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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Determination of carbon and microbial biomass amounts in neglected urban pavement crevice soils</title>
      <link>https://trid.trb.org/View/2632604</link>
      <description><![CDATA[Urbanization is causing soil sealing and ecosystem fragmentation, affecting soil health, biodiversity, and carbon storage potential. While green infrastructure is being promoted to address these challenges, small-scale habitats such as urban crevice soils (UCSs), referred to as soils in the gaps between concrete and asphalt surfaces in heavily urbanized areas, remain overlooked. The aim of this study was to determine whether UCSs are advantageous ecological units that sustain microbiological life and perform ecosystem services. This study quantified soil heterotrophic respiration, microbial biomass carbon (MBC) and nitrogen (MBN), soil organic carbon (SOC) and inorganic carbon (SIC), and total nitrogen (TN) in UCSs (with and without plants), nearby roadside soils, and soils from a switchgrass cropland in an urban farm within the Nashville metropolitan area in Tennessee, USA. On average, UCSs exhibited up to 436.2 %, 59.4 %, 217.6 %, and 266.9 % higher SOC, MBC, MBN, and C/N ratio compared to roadside and switchgrass soils, respectively. UCSs with plants have the highest microbial biomass, highlighting the synergistic role of plant presence in enhancing microbial function. These findings challenge the belief that urban soils are universally degraded and biologically inert, and regard UCSs as dispersed, small-scale contributors to urban ecosystem services. UCSs could serve as scalable, low-cost nature-based solutions that support resilient and sustainable cities amid rapid urbanization and environmental stress. Future studies should evaluate the ecological potential of UCSs as microhabitats for microbial biodiversity conservation, carbon storage, and ecosystem service delivery across various cities of different scales.]]></description>
      <pubDate>Wed, 18 Feb 2026 13:22:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632604</guid>
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      <title>Enhancing Transportation Impact Studies: Incorporating Safety and Multimobility Analyses</title>
      <link>https://trid.trb.org/View/2664090</link>
      <description><![CDATA[Over the last two decades, Nashville, Tennessee’s population has increased more than 60 percent. As the population continues to grow at a fast pace, so does traffic, transportation-related emissions, impacts on the environment, the need for better infrastructure and more housing, medical services, grocery stores, schools, parks, offices, restaurants, and retail. The amount of development occurring in the county has been enormous, with more than 28,000 building permits issued from 2022 to June 2025, which included residential, commercial, demolition, and use and occupancy building permit types. This article discusses the role that Transportation Impact Studies (TIS) have played in Nashville's development. It also emphasizes Nashville's Multimodal Transportation Analysis (MMTA) Guideline. Outcomes of a development’s TIS include mitigation measures to offset the added trips generated. Typical mitigation measures would include additions of turn lanes, traffic signals, signal retiming, road widenings, new public roads, sidewalks, transit facilities, and safety improvements. While development impact fees cannot be utilized in Tennessee, Nashville depends on the TIS to ensure infrastructure needs are addressed.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:11:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664090</guid>
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    <item>
      <title>Evaluating safety effects of variable speed limit systems via joint modeling</title>
      <link>https://trid.trb.org/View/2604806</link>
      <description><![CDATA[Variable Speed Limits (VSL) systems are key components in Active Traffic Management System (ATMS). They dynamically and coordinately adjust speed limits to harmonize traffic flow thereby enhancing travel safety and reliability. The objective of this study is to evaluate the safety impacts of the VSL deployed on the I-24 Smart Corridor, Nashville, Tennessee, which went online in June of 2023. Safety indicators were measured by various crash outcomes, and they were typically modeled separately in previous studies. The potential correlations between collision type and its consequence represented by severity were often overlooked, leading to the underestimation of treatment effects. Hence, this study attempts to jointly model the rear-end, injury, and Property Damage Only (PDO) under the copula framework. The treatment effect, which is also known as the Crash Modification Factor (CMF) in before-after studies, is estimated by the Difference-in-Differences estimator in the marginal Negative Binomial (NB) model. Gaussian, Frank, and Clayton copulas were compared, and the best-fitting copula was used to estimate the model parameters. The results indicate that the copula models significantly outperform the separate NB models. The CMFs of rear-end and injury crashes resulting from VSL implementation are 0.677 and 0.686 respectively. Their scale-invariant correlation is very high (i.e., 0.91 out of 1), which suggests that the reduction in injury crashes may be attributed to the reduction of rear-end crashes. However, the change in PDO crashes was not statistically significant, possibly due to the shift from injury crashes to PDO crashes after traffic slowing down in adverse traffic conditions. Finally, the study results confirm the positive impact of implementing VSL systems and help justify future investments for candidate corridors.]]></description>
      <pubDate>Mon, 27 Oct 2025 09:34:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604806</guid>
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    <item>
      <title>What Policy and Budget Choices Yield the Greatest Decreases in Pedestrian &amp; Bicyclist Fatality Rates?</title>
      <link>https://trid.trb.org/View/2596495</link>
      <description><![CDATA[US pedestrian fatalities increased from 22,100 during the 2008-2012 five-year period to 32,674 during the 2017-2021 five-year period (a 48% increase). Bicyclist fatalities increased from 3,385 to 4,450 during the same timeframe (a 31% increase). However, changes in fatality rates were not distributed evenly across US communities between 2008-2012 and 2017-2021. Overall, ACS journey-to-work data showed that US pedestrian commuting decreased from 2.82% to 2.48% and bicycle commuting decreased from 0.56% to 0.48% of all workers between the baseline and later study periods. However, pedestrian commuting increased in MSAs such as Virginia Beach, VA, San Diego, CA, San Jose, CA, and Dallas, TX and counties such as Collin County, TX (Plano), San Francisco County, CA, Davidson County, TN (Nashville), and Jefferson County, AL (Birmingham). Bicycle commuting increased in MSAs such as New York, NY, San Antonio, TX, and Washington, DC, and counties such as Collin County, TX (Plano), New York County, NY (Manhattan), and Hudson County, NJ (Jersey City). Nationally, pedestrian fatality rates increased by 51% (from 1.12 fatalities per thousand to 1.70 fatalities per thousand walk commuters) and bicyclist fatality rates increased by 40% (from 0.86 fatalities per thousand to 1.20 fatalities per thousand bike commuters). Yet, pedestrian fatality rates decreased in New York, Massachusetts, New York County, NY (Manhattan), Collin County, TX (Plano), Kings County, NY (Brooklyn), and Essex County, MA. Bicyclist fatality rates decreased in New York, Massachusetts, Arkansas, Hartford County, CT, Queens County, NY, Kings County, NY (Brooklyn), and San Mateo County, CA. Identifying leading communities may help reveal policies and practices that can be used in other parts of the country to increase pedestrian and bicyclist activity and reduce pedestrian and bicyclist fatalities.]]></description>
      <pubDate>Wed, 24 Sep 2025 15:31:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2596495</guid>
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    <item>
      <title>Identification of Simulation Calibration Parameters Using Urban Freeway Data</title>
      <link>https://trid.trb.org/View/2526713</link>
      <description><![CDATA[The reliability of a microsimulation model such as VISSIM depends on proper calibration and validation to accurately represent real-world traffic conditions. However, the VISSIM default values do not apply to local traffic conditions and need to be calibrated for local traffic conditions considering the higher number of car-following parameters. Hence, the present study determines TN-specific calibration parameters for PTV VISSIM microsimulation software using urban freeway data in TN. Field data were collected from the four majorly populated cities of TN namely Memphis, Nashville, Knoxville, and Chattanooga during the peak and off-peak hours of traffic using videography method. Trajectories were extracted using the YOLO-v8 computer vision techniques and the traffic flow variables were obtained from the microscopic trajectories. Wiedmann 99 carfollowing parameters were selected for the calibration of VISSIM. It was found that considering all the ten carfollowing parameters in the simulation model significantly reduces the error values between observed and simulated flow rates for the TN urban freeways.]]></description>
      <pubDate>Tue, 25 Mar 2025 09:30:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2526713</guid>
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    <item>
      <title>Integrating AI and edge computing for advanced safety at railroad grade crossings</title>
      <link>https://trid.trb.org/View/2483404</link>
      <description><![CDATA[The integration of artificial intelligence (AI) and machine learning (ML) into the Railroad High-Grade Crossing (RHGC) systems represents a significant milestone in enhancing both safety and operational efficiency. The fusion of various technologies enables the seamless integration of real-time identification, accurate forecasting, and prompt reaction to pivotal traffic situations. This research introduces a state-of-the-art architecture based on edge cloud technology. It integrates advanced computer vision algorithms for object detection and segmentation with a custom dataset for RHGC safety. In the proposed novel framework, the authors utilize a Weighted box- Fusion (WBF) ensemble approach, integrating diverse object detection algorithms, such as YOLOv8M (medium), YOLOv8L (Large), and YOLOv8X (extra-large), to enhance the detection of safety measures at RHGCs objects. Moreover, the authors incorporate a UNet segmentation model to identify trains approaching the RHGCs. The amalgamation of these methodologies leads to a fully automated, AI-driven safety mechanism for RHGC. The edge-cloud architecture is employed, with surveillance cameras linked directly to an edge server strategically positioned at grade crossings. This arrangement facilitates real-time data processing, ensuring efficient bandwidth usage and minimal latency by relaying only the necessary processed information to the cloud. The authors' ensemble model demonstrated an impressive precision rate of 97%, with the segmentation model achieving a higher rate of 98%. This system establishes a novel standard within the discipline, amalgamating artificial intelligence, edge computing, and cloud technology to significantly augment safety and efficiency at grade crossings.]]></description>
      <pubDate>Mon, 27 Jan 2025 15:39:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2483404</guid>
    </item>
    <item>
      <title>Safety Insights from E-Scooter Rider and Bicyclist Behavior Observations in Two U.S. Cities</title>
      <link>https://trid.trb.org/View/2447292</link>
      <description><![CDATA[E-scooters, a novel micromobility mode, have transformed U.S. transportation in urban cores, offering potential advantages like cost-effective mobility, congestion reduction, community accessibility, and lower emissions. However, owing to their novelty, their associated safety impacts and rider behaviors remain uncertain, complicating policy formulation. Specifically, e-scooter policy often mirrors bicycle policy, yet there have been few studies that have explicitly investigated how e-scooter and bicycle rider behaviors compare. This research investigated rider behavior relative to infrastructure by examining riding patterns through a video-based platform on 26 Nashville and Portland streets, offering insights on e-scooter and bicyclist behaviors, including riding location and helmet use. This study differs from other observational studies since it covers longer observation periods than prior in-person studies, including nighttime riding behavior. The video analysis also allows for observations of basic demographic characteristics. The findings revealed that bike lanes were well-used and dramatically reduced sidewalk riding and general travel lane usage. Without bike lanes, riders typically resorted to using sidewalks on high-capacity roads and sharing lanes with vehicles on low-capacity streets. The data also suggested demographic trends, such as riskier behavior among younger, male riders, and low helmet usage among e-scooter riders. The results emphasize the need for micromobility-supportive infrastructure in road design to encourage safer riding practices.]]></description>
      <pubDate>Tue, 05 Nov 2024 14:27:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2447292</guid>
    </item>
    <item>
      <title>Analysing Autonomous Delivery Acceptance in Food Deserts Based on Shopping Travel Patterns</title>
      <link>https://trid.trb.org/View/2420021</link>
      <description><![CDATA[Food desert communities in the US have a widely recognized gap between the demand for healthy foods and the minimum order size that makes it worthwhile for food purveyors to deliver to such neighborhoods, thereby creating delivery deficiencies. A diverse set of mobility constraints and activity-travel patterns exist for disadvantaged segments in these communities, especially the elderly, unemployed, and socially excluded. Appreciating this complexity, an effective solution would be to improve the food access of such communities by providing faster, inexpensive, and flexible online deliveries of healthy foods. However, little is currently known about the shopping travel pattern in food desert communities and the associated mobility inequalities. This paper fulfills this critical research gap and quantifies the differences in shopping travel behavior observed among consumers residing in food deserts and food oases using data collected from Portland and Nashville Metropolitan areas. The paper subsequently captures the perceived acceptance of autonomous delivery robots (ADRs) among these consumers to overcome their mobility inequalities. The results indicate that food desert residents aged between 18 to 25 years, African Americans and earning more than $75,000 are more likely to engage in internet shopping than food oasis residents. Despite the perceived potential of ADRs to reduce the mobility inequalities in food deserts, acceptances levels for this emerging technology are found to be significantly less among food desert residents, especially among older generational cohorts and less qualified. This study will provide key takeaways to e-commerce companies to expand their delivery service through ADRs in underserved areas.]]></description>
      <pubDate>Mon, 26 Aug 2024 11:21:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2420021</guid>
    </item>
    <item>
      <title>Quantifying Support Practice Sub-Factor Values for Erosion-Control and Sediment Retention Devices</title>
      <link>https://trid.trb.org/View/2343494</link>
      <description><![CDATA[Roadway construction sites can be substantial contributors to sediment pollution; however, erosion can be mitigated by utilizing erosion prevention and sediment control devices. An estimation of the erosion can be determined empirically through the revised universal soil loss equation (RUSLE) or deterministically with the water erosion prevention project (WEPP) to design sediment control measures. Due to RUSLE’s empirical structure, limitations occur in determining accurate erosion yields per use of empirical factors. WEPP can simulate erosion yields based on physical site conditions. In this study, WEPP was used to estimate the RUSLE erosion control practices factor (P-factor). A variety of different parameters influence the efficiency of these sediment control devices, including drainage area, climate, soil types, topography, and land use/cover. This study focused on a combination of five common soil types (clay loam, silt clay loam, silt clay, silt loam, and loam) and four climate regions (Knoxville, Nashville, Chattanooga, and Memphis) in Tennessee to generate P-factors for silt fences and straw-filled sediment tubes. The study was performed by generating and calibrating a hillslope model, performing numerical simulations for a generated watershed, and determining and analyzing the P-factor. While no significant fluctuations of the P-factor for the different climate regions were found, there were significant differences for the soil type. The soil type had the greatest influence on the efficiency of these sediment control devices due to variations in soil composition and hydraulic conductivity. The soil type with the greatest efficiency was silt clay loam (P= 0.34 for silt fences), while silt loam produced the least level of reduction (P= 0.55 for straw-filled sediment tubes). Both tables and regression equations were created to model the P-factor for each combination of climate and soil type.]]></description>
      <pubDate>Mon, 11 Mar 2024 16:32:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2343494</guid>
    </item>
    <item>
      <title>Analysis of spatiotemporal transit accessibility and transit inequity of essential services in low-density cities, a case study of Nashville, TN</title>
      <link>https://trid.trb.org/View/2310868</link>
      <description><![CDATA[Evaluating the accessibility and equity of transit services to essential services that fulfill people’s fundamental needs is critical, especially in lower-density areas with limited transit services. Although numerous studies have analyzed the inequity of transit accessibility in dense, urban areas with robust transit networks, few of them evaluated transit inequity across multiple essential service categories (e.g., food stores, healthcare facilities, schools, etc.). This paper fills this research gap by focusing on a low-density, automobile-oriented city (Nashville, TN) to evaluate spatial transit inequities across essential service deserts and sociodemographic groups. The results of the case study show that many areas with higher transit-dependent demand (i.e., populations with limited personal vehicles, those living in poverty, and minority populations) tend to experience more restricted transit access to food, healthcare, school, and childcare facilities; interestingly, this is not the case for transit access to green space (specifically, parks). This study further identified essential service deserts by Local Indicator of Spatial Association (LISA) clustering and analyzed the correlation among them. The correlation results suggest that food deserts, healthcare deserts, school deserts, and childcare deserts are highly correlated with each other, while they have a lower correlation with park deserts. The findings of spatial transit inequity and the identification of essential service deserts provide crucial policy implications that can be used by transit agencies and local planning departments to prioritize their resources and target interventions to improve transit equity. This study contributes to the existing literature by proposing a systematic process that utilizes publicly available datasets to measure spatiotemporal transit supply, identify essential service deserts, and explore the correlation among these areas in a low-density city.]]></description>
      <pubDate>Fri, 26 Jan 2024 10:02:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2310868</guid>
    </item>
    <item>
      <title>The Potential for Green Infrastructure Practices to Reduce Combined Sewer Overflows as Examined in Nashville, Tennessee</title>
      <link>https://trid.trb.org/View/2271504</link>
      <description><![CDATA[The Nashville downtown, as in many cities, is drained by a combined sewer suffering from overflows. This project was performed as part of an overall evaluation of the use of Green Infrastructure (GI) to reduce the runoff entering the system. Continuous simulations were performed with 36 years of local rainfall and potential evapotranspiration data. Prototype bioretention cells, pervious pavements, green roofs and tree planters were modeled using the Environmental Protection Agency Storm Water Management Model (SWMM). SWMM was used to model the GI prototypes. Rainfall, surface evaporation, infiltration, transpiration, deep percolation, runoff and runon were considered. To test sensitivity and create design curves, a full range of models was created by varying media depths, ratio of runon area to facility area, deep percolation rates, media and plantings. A total of 103 prototype models were run and evaluated for the volume of runoff. The modelling results were realistic and showed clear trends in runoff volume. The GI practices were found to significantly reduce volume of runoff. Runoff volume was sensitive to deep percolation rate and runon area, and less sensitive to media and planting characteristics. Design curves were created based on the continuous modelling so that designers could properly size GI facilities to consider the full range of flows, rather than on a single event flow or rule of thumb.]]></description>
      <pubDate>Fri, 22 Dec 2023 08:46:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2271504</guid>
    </item>
    <item>
      <title>Shared e-scooter service providers with large fleet size have a competitive advantage: Findings from e-scooter demand and supply analysis of Nashville, Tennessee</title>
      <link>https://trid.trb.org/View/2286763</link>
      <description><![CDATA[Shared e-scooter systems are one of the fastest-growing micromobility modes in the United States. In response to service providers’ rapid deployment of e-scooter vehicles, several city governments have regulated shared e-scooters through permits and pilot programs, including the number of service providers, their fleet size, and provisions for expanding/downsizing the fleet size. However, the literature lacks an empirical analysis of the demand elasticity of shared e-scooters. The authors used a Poisson fixed effects regression to evaluate the demand elasticity of e-scooter vehicle deployment using the Shared Urban Mobility Device (SUMD) dataset from Nashville, Tennessee, between March 1, 2019 and February 2020. This dataset included disaggregated e-scooter trip summary data and vehicle location data that updates approximately every five minutes. The authors also estimated land-use specific demand elasticity of e-scooter vehicle deployment by clustering Traffic Analysis Zones (TAZs) using the K-means algorithm. The authors found that the average daily demand elasticity of e-scooter vehicle deployment is inelastic (0.64). Service providers with large fleet sizes (>500 average daily e-scooters) have a demand elasticity of e-scooter deployment that is 1.8 times higher than that of medium fleet-sized service providers (250–500 average daily e-scooters). Fleet size is likely correlated to service provider-specific attributes such as vendor popularity, brand loyalty, and rideshare services. The authors also found a significant difference in demand elasticity of e-scooter deployment for land use types, with university and park & waterfront land uses having the highest elasticity values. These findings could be helpful for city governments to identify the optimal number of service providers and fleet sizes to permit so that demand is fulfilled without an oversupply of e-scooter vehicles in public spaces.]]></description>
      <pubDate>Mon, 20 Nov 2023 09:12:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2286763</guid>
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    <item>
      <title>Gateway Boulevard over the Cumberland River Nashville, Tennessee</title>
      <link>https://trid.trb.org/View/2235731</link>
      <description><![CDATA[The City of Nashville, Tennessee contracted with HNTB Corporation to complete environmental documents, preliminary design and final design for the new Gateway Boulevard Bridge over the Cumberland River in downtown Nashville. The primary criterion for the bridge was to create a "signature bridge" that would become a trademark of Nashville. HNTB developed several alternatives for this bridge including haunched plate girders, thru arch, tied arch and cable-stayed alternatives. The City chose the thru arch as the structure type to be advanced to final design and construction. The total bridge length is 495 meters (1624 feet) with a navigation span of 180 meters (591 feet). The cross section of the bridge includes six traffic lanes with a bike lane and 3 meter (10 foot) sidewalks on each side giving an overall bridge width of 31 meters (102 feet). This project includes roadway design, geotechnical investigation and evaluation, aesthetic lighting and drainage design. It is anticipated that the construction will be completed near the end of 2003. This paper will look at the design, fabrication and erection of the steel box arch rib and roadway, including very different foundation conditions on the east and west banks of the Cumberland River.]]></description>
      <pubDate>Fri, 17 Nov 2023 11:32:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235731</guid>
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    <item>
      <title>Rehabilitation of Shelby Street Bridge - Combining the ''New And The Old''</title>
      <link>https://trid.trb.org/View/2235729</link>
      <description><![CDATA[The study concluded that the bridge could be rehabilitated, but that extensive work was needed. The concrete in both the superstructure and substructure had always been a problem; so long term solutions were necessary so as not to impose excessive maintenance costs on the city. The work would have to be carefully done to respect the historic integrity of the bridge. The important elements such as the piers and trusses would have to incorporate details that were acceptable to the State Historic Preservation Officer.]]></description>
      <pubDate>Fri, 17 Nov 2023 11:32:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235729</guid>
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    <item>
      <title>I-24 MOTION: An instrument for freeway traffic science</title>
      <link>https://trid.trb.org/View/2240587</link>
      <description><![CDATA[The Interstate-24 MObility Technology Interstate Observation Network (I-24 MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 MOTION consists of 276 pole-mounted high-resolution traffic cameras that provide seamless coverage of approximately 4.2 miles I-24, a 4-5 lane (each direction) freeway with frequently observed congestion. The cameras are connected via fiber optic network to a compute facility where vehicle trajectories are extracted from the video imagery using computer vision techniques. Approximately 230 million vehicle miles of travel occur within I-24 MOTION annually. The main output of the instrument is vehicle trajectory datasets that contain the position of each vehicle on the freeway, as well as other supplementary information such as vehicle dimensions and class. This article describes the design and creation of the instrument, and provides the first publicly available datasets generated from the instrument. The datasets published with this article contains at least 4 hours of vehicle trajectory data for each of 10 days. As the system continues to mature, all trajectory data will be made publicly available at i24motion.org.]]></description>
      <pubDate>Mon, 25 Sep 2023 14:46:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2240587</guid>
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