<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.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>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <item>
      <title>Alaska Continuously Operating Reference Network (ACORN) GNSS</title>
      <link>https://rip.trb.org/View/2512629</link>
      <description><![CDATA[As Alaska is late to the implementation game, there is an opportunity to skip the physical infrastructure and base station installation and deploy NTRIP (Network Transport of RTCM via Internet Protocol). This would allow for the creation of a VRS (Virtual Reference Station) where needed allowing for field crews, drones or self-driving cars to stay connected as needed. This project allows the saving of a considerable amount of money by deploying a digital public service while laying the foundation for next gen precision technologies.]]></description>
      <pubDate>Fri, 21 Feb 2025 22:21:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512629</guid>
    </item>
    <item>
      <title>Improved Modeling for ACE and Ventilated Shoulder Design</title>
      <link>https://rip.trb.org/View/2512628</link>
      <description><![CDATA[Embankment deformation that results from thawing permafrost foundation soils often results in safety and drivability problems, and in extreme cases can result in structural embankment failure. Regular maintenance (often on an annual or bi-annual basis) is then needed to avoid safety and drivability problems. Air convection embankments (ACE) and ventilated shoulder systems can reduce or eliminate thaw settlement and related maintenance problems, but they are expensive to construct. Improved modeling and design tools would allow better “tuning” of these systems leading to improved thermal performance and reduced costs. 
Alaska Department of Transportation and Public Facilities (AKDOT) is currently using the Geoslope suite of modeling tools to analyze heat transfer in highway embankment designs, including ACE and ventilated shoulder installations. However, the existing Geoslope models are not capable of including the complex boundary conditions that arise when ambient air is drawn into and out of these roadway features, thus limiting the amount of detailed design that can be accomplished. The potential economic benefits generated by the proposed work will result from AKDOT design engineers being better able to predict the cooling behavior of ACE and ventilated shoulder layers. Currently these features are used sparingly due to the high cost of the required rock fill materials, even though they have proven effective at cooling foundation soils and maintaining the structural integrity of the supporting permafrost. Costs could be reduced significantly through the utilization of better modeling and design tools that would allow designers to reduce the required rockfill volumes without sacrificing the necessary amount of convective cooling capacity.]]></description>
      <pubDate>Fri, 21 Feb 2025 22:19:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512628</guid>
    </item>
    <item>
      <title>AI Tools for Rapid Post-Earthquake Damage Assessment for Bridges</title>
      <link>https://rip.trb.org/View/2512626</link>
      <description><![CDATA[The main goal of this study is to develop tools (artificial intelligence (AI) and analytical) that perform post-earthquake PDA and DDA on both standard and substandard columns that are in-service in Alaska. To achieve this goal, the following will be carried out (1) review of the BrM database and other resources such as drawings and inspection reports to extract the common column detailing specific to Alaska and to categorize them into standard and substandard columns, (2) a comprehensive literature review on the performance of such columns, (3) development of a comprehensive experimental database for substandard columns, (4) performing large-scale testing to establish damage pattern for substandard columns common in Alaska, and (5) development of AI and other analytical tools that can perform PDA and DDA on Alaska’s standard and substandard columns. Cloud-based tools or mobile applications equip with PDA and DDA tools can significantly expediate post-earthquake assessment of bridges by deploying local DOT personnel that are not necessarily bridge engineers/inspectors. These tools provide quick and safe evaluation to decide to open, partially open to first responders, or close the bridge.]]></description>
      <pubDate>Fri, 21 Feb 2025 22:11:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512626</guid>
    </item>
    <item>
      <title>Evaluation of Low Earth Orbit Broadband</title>
      <link>https://rip.trb.org/View/2512625</link>
      <description><![CDATA[High speed broadband and rural Alaska are not commonly referenced in a positive manner; however Alaska is getting a much-needed upgrade with Low Earth Orbit Internet Services and coverage areas coming online daily. Even today within 
Alaska Department of Transportation and Public Facilities (DOT&PF) staff are forced to operate in connectivity dead zones or even call into meetings because their internet connectivity cannot support the bandwidth. What we consider normal features at the workplace, many places in Alaska have yet to experience true broadband connectivity. With connected driving technologies, including IOT devices it is vital that Alaska catch up with the rest of the nation on connected services. If DOT&PF ever expects to operate as one DOT, then they need to fix connectivity and bandwidth. This project fixes Alaska’s biggest problem, infrastructure. Alaska is unable to provide a single solution across the state. Using this innovative space-based solution will offer more bandwidth for a fraction of the cost and enable nextgen technologies to be used at projects across the state.]]></description>
      <pubDate>Fri, 21 Feb 2025 22:05:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512625</guid>
    </item>
    <item>
      <title>Refine BrM Bridge Asset Management Models</title>
      <link>https://rip.trb.org/View/2512621</link>
      <description><![CDATA[The Alaska Department of Transportation and Public Facilities (DOT&PF) recently upgraded its AASHTOWare Bridge Management software (BrM) to the latest version. This upgrade resulted in changes to how the software identifies and recommends potential projects and forecasts future conditions. Support is needed to assist with the upgrade and the refinement of unit cost estimates, performance models, converter policies and other system inputs and settings. The regulation for Bridge Asset Management Plans includes bridge modeling standards in 23 CFR 515.17. This research will refine the current BrM model by updating the cost benefit analysis and evaluating work type alternatives for managing the condition of bridge assets. Work type recommendations are part of the Transportation Asset Management Plan (TAMP). Work type consistency reviews are completed by the Federal Highway Administration (FHWA) annually.]]></description>
      <pubDate>Fri, 21 Feb 2025 21:49:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512621</guid>
    </item>
    <item>
      <title>Freight Route Management Application for the Port of Anchorage</title>
      <link>https://rip.trb.org/View/2512620</link>
      <description><![CDATA[The objective of this research is to develop and evaluate an intelligent transportation management application for improving the efficiency, safety, reliability, and cost-effectiveness of freight and fuel truck movement to/from the Port of Alaska located in Anchorage, Alaska. This is a partnership project between the City of Anchorage’s Port of Alaska and Alaska Department of Transportation and Public Facilities (DOT&PF).  Truck transportation network located at the port will be able to better route and stage cargo transport within the Port of Alaska footprint. The application could be used outside the port by truck drivers, Alaska 511, and traffic operations centers.]]></description>
      <pubDate>Fri, 21 Feb 2025 21:42:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512620</guid>
    </item>
    <item>
      <title>Evaluation of Load Ratings for Alaska Legal Loads Exempted by Federal Law</title>
      <link>https://rip.trb.org/View/2512619</link>
      <description><![CDATA[In Alaska, the gross vehicle weight (GVW) is not specified. Alaska Department of Transportation and Public Facilities (DOT&PF) is working with Modjeski and Masters to evaluate how this could affect the bridge inventory. The study includes the review of weigh-in-motion (WIM) data, overload permit history, current bridge inventory capacity, plus AASHTO and National Bridge Inspection Standards (NBIS) requirements. The research study deliverables include (1) development of a notional load, rating formula, recommended maximum GVW, and live load factors to address loads on designated Alaska Interstate routes which conform to state legal limits but exceed the 80,000-pound Interstate GVW limit, (2) analysis of vehicles from legal loads up to 125% of state legal loads, and (3) recommended reduced inspection frequencies according to the new NBIS requirements for any affected bridges.]]></description>
      <pubDate>Fri, 21 Feb 2025 21:37:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512619</guid>
    </item>
    <item>
      <title>Anchorage Protected Bike Lane Pilot Study</title>
      <link>https://rip.trb.org/View/2512618</link>
      <description><![CDATA[This project documents and presents the results of a protected bike lane (PBL) pilot study conducted on two different Anchorage roads during the summers of 2023 and 2024. The pilots designed and installed one-way PBLs on both sides of Pine Street and McCarrey Street and a two-way PBL on the left side of 6th Avenue and A Street using temporary plastic flex-posts, rubber curb stops, traffic signs, striping, markings, and bike signals installed on a temporary basis. Public outreach measured cyclist and pedestrian comfort and public perception of different user groups, while traffic analysis quantified cycling usage, vehicle speed and travel time, and crash statistics. The study found that pilot protected bike lanes increased cyclist comfort and cyclist usage, resulted in minimal impact on traffic circulation, and identified common concerns from business owners and drivers for future projects. Moreover, the study demonstrated that pilot installations with lane conversions and temporary materials can be effectively implemented for use by the travelling public to investigate existing safety concerns, test out designs, and gather extensive public feedback.]]></description>
      <pubDate>Fri, 21 Feb 2025 21:32:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512618</guid>
    </item>
    <item>
      <title>Computer Vision Tools for Bridge Inspections and Reporting</title>
      <link>https://rip.trb.org/View/2512617</link>
      <description><![CDATA[This project focuses on research to develop practical artificial intelligence (AI) tools that help bridge inspectors with defect detection and measurements and to facilitate the inspection and reporting following National Bridge Inventory (NBI) and AASHTO Manual for Bridge Element Inspection (MBEI) requirements. The research team will produce a final report with recommendations including a set of verified open-source computer vision codes for damage detection and measurements, a user-friendly software for routine inspection and reporting, as well as a user guide and training sessions for Alaska Department of Transportation and Public Facilities (DOT&PF) engineers.]]></description>
      <pubDate>Fri, 21 Feb 2025 21:12:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512617</guid>
    </item>
    <item>
      <title>Corrosion Concerns in Alaska to Personal and Commercial Vehicles Caused by Winter Operations Chlorides</title>
      <link>https://rip.trb.org/View/2512615</link>
      <description><![CDATA[The objective of this research effort was to synthesize relevant information on corrosion to Department of Transportation (DOT) equipment and vehicles caused by chloride-based deicing materials used in the state of Alaska. To accomplish this, a survey of Alaska Department of Transportation and Public Facilities (AKDOT & PF) personnel was used to identify deicers used and corrosion concerns. A literature review was conducted, and a synthesis document was developed that identified common corrosion issues and best management practices (BMPs) that can be used to prevent and or reduce corrosion. Fact sheets were developed to share information on corrosion concerns and BMPs that can be used to prevent and or reduce corrosion for both AKDOT & PF and the public. Identified best practices include using corrosion inhibitors in deicing products, washing equipment and vehicles as frequently as is feasible, following washing applying barrier protection when feasible, and conducting routine inspections of equipment and vehicles to report and initiate repairs of corrosion related damage.]]></description>
      <pubDate>Fri, 21 Feb 2025 20:53:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512615</guid>
    </item>
    <item>
      <title>Cracking Resistance of Alaskan Asphalt with RAP Material</title>
      <link>https://rip.trb.org/View/2512614</link>
      <description><![CDATA[This research project aims to investigate the impact of reclaimed asphalt pavements (RAP) and rejuvenators on cracking performance of Alaskan hot mix asphalt (HMA) materials containing RAP and to develop a method to estimate RAP content for a given mix. Potential cost savings of up to 36% could be achieved when using the correct RAP combinations.]]></description>
      <pubDate>Fri, 21 Feb 2025 20:44:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512614</guid>
    </item>
    <item>
      <title>Computer Vision Tools for Bridge Inspections and Reporting</title>
      <link>https://rip.trb.org/View/2420106</link>
      <description><![CDATA[The Alaska Department of Transportation & Public Facilities (DOT&PF) is responsible for condition assessment of approximately 1000 bridges in the state.  Each year, Alaska DOT&PF engineers inspect about 500 bridges.  Per the Alaska Bridge Inspection Program, the inspector must complete both a National Bridge Inventory (NBI) inspection (following the FHWA Recording and Coding Guide) and an element level inspection (following the AASHTO Manual for Bridge Element Inspection, MBEI) for each bridge.  Using either NBI or MBEI, a significant amount of data must be collected and reported.  However, the data collection/reporting is usually done manually, which is time consuming, error prone, and sometimes not consistent when repeated.  For example, the deck defect mapping requires manual detection and measurement of delaminated concrete, patch repairs, exposed reinforcing steel, and spalling.  Computer vision, a type of image processing that incorporates artificial intelligence (AI) for analyzing the surroundings, can significantly expedite the process of damage/defect identification and measurement only using photographs of bridge deck and other elements.  Furthermore, this and other AI tools can be utilized to expedite and unify reporting.  The main goal of the present study is to develop practical AI tools that help inspectors with measurements and reporting of bridge defects following NBI and MBEI requirements.  To achieve this goal, a few bridge elements (e.g., decks and girders) will be targeted for further investigation, inspection database including photographs of the selected elements with/without damage will be compiled, and computer vision tools will be developed for the selected elements to recognize the element defects, quantify the defect per NBI/MBEI, and produce a report following the DOT&PF standard practice.  The tools, which can be standard software or web-based, will incorporate mobile devices for the ease of data collection, access, sharing, and reuse in future inspections.]]></description>
      <pubDate>Fri, 23 Aug 2024 14:40:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/2420106</guid>
    </item>
    <item>
      <title>Remote Sensing for Asset Data Collection in Rural Alaska</title>
      <link>https://rip.trb.org/View/2190091</link>
      <description><![CDATA[Data gaps in rural Alaska will be addressed and project delivery will be improved by optimizing UAS platforms, identifying which assets can be successfully captured and digitized, and determining acceptable image resolution, data quality standards and file formats. Tasks include: (1) collaboration and stakeholder partnering and community outreach, (2) testing and airworthiness, (3) demonstration and analytics, (4) workflow integration and geographic information system (GIS) integration deliverables, and (5) recommendation and reporting.]]></description>
      <pubDate>Fri, 02 Jun 2023 20:31:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2190091</guid>
    </item>
    <item>
      <title>DOT&amp;PF ArcGIS Image Server Deployment</title>
      <link>https://rip.trb.org/View/2190090</link>
      <description><![CDATA[This project develops the foundation for the next steps into the standardization of reality capture and remote sensing data. The image server will allow Alaska Department of Transportation and Public Facilities to collect, manage, and
serve imagery from a wide range of sensors on platforms ranging from satellites, aircraft, and drones. Tasks include: (1) kickoff and goal setting, (2) install and configure image for ArcGIS Online, (3) install and configure image server on Prem, (4) install and configure image server in Azure, (5) install and configure Virtual desktops, (6) conduct workshop for discussions, feedback on review, support, and capture feedback, and (7) summary of findings and recommendations for implementation in production.]]></description>
      <pubDate>Fri, 02 Jun 2023 20:22:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2190090</guid>
    </item>
    <item>
      <title>Integrated Avalanche Detection Warning &amp; Snow Distribution Mapping</title>
      <link>https://rip.trb.org/View/2190089</link>
      <description><![CDATA[The proposed research plan consists of multiple research objectives that include: (1) identifying minimum specifications for the hardware and location of infrasound sensors to detect avalanche activity along the Thane Road corridor; (2) determining the ideal placement of infrasound sensors to detect avalanche activity in the starting zones of Snowslide Creek, Middle Path, and Cross Bay Creek; (3) collaborating with subject matter experts to develop and implement an avalanche detection/warning system that can be used to alert officials of natural avalanches; (4) determining the size and location of natural avalanches using infrasound sensors; (5) conducting snow depth, avalanche size and distribution mapping using UAS with LiDAR and photogrammetry; (6) determining best available payloads to collect snow distribution data; (7) capturing and documenting avalanche occurrence spatially using UAS platforms to capture information during inclement weather; (8) developing standard operating procedures that can be shared with agency partners to showcase how emerging technologies can aid in avalanche hazard forecasting and decision making.]]></description>
      <pubDate>Fri, 02 Jun 2023 20:17:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2190089</guid>
    </item>
  </channel>
</rss>