as they move along the road. Variations in this process may occur across the state. Previous studies have looked at litter collection but have typically focused on all forms of litter and collecting it from roadsides, under guardrails, throughout grass infields, etc. These studies did not include detailed time studies in order to compare various processes and equipment.  

OBJECTIVE: The goal of this research is to determine the best method(s) for providing safe, efficient and cost-effective ways to pick up/collect large litter and debris from paved shoulders and under guardrail.
                         ]]></description>
      <pubDate>Wed, 31 Dec 2025 13:44:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646925</guid>
    </item>
    <item>
      <title>Pavement Condition Rating Method and Use for Local Agencies 
</title>
      <link>https://trid.trb.org/View/2618201</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) collects pavement condition ratings (PCR) on the state network annually and a subset of the local network that is federal aid eligible on a biennial basis. This data is made available to local public agencies (LPAs) through the TIMS system. Many LPAs also collect their own set of pavement condition ratings on all pavements within their jurisdiction to identify roads for resurfacing, repair, and other planning purposes. The data sets collected by LPAs may differ significantly from ODOT's PCR and in most cases the detailed level of distress information collected in ODOT PCR may not be necessary for their purposes. In addition, the collection methods, schedules, and data types differ from locality to locality statewide.

Metropolitan Planning Organizations (MPO's) use ODOT's PCR ratings to help compare the condition of various areas and for grant applications. While ODOT PCR may be helpful to MPOs, the feedback ODOT has received from LPAs who are responsible for maintaining the local roads is that ODOT's PCR data may not be helpful in many cases. In addition, LPAs would prefer to have data on the whole local network as opposed to a subset. Since ODOT collects and reports pavement data on federal aid eligible roads, identifying a pavement rating methodology that would be useful for all parties (LPAs and MPOs) is desired.
 
The goal of this research is to recommend pavement rating methods that would be useful to cities, counties, townships, and MPOs. Findings from this research will help ODOT to focus current efforts to collect local pavement condition ratings to be useful to the agencies responsible for the routes the data represents. Identifying and implementing a pavement rating methodology that would be useful for all parties (LPAs and MPOs) would help reduce duplication of effort and enhance data integrity and utilization. A more unified approach to pavement data collection can ultimately improve pavement management for local agencies.
                 ]]></description>
      <pubDate>Tue, 04 Nov 2025 15:32:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2618201</guid>
    </item>
    <item>
      <title>Model as a Legal Deliverable: Exploring the Technological, Implementation, and Legislative Pathways for ODOT
</title>
      <link>https://trid.trb.org/View/2617997</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) currently has no process in place to allow for the delivery of Building Information Modelling (BIM)  models as part of the project contract, nor does ODOT have a full grasp of all the regulations or codes that exist in Ohio that may prevent or support this process. While ODOT develops 2D/3D models for design, that data is used to create traditional (2D) plan sheets and supplemented with extensive documentation before being provided as reference information on a construction contract. The contractor then uses the design information from the plan sheets which are the contract document and will generate a new 2D/3D model to be used to understand construction needs and for their due diligence, usually at a cost to ODOT. With new technology and the implementation of BIM for Infrastructure strategies, there is an opportunity to streamline processes, enhance collaboration, and improve design/construction accuracy through the development and delivery of model-based deliverables. Other states have already begun adopting BIM models as legal deliverables and have demonstrated the benefits of native model-based and advanced digital delivery processes.

There is a pressing need to modernize ODOT's approach to model deliverables to keep pace with technological advancements and industry standard practices. Research is needed to provide a comprehensive analysis of benefits and challenges associated with adopting a model-based approach.  The goal of this study is to determine the feasibility and implications of adopting a model as a legal deliverable approach for transportation projects in Ohio. 
                       ]]></description>
      <pubDate>Tue, 04 Nov 2025 14:22:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617997</guid>
    </item>
    <item>
      <title>Economic Development Impacts of ODOT Funding on Public Roadways</title>
      <link>https://trid.trb.org/View/2603395</link>
      <description><![CDATA[While the Ohio Department of Transportation (ODOT) has several models that quantify the economic benefits and impacts of its investments, the Economic Development Impact Tool (EDIT) is the unique product of national research in market access, development capacity,and historical economic performance. A review of national literature and existing ODOT models provides the foundation for an interactive evidence-based process to assign new business attraction potential to ODOT projects and project areas. Findings include an overview of how the national body of literature applies to development settings faced by ODOT, observations of where development capacity, labor market access and freight market access are most sensitive to ODOT system performance,and empirical findings from a Machine-Learning model of economic responses to ODOT’s investments over 10-20 years. Future research areas identified include expansion of the EDIT resources to address freight and transit access, international gateways and controlling for competing development sites within Ohio.]]></description>
      <pubDate>Tue, 30 Sep 2025 10:23:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2603395</guid>
    </item>
    <item>
      <title>Recruiting and Retaining Staff</title>
      <link>https://trid.trb.org/View/2601523</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) has been challenged to address a shortage of staff due to staff turnover, less hiring of full-time staff and increasing technological capabilities, all of which have been exacerbated by the retirement of the baby-boomer generation from the workforce. It is imperative that ODOT explore and implement innovative practices to recruit and retain a highly qualified, diverse workforce by developing and recruiting for careers that balance economic, environmental, and social factors while effectively meeting today's engineering challenges. This research aims to tackle the pressing challenges of recruiting and retaining staff within ODOT using a multifaceted and innovative approach. The baby-boomer generation is reaching the age of retirement, leaving many open positions to be filled. The goal of this research is to identify innovative practices geared towards future generations to recruit and retain employees.]]></description>
      <pubDate>Tue, 30 Sep 2025 09:32:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2601523</guid>
    </item>
    <item>
      <title>Cost Effective Alternatives for Mitigating Debris and Environmental Impacts Around Bridge Piers</title>
      <link>https://trid.trb.org/View/2595173</link>
      <description><![CDATA[This research study addressed three key problems: 1) identifying safer, timely, and cost-effective solutions for removing accumulated debris from bridge piers, 2) designing and implementing countermeasures to prevent debris accumulation, and 3) finding technological solutions to enhance bridge inspection, scour detection, and mapping of river cross sections. The project evaluated various equipment solutions for debris removal, ultimately developing and testing a custom knuckleboom crane with grapple and saw attachments. The knuckleboom crane improved worker safety, minimized lane closures, and allowed for streamlined environmental permitting. On small projects completed by ODOT County forces, labor was reduced by 43%. Large or difficult projects that have typically been sold to contractors can now be completed by ODOT forces with cost reductions ~80-90%. Numerous methods and materials were evaluated to develop strategies to mitigate debris accumulations and counteract scour. Chevron vane structures were designed and implemented at SR 122 over the Great Miami River in Butler County to better align river flow and direct debris away from piers. Debris snagging on piers has been greatly reduced, but not fully eliminated. Debris removal in conjunction with the mitigation measures has been highly effective. Additionally, a cross-vane structure was implemented at SR 52 over Ray’s Run in Clermont County. The vane was constructed to address scour of the abutments. The project remedied systemic degradation of the streambed and halted scour. The research also explored remote, non-contact methods to aid in subsurface investigations for bridge inspection primarily focused on sites with water depths >5-feet. Demonstrations of uncrewed surface water vehicles and single and multibeam sonar were coordinated and used to evaluate hardware, sensors, software, and outputs. These technologies provided valuable data for evaluating scour and establishing repeatable cross sections for change detection in subsequent surveys. To facilitate technology transfer, multimedia educational materials were developed.]]></description>
      <pubDate>Fri, 26 Sep 2025 13:40:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2595173</guid>
    </item>
    <item>
      <title>Determining the Effectiveness of Commercial Vehicle Safety Alerts</title>
      <link>https://trid.trb.org/View/2589125</link>
      <description><![CDATA[The Ohio Department of Transportation has partnered with Drivewyze to improve safety and mobility on Ohio’s highways, focusing on commercial vehicle safety alerts (CVSAs). Through this partnership, Drivewyze provides commercial motor vehicle (CMV) drivers with real-time alerts via in-cab electronic logging devices (ELDs). The alerts are intended to warn drivers about urgent road conditions, providing them with an opportunity to react proactively to incidents. The primary goal of this research project is to assess the effectiveness of Drivewyze alerts,   specifically congestion  and  sudden  slow-down  alerts,  in  enhancing  safety  and  mobility  on    Ohio’s highways. A data-driven analysis was used to quantify the mobility and safety effectiveness of Drivewyze CVSAs. The  research  team  also  surveyed  commercial  vehicle  drivers,  state  transportation  agencies,  and  trucking  companies  to  obtain  feedback  and  opinions  on  the  effectiveness  of  CVSA  systems  and  identify  available  alternative CVSA systems. Findings from the effectiveness analysis suggest that the use of the Drivewyze system may yield positive returns on safety and mobility. Furthermore, survey results indicate positive feedback about CVSAs  and  show  that Drivewyze  has  the highest  penetration  rate  compared  to  similar  technologies such  as  Global  Positioning  Systems  (Garmin,  Rand  McNally,  etc.),  Samsara,  PrePass,  Motive,Geotab,  Trucker  Path, etc.  This report  also  provides  recommendations  for  enhancing  the  effectiveness  of  CVSA  systems based  on  survey data and data-driven analyses.]]></description>
      <pubDate>Thu, 21 Aug 2025 16:38:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589125</guid>
    </item>
    <item>
      <title>ODOT’s Snow and Ice Performance Evaluation Tools - A Student Transportation Advancement Research (STAR) Project</title>
      <link>https://trid.trb.org/View/2589127</link>
      <description><![CDATA[Severe winter weather poses a significant threat to road users, primarily due to slippery road surfaces, which considerably increase the risk of crashes and injuries. Additionally, such conditions can disrupt traffic flow on highways, causing speed reductions, decreased highway capacity, or even complete traffic lockdowns. Most Departments of Transportation (DOTs) in snowy regions rely on Road Weather Information Systems (RWIS) as their primary source of weather data. However, RWIS has several limitations including downtime, erroneous data due to system or equipment failure, and the high cost of installation and operation, resulting in a limited number  of  stations  across  states.  This  necessitates  the  need  for  alternative  weather  data  sources  to complement  RWIS. The primary  goal  of  this  project  is  to  identify  alternative  sources of weather  data  to supplement and  complement the Ohio  Department  of  Transportation  (ODOT) RWIS for winter  maintenance operations. Several sources have been identified from the literature that can provide alternative weather data. Based on the accessibility and reliability of these data sources, four potential sources are proposed that can be used  by ODOT: Automated  Surface  Observing  System (ASOS),  Next  Generation  Weather  Radar  (NEXRAD), Meteorological  Assimilation  Data  Ingest  System  (MADIS),  and  Multi-Radar/Multi-Sensor  System  (MRMS). The research team developed and implemented data scraping frameworks that can be integrated into the ODOT snow and ice performance and evaluation tool.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:08:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589127</guid>
    </item>
    <item>
      <title>Verification of ODOT Rock Channel Design Procedures</title>
      <link>https://trid.trb.org/View/2589126</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) employs rock channel protection (RCP), also known as riprap, to manage energy dissipation and prevent scouring at culvert and storm drain outlets. The design for RCP at outlets follows guidelines outlined in Figure 1002-4 of ODOT's Location and Design Manual Volume  2,  incorporating  specifications  from  ODOT  Construction  and  Material  Specifications  601.  RCP  types (Type A, Type B, and Type C) are determined based on size, with specifics such as type, length, and depth guided by pipe diameter and outlet velocity as shown in Figure 1002-4. This design method, established by ODOT in July 1968, is still used to calculate RCP dimensions. However, the origins of this methodology and the basis for Figure 1002-4 are unclear, prompting a review of current procedures or adoption of a new methodology to ensure proper RCP sizing at conduit outlets due to ODOT's relatively less  conservative  approach.  The  research  team  conducted  scaled  hydraulic  modeling  and  identified hydraulic conditions that impact RCP lengths, including factors not considered in previous studies.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:08:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589126</guid>
    </item>
    <item>
      <title>District Highway Management Research On-Call (ROC)  FY26-28</title>
      <link>https://trid.trb.org/View/2582820</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) is charged with the management and maintenance of Ohio's vast transportation system.  ODOT strives to execute this charge in the most effective and efficient manner possible.  At times, ODOT encounters situations where low-cost, short-term, focused research tasks are needed to address an urgent issue.  While important and potentially impactful, these research tasks do not warrant the level of a full-scale research project.  Due to the time-sensitive nature of these tasks, it is possible that some of these tasks go unmet because the standard contracting process requires more time than available.  To address this issue, ODOT developed the Research-On-Call (ROC) program.  The ROC is designed to provide direct, quick access to researchers in specific areas of expertise to conduct short-term, focused, urgent research tasks.  This ROC will focus on tasks to support District Offices with system management and maintenance improvements.  
             ]]></description>
      <pubDate>Mon, 04 Aug 2025 13:34:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2582820</guid>
    </item>
    <item>
      <title>A critical assessment of the role of mapping in Ohio Safe Routes to School travel plans</title>
      <link>https://trid.trb.org/View/2559700</link>
      <description><![CDATA[Safe Routes to School is a billion-dollar U.S. government program that funds infrastructure to make walking and biking to school safer. The Ohio Department of Transportation (ODOT) selects projects to fund using GIS. These maps show where students live in relationship to the school and where pedestrian and bicycle crashes occurred nearby in the past five years. In this paper, the author takes a closer look at what data is used -- and how it is used -- in this analysis and ask if a more detailed, literature-informed GIS analysis could improve the metrics used to select the most impactful neighborhood projects. To answer this question, the author analyzed the application of quantitative criteria to create a school travel plan in Kent (Ohio) City School District as well as the guidelines that explain how these data are used to make funding decisions. She then created new maps that use similar data but change the methodology by following best practices for identifying walkability and traffic issues. The analysis indicates that a more nuanced GIS analysis can identify the most impactful projects better than the maps created by the current mapping approach used in the Ohio SRTS program.]]></description>
      <pubDate>Fri, 18 Jul 2025 15:10:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2559700</guid>
    </item>
    <item>
      <title>Applications of AI to LiDAR Data: Innovating Surveying Practices</title>
      <link>https://trid.trb.org/View/2534021</link>
      <description><![CDATA[Traditional surveying methods, such as leveling and total station surveys, rely heavily on manual processes for data collection and classification. These methods are time-consuming, labor-intensive, and susceptible to human error, which can lead to inaccuracies in the surveyed data. As a result, errors in point classification (e.g., distinguishing between pavement, vegetation, and utilities) can compromise the quality of information used for infrastructure planning and design. Additionally, these outdated techniques often lack the ability to capture comprehensive, high-density spatial data in a single survey, limiting their effectiveness for large-scale or complex projects. Consequently, relying solely on traditional tools can increase project costs, extend timelines, and necessitate costly revisions during later stages of construction and maintenance.

This research explores the potential of Artificial Intelligence (AI), particularly object detection in Light Detection and Ranging (LiDAR) data, to identify infrastructure assets, mainly manholes and drop inlets and classify them with relevant information such as global positioning system (GPS) coordinates, elevation, and type. The study aims to advance surveying practices by leveraging AI-driven insights to enhance accuracy and efficiency.  The primary goal of this research project is to leverage existing LiDAR data to enhance surveying practices through automation and AI integration. The specific objectives include: (1) identify the best AI model to detect selected infrastructure assets from LiDAR Data; (2) train and validate the selected AI models; and (3) develop guidelines for implementing the developed AI to analyze Ohio Department of Transportation (ODOT) LiDAR data and provide outputs in the corresponding formats: .LAS, .BIN, and CSV (COGO Points).
]]></description>
      <pubDate>Thu, 03 Apr 2025 08:55:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2534021</guid>
    </item>
  </channel>
</rss>