<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>Pavement Conditions Assessment and Prediction (PCAP): A geospatial machine learning approach to inform decision-making</title>
      <link>https://rip.trb.org/View/2570737</link>
      <description><![CDATA[The Maine Department of Transportation (MaineDOT) continues to observe an increased rate of pavement deterioration on its 8,800 mile roadway network, which is the largest and most heavily used component of the transportation system under the MaineDOT’s jurisdiction. Pavement deterioration is governed by a variety of factors, including traffic load, quality and design of the pavement structure, increased frequency of climatic events like freeze-thaw cycles, topographic influences and drainage, and geologic considerations like the native subgrade soils. While these factors have been identified individually as potential attributes to pavement degradation and distress, it is likely the confluence of several attributes that impute the greatest rate of degradation on pavement systems. However, the combination(s) of attributes linked to varying degrees of the pavement degradation rate remain poorly understood and must be identified to make informed decisions regarding resource allocation. 
This project seeks to identify and link the combination(s) of attributes described in the preceding section (e.g. pavement design/structure/quality, traffic loading, environmental stressors) to temporal and spatial differences in the rate of pavement degradation on MaineDOT’s highway network; i.e. to understand the relative influence of attributes imputing pavement distress. By working with the MaineDOT, UMaine will use existing and/or collect new pavement quality data (geo-located cracking index values) using the Automatic Road Analyzer (ARAN) to quantify the degree of pavement distress. ARAN data surveyed across the state will allow an assessment of variations in pavement quality across pavement types (e.g. new construction, rehabilitation, spot improvements, LCP, preservation paving), regions/space (i.e. for consideration of climate, geology, drainage, wetness, soil, and traffic loading) and epochs (time since last paving or improvement). 
The project is expected to consist of three components:
Phase 1a (3-6 months): A literature review of existing studies and methods that incorporate data-driven analyses of spatial and/or temporal differences in the rate of pavement degradation. 
Phase 1b (18-21 months): Data-collection and integration, mapping & visualization, and predictor selection and attribution of factors influencing pavement degradation rates via machine learning. 
Phase 2: (18 months): Extension and refinement of Phase 1b to develop a tractable forecasting model to predict the degradation rate of pavement systems.



]]></description>
      <pubDate>Wed, 02 Jul 2025 11:39:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2570737</guid>
    </item>
    <item>
      <title>Cenozoic fracture systems in western North Carolina and their contribution to large, slow-moving, deep-seated landslides</title>
      <link>https://rip.trb.org/View/2563763</link>
      <description><![CDATA[Recent studies have shown that multiple fracture systems occur across western North Carolina that are associated with linear topographic lows, such as the Swannanoa Lineament that contains the I-40 corridor from Swannanoa through Asheville. Earthquakes have occurred on several of these lineaments suggesting they are seismically active. Multiple large, slow-moving landslides have been identified within these lineaments. This study will test the hypothesis that bedrock fractures within Cenozoic aged lineaments across western North Carolina are planes of weaknesses that contribute to these large, slow-moving landslides. This study will combine geologic mapping in the field and from high-resolution LiDAR data with kinematic slope stability analyses and topographic studies. This work will (1) constrain the bedrock structures that act as failure planes, (2) relate these structures to the lineament fracture systems, and (3) characterize the topographic evolution that resulted from these fracture systems that may influence the stability of slopes. Understanding the dynamics of these large, slow-moving landslides will enable the 
North Carolina Department of Transportation (NCDOT) to develop efficient practices to mitigate damage to infrastructure.]]></description>
      <pubDate>Fri, 13 Jun 2025 12:08:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2563763</guid>
    </item>
    <item>
      <title>Demonstrating the Capabilities of UAS Topobathymetric LiDAR Mapping in Support of DOT Project Planning, Monitoring and Modeling</title>
      <link>https://rip.trb.org/View/2003589</link>
      <description><![CDATA[University of North Carolina Wilmington (UNCW) has uniquely positioned itself as a leader in the unmanned aerial systems (UAS hereafter) field over the last several years, in large part thanks to a research contract awarded by the North Carolina Department of Transportation (NCDOT) in August 2019, slated to end Dec. 31st 2021. Through prior UAS work led by PI Pricope and the work completed under RP2020-04 (Fusing multi-source UAS-derived data to improve project planning and the NCDOT Wetlands Prediction Model), the researchers have gained invaluable experience working with UAS-collected topographic LiDAR (Light Detection And Ranging) data and this uniquely positions UNCW to continue to lead the development of frontier applied data collection, processing and implementation for NCDOT’s next generation topo-bathymetric LiDAR integration. Previous work has enabled the research lab to: (1) develop field data collection, sampling, calibration and validation protocols for effective UAS data collection and processing using both fixed-wing passive, as well as rotocopter-mounted active (LiDAR) sensors; (2) implement effective, replicable and transparent processing workflows to create validated, ortho-photogrammetrically and planimetrically correct UAS-derived products, following ASPRS technical standards for imagery and LiDAR data horizontal and vertical positioning accuracy; and (3) develop and apply geospatial analytical data classification (including machine learning) workflows and UAS to satellite imagery fusion techniques. Work conducted at multiple coastal wetland sites throughout the southeastern NC showed that the capabilities of topographic LiDAR data collection are severely limited in water-covered, partially-inundated, or tidally-influenced zones, where LiDAR returns are null. In this proposal, building on the extensive field, lab, data processing and machine learning classification approaches developed under RP2020-04, the research team makes the case for extending NCDOT’s LiDAR capabilities by adding the capabilities of a topo-bathymetric LiDAR instrument to the array of UAS-borne sensors in NCDOT’s inventory. The team proposes to conduct highly applied research across a spectrum of clear, tannic and turbid waters of varying depths to fill gaps and improve data quality and collection capabilities for activities that include planning, monitoring and inspections. Examples of applications and data products include but are not limited to planning guidance for bridge, drainage, ferry, mitigation and abatement projects, modeling and mapping flooding and stormwater management approaches, aquatic habitats, hydrography, substrate and sediment transport, underwater archeology, and tidally-influence zones, and monitoring debris accumulation (dams, bridges), scouring, shoaling, channelization and sedimentation in ferry or shipping corridors. The team plans to accomplish five distinctive tasks: (1) conduct thorough literature and technical review of the state-of-the-art in the UAS-based topo-bathy space both from an academic and industry perspective, including outreach and a review of other state DOTs similar capabilities and approaches; (2) create a replicable and easy to implement project design and sampling strategy that spells out pre- and mission criteria and considerations to ensure safe and successful project execution; (3) design and execute field data collections across a gradient of use cases and conditions and conduct outreach to public schools in the region during this process; (4) implement end-to-end data pre- and processing workflows for the site data collected and construct an implementation practicality envelope that clearly spells out what is and is not feasible and accomplishable with the request technology from an applied perspective by area of application (planning, modeling and mapping, and monitoring); and (5) conduct sustained outreach throughout the duration of the project to K-12 and university students from a range of socioeconomic backgrounds, conduct a 2-day NCDOT training/webinar series and create clear and usable final deliverables, including but not limited to technical instructions manuals for all stages of planning, collection, preprocessing, processing and visualizations, data dictionaries and metadata for all datasets created during the project, and final copies of all data collected. This project will result in time and cost savings through increased inspection capabilities, improved mapping and models of water areas, and more robust measurements of drainage system capacities.]]></description>
      <pubDate>Fri, 05 Aug 2022 08:50:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2003589</guid>
    </item>
    <item>
      <title>Environmental Justice Implications of Roadway Topography </title>
      <link>https://rip.trb.org/View/1635480</link>
      <description><![CDATA[Automobile emissions from highways are known to have harmful effects on the public. These harmful effects also raise concerns of environmental justice because their severity is highest near the transportation network. Established methodologies used in regional planning to identify the critical extent of emission dispersal from the highway and also to demarcate the boundaries of population group that is most at risk uses a fixed distance buffer analysis. These established methodologies also do not account for the effect of roadway topography on amount of emissions. Recent studies have shown that roadway topography can result in overestimation or underestimation of the quantity of emissions. The spatial concentration of pollutants depends to a large extent on quantity emitted. Therefore, it is possible, depending on local conditions, that a fixed distance buffer analysis could overestimate or underestimate the boundaries of the affected population. 

This proposed research will investigate the implications of roadway topography on the ubiquitous fixed distance of 200 m that is usually used in analysis. It will use Vissim simulation to generate vehicle activity data over high traffic highway corridor and use the vehicle activity data to estimate emission inventories. The estimated emissions will be used as input in an air dispersal model to investigate the spatial concentration of the pollutant from the highway in order to verify the adequacy or inadequacy of the fixed critical distance. 

The findings from this research will be beneficial to decision makers at Metropolitan Planning Organizations (MPOs) and city governments who have to consider environmental justice effects of their transportation plans. This research is significant because it will increase our understanding on whether existing methodologies are doing enough to accurately account for populations that are exposed to the detrimental effects of automobile emissions.  ]]></description>
      <pubDate>Thu, 04 Jul 2019 10:48:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/1635480</guid>
    </item>
    <item>
      <title>Supplement to Phase 1 of the Alabama SHSP Update</title>
      <link>https://rip.trb.org/View/1365434</link>
      <description><![CDATA[In response to the latest federal transportation authorization, the Moving Ahead for Progress in the 21st Century Act (Map-21), the Alabama Department of Transportation (ALDOT) is updating its Strategic Highway Safety Plan (SHSP).   Purpose of the SHSP is to serve as the comprehensive safety program for all public roads in the State.  It is produced in coordination with other State safety agencies, is consistent with other State safety plans, and provides the framework for reducing fatalities and serious injuries on the State's roadway network.   It is proposed that a team comprising the University of Alabama (UA) and Cambridge Systematics (CS) conduct Phase 1 of Alabama SHSP update.  The University Transportation Center for Alabama (UTCA) will lead the project with support from the Center for Advanced Public Safety (CAPS) at UA.  Cambridge Systematics will provide technical support and strategic guidance over the course of Phase 1. The proposed project will add the Birmingham and Southwest Alabama Regions to Phase I of SHSP.  By including the additional regions, the team will be able to develop a comprehensive understanding of the different demographic, socio-economic, topographical and road safety issues throughout the State.  The objective of the proposed project is to produce two additional SHSPs for the new regions added herein.]]></description>
      <pubDate>Fri, 14 Aug 2015 01:00:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1365434</guid>
    </item>
    <item>
      <title>Speed and Design Consistency of Combined Horizontal and Vertical Alignments in Two-Lane Rural Roads</title>
      <link>https://rip.trb.org/View/1249657</link>
      <description><![CDATA[The American Association of State Highway and Transportation Officials (AASHTO) establishes that the highway design speed should be logical with respect to the anticipated operating speed, the topography, the adjacent land use, and the functional classification. The AASHTO equation for the minimum horizontal curve radius for a given design speed depends on the combination of the superelevation rate and the side friction factor. This equation provides a balance of forces acting on a vehicle traversing on a circular path for a given speed, but does not consider the effect on the actual speed and the safety performance of an overlap between horizontal and vertical curves. The presence of the longitudinal grade in horizontal curves tends to increase the risk of crashes because it affects the driver's perception of the horizontal curvature. The objective of this investigation is to study the influence in safety and operating speeds when a horizontal curve is combined with a vertical curve. The study will identify the relationship between the combined horizontal and vertical alignment conditions, operating speeds, and safety, used in the design consistency assessment of two-lane rural highways. A sampling of two-lane rural roads will be performed to identify horizontal curves overlapped with vertical curves in Puerto Rico. Roadway geometry, free-flow speed and crash data will be collected for the selected sites. The speed data will be collected at different points along the horizontal curve with the use of portable traffic classifiers and vehicle-tracking speed guns. The radius of horizontal curves has been identified as one of the most relevant highway features in influencing operating speeds (driving behavior). Most of the earlier studies on speed prediction and design consistency focused on isolated horizontal alignment conditions. One of the expected results is a comprehensive review of recent studies that have explored the issue of combined horizontal and vertical alignment and design consistency. It is anticipated that the recent literature will demonstrate the need for a speed prediction model for different types of curves radius and vertical grades. Another anticipated result is the development and calibration of a curve speed model that considers the geometric design of combined horizontal and vertical alignments. This model could serve to update current geometric design practices and the AASHTO horizontal curve design equation. In addition, the speed and crash data could serve to update speed and crash prediction models for two-lane rural roads that could enhance the roadway assessment tools included in the Highway Safety Manual and Safety Analyst.]]></description>
      <pubDate>Fri, 03 May 2013 01:00:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1249657</guid>
    </item>
  </channel>
</rss>