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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>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>A Performance- and Cost-Based Framework to Evaluate the Value of Multimodal Logistics Infrastructure</title>
      <link>https://trid.trb.org/View/2703796</link>
      <description><![CDATA[This project develops a practical, data-driven framework to evaluate the value of logistics infrastructure in a multimodal freight region. Focusing on the St. Louis metropolitan area, the framework integrates freight performance measurement with generalized logistics cost modeling to translate travel time, reliability, and terminal access improvements into economic outcomes. Methods include assembling a regional freight network representation, computing corridor-level travel time and variability metrics, and applying scenario-based valuation to estimate marginal benefits of targeted investments. The project also includes a private-sector truck–rail–barge use case to quantify multimodal tradeoffs and assess the competitiveness of inland waterway transportation under alternative infrastructure scenarios. The resulting workflow provides agencies and regional partners with transparent, repeatable methods to support freight investment prioritization and decision-making.]]></description>
      <pubDate>Sat, 16 May 2026 11:52:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703796</guid>
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    <item>
      <title>Eads Bridge Highway Deck Reconstruction</title>
      <link>https://trid.trb.org/View/2235378</link>
      <description><![CDATA[The Eads Bridge, the first bridge to span the Mississippi River at St. Louis, was dedicated on July 4, 1874. The double deck structure is a National Historic Landmark that has carried countless horse drawn wagons, locomotives, automobiles, trucks and pedestrians. For most of its history, the Eads Bridge was owned by various railroads. The Terminal Railroad Association of St. Louis operated the upper highway deck as toll bridge even after the lower rail deck was closed in 1974. The City of St. Louis acquired the bridge in 1989 and donated the lower level to be used by the community's light rail system, MetroLink. The lower rail deck was rehabilitated and re-opened in 1993 when MetroLink debuted. The upper roadway deck became structurally deficient and the bridge was closed to highway traffic in 1991 during the construction of MetroLink. The most recognizable feature of the bridge is the portion over the river, which consists of three long steel arch truss spans. Besides the main river spans, the historic structure consists of the West Approach, the West Arcade and the East Arcade. The Eads Bridge also includes two East Approach ramps that had been entirely replaced before the bridge was 50 years old. The historic structure is approximately 3000 feet in length while the ramps are each approximately 1000 feet long. The demolition portion of the project included removal of the existing deck and toll facilities on the historic structure and removal of the entire East Aproach ramps. After an extensive rehabilitation that began in late 1998, the highway deck was re-opened in a ceremony held July 4, 2003, 129 years after its original debut.]]></description>
      <pubDate>Mon, 20 Apr 2026 09:22:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235378</guid>
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      <title>Construction of Seismic Retrofit Strategies of the US 40/I-64 Double Deck Bridge Complex</title>
      <link>https://trid.trb.org/View/2235353</link>
      <description><![CDATA[The 1989 Loma Prieta Earthquake collapsed part of the Interstate 880 Freeway (Cypress Street Viaduct) taking the largest human toll exacted on a highway system. As a result, the Federal Highway Administration began a program requiring immediate evaluation of all double deck highway bridges in the United States. This paper presents the evaluation of one such structure in St. Louis, Missouri highlighting seismic retrofitting techniques designed to improve the performance of concrete elements and overall bridge performance in an urban setting. The Daniel Boone Expressway in downtown St. Louis, Missouri, is one such multi-level bridge providing a major east-west transportation link for Interstate 64 in this Midwestern city. Built in the mid 1960s, the bridge complex is about 1.5 miles in length comprised of equal part side by side elevated structure and over-under elevated structure. The mainline bridge is typically concrete slab on steel I-girder with reinforced concrete substructure units. The substructure units vary from single column bents to multi-frame column bents. The elevated ramps leading to or from the bridge complex vary from concrete slab on steel I-girder to continuous voided slab or box-girder spans. Given the variety of structural elements, this project, now in its tenth year, has provided a wealth of experience in seismic retrofit for the Central United States.]]></description>
      <pubDate>Mon, 20 Apr 2026 09:22:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235353</guid>
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    <item>
      <title>Replacement of the Merchants Bridge Deck Truss Spans</title>
      <link>https://trid.trb.org/View/2235314</link>
      <description><![CDATA[The Merchants Bridge is a two-track railroad structure that crosses the upper Mississippi River at Mile 183.2, just north of downtown St. Louis, Missouri. It is owned and operated by the Terminal Railroad Association (TRRA) of St. Louis, a local railroad with a history that dates back to 1889. The bridge itself was completed and opened to traffic in 1890. The Merchants Bridge is a key route for TRRA and its tenant lines. It is a critical link in the transcontinental railroad system. It affords access to industrial districts on both sides of the river and serves as a connection for numerous rail lines. Currently, the structure carries traffic consisting of approximately 35 trains a day and 40 million gross tons each year.]]></description>
      <pubDate>Thu, 26 Mar 2026 13:38:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2235314</guid>
    </item>
    <item>
      <title>Explaining the variation of bus stop Amenities: The case of St. Louis, MO, USA</title>
      <link>https://trid.trb.org/View/2647581</link>
      <description><![CDATA[Bus stops in the United States vary widely in the amenities they provide riders. Commonly, bus stops consist of a sign on a pole, although some feature sheltered structures, benches, ADA ramps, trash cans, and even art. Existing literature highlights the importance of bus stop amenities to protect riders and provide comfort while waiting for their bus. Emerging research indicates that bus stop amenities are not equitably distributed to members of disadvantaged communities, who often are also transit dependent. We explore the socio-economic factors and transit system characteristics associated with the distribution of bus stops and bus stop amenities at the block group level in the city of St. Louis, MO, a major United States city with a legacy of racial segregation. Using census data, ArcGIS, and linear regressions, we find that even though minority populations are positively correlated with overall bus stops, they are negatively correlated with stop amenities, particularly with shelters. We also find a positive relationship between bus stop amenities and jobs. Even though bus stops are usually overlooked given the tight budgets of transit agencies, the addition of amenities can protect riders and attract potential new users. Taking an equity perspective, we emphasize the need to understand and even out how transportation infrastructure is distributed among disadvantaged groups in order to address any transit and urban planning disparities.]]></description>
      <pubDate>Fri, 20 Mar 2026 17:00:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647581</guid>
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    <item>
      <title>Transportation System Modeling and Decision Support for Catastrophic Event Planning in the Central United States: A Case Study of St. Louis Area</title>
      <link>https://trid.trb.org/View/2263810</link>
      <description><![CDATA[Under earthquake impacts, the failure of transportation infrastructure not only hinders normal everyday activities, but also impairs the post-disaster response and recovery, resulting substantial socio-economic losses. This paper describes recent developments of the network loss analysis (NLA) module for transportation system functionality assessment at the Mid-America Earthquake (MAE) Center. Traffic assignment models are used to evaluate the travel delays on the transportation network. The network loss analysis module is demonstrated through a case study of the real-world road network in the seismically vulnerable St. Louis metropolitan area. The MAEViz NLA module is useful to evaluate system performance of transportation systems for emergency management. The results of traffic flow and travel delays provide useful information for emergency managers and relevant government agencies to make emergency response plans for ingress and egress of impacted area (e.g. disaster relief dispatch and evacuation), and to identify emergency routes and evaluate their performance under extreme events.]]></description>
      <pubDate>Mon, 09 Feb 2026 08:39:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2263810</guid>
    </item>
    <item>
      <title>Spatial and policy analysis of livability in the city of St. Louis, Missouri, USA</title>
      <link>https://trid.trb.org/View/2611189</link>
      <description><![CDATA[A livable city ensures safety, health, inclusivity, sustainability, housing, mobility, and opportunities for all. The Global Observatory of Healthy and Sustainable Cities (GOHSC) launched the 1000 Cities Challenge to assess urban health and sustainability globally. This study uses the GOHSC’s spatial and policy indicators to evaluate livability in St. Louis, Missouri. Using a mixed-methods approach, we analyzed the spatial distribution of built environment and transport features alongside planning and sustainability policies. Spatial indicators were derived from open data. Policy documents were coded for their governance level, alignment with evidence from healthy cities, and inclusion of measurable targets. Most residents (91.7%) lived in neighborhoods with optimal street intersection density (100 intersections/km2). However, only 2.8% lived in areas with optimal population density (5,700 people/km2). Just 26.3% lived near public transit, and 44.5% had access to large public open spaces below the GOHSC city averages (44.6% and 66%). While there was good coverage of policies, policy quality was low (31%), with most lacking measurable targets. The policy and spatial indicators enabled a comprehensive evaluation of livability. Future research should synthesize local and regional policies, supplement livability indicators with measures of environmental (in)justice within cities and utilize streetscape micro-scale data to deepen livability analysis.]]></description>
      <pubDate>Wed, 19 Nov 2025 17:09:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611189</guid>
    </item>
    <item>
      <title>Safe Routes to School in St. Louis &amp; Beyond</title>
      <link>https://trid.trb.org/View/2608502</link>
      <description><![CDATA[Since the passing of the Bipartisan Infrastructure Bill in 2021, high schools and nonprofits are now (re)eligible for Safe Routes to School (SRTS) funding. This capstone’s client, Trailnet, is an active transportation non-profit based in St. Louis, Missouri, where the capstone project will center its work. Trailnet has tasked this project with addressing three questions: (1) why there is a lack of programmatic funding in the St. Louis region (2) how current successful/engaged SRTS programs around the nation are operating and (3) how Trailnet could practically support local school districts. In pursuit of these questions, this capstone followed a three-prong approach. By conducting informational interviews with national SRTS practitioners, working with a local school district (Bayless), and researching funding evaluation criteria in the region, we were able to highlight both challenges and opportunities for kids walking and biking to school in St. Louis. Specifically, we address the challenges that resource-scarce school districts face in applying for national funding and the importance of building coalitions and having champions at the school level. To tackle these resource constraints, we propose the creation of a planning assistance fund and an administrative support fund, similar to those of Oregon, for communities that could be classified as “support priority”. The first will provide resources to help schools compile initial resources necessary to be competitive for national funding while the latter will help sustain schools with programming support upon receipt of grant money. Additionally, this capstone pursued an extensive evaluation of current funding criteria and made recommendations for updated priorities that highlight environmental and transportation justice considerations.]]></description>
      <pubDate>Fri, 07 Nov 2025 11:31:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608502</guid>
    </item>
    <item>
      <title>Earthquake Hazard Input for Loss Estimation Study: St. Louis Highway System</title>
      <link>https://trid.trb.org/View/2187897</link>
      <description><![CDATA[The long recurrence period and high consequence earthquakes events in the New Madrid Seismic Zone have caused some federal agencies (e.g., NEHRP, FHWA) to look at the more densely populated areas where higher seismic risk is present. This paper presents the data collection, interpretation, and analysis of the geotechnical information required for an earthquake loss estimation study in St. Louis metro area. The loss estimation study was limited to the highway transportation system, where only the major highways were considered. The project information was processed using a GIS, and the subsequent loss analysis was executed using the HAZUS-MH program.]]></description>
      <pubDate>Thu, 19 Dec 2024 11:44:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2187897</guid>
    </item>
    <item>
      <title>Advocating for transportation equity: A critical examination of paratransit service reductions in St. Louis and its impact on health and community social participation</title>
      <link>https://trid.trb.org/View/2434291</link>
      <description><![CDATA[Social participation is associated with better health, quality of life, physical activity, and engagement in community living and is thus an emerging health priority. Transportation plays an important role in facilitating social participation. The team recently reported in the Journal of Disability and Health that Missouri-dwelling adults aging with long-term physical disabilities who use paratransit services as their primary transportation mode are more likely to participate in social roles and activities outside the home compared to those who do not use paratransit. In March of 2023, the paratransit company Metro Call-A-Ride that serves St. Louis announced major scale backs to their coverage zones due in part to staffing shortages. This decision has been met with a formal complaint filed to the U.S. Department of Justice as well as protest from the St. Louis disability community and advocates. Thousands of individuals who relied on Call-A-Ride for their routine community outings-to work, grocery stores, or medical appointments, for example-have been affected by the cuts. In this commentary, the authors will summarize the media coverage this decision has received, including the perspectives of disability rights advocates and individuals who have been directly affected. The authors will then present an overview of their original research findings in the context of these recent events and a brief synthesis of existing literature on paratransit services in the U.S. The commentary will end with proposed policy, research, and programming solutions for St. Louis's Metro Call-A-Ride and public transportation at large.]]></description>
      <pubDate>Fri, 04 Oct 2024 13:51:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2434291</guid>
    </item>
    <item>
      <title>Dynamic Modeling of the Interaction between Urban Transportation and Urban Landuse Change</title>
      <link>https://trid.trb.org/View/2263470</link>
      <description><![CDATA[One major cause to urban sprawl can be attributed to the urban transportation system. The building of new highways and roads tends to bring about new traffic and thus reduces the expected increase in efficiency. In this model an effort has been made to model the mutual interaction between urban transportation system and the urban landuse pattern and its change with time. The major factor influencing the location of the middle-class population is the travel time to their places of interest and the state of the transportation facilities available for this travel. The impacts of transportation viz., environmental impact, social impact and economic impact have been considered while coming up with this model. An existing layout of transportation network and policies can be easily studied for their most likely impact in the region over a few decades under different economic scenarios to help envisage the pattern of future growth. Such a tool could be very useful in regional policy decision-making and transportation planning. This model has been applied as part of the LEAM model in the Peoria region, the results of which have been briefly discussed. An improved model is being applied in the greater St. Louis region.]]></description>
      <pubDate>Sat, 21 Sep 2024 15:11:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2263470</guid>
    </item>
    <item>
      <title>Hierarchical Classification—Regression (HiClassR) to Improve Incident Clearance Time Prediction</title>
      <link>https://trid.trb.org/View/2389983</link>
      <description><![CDATA[Incident clearance time prediction is a key task in Advanced Transportation Management and Advanced Traveler Information Systems, as it informs mitigation and response strategies adopted by transportation agencies. Incident clearance time prediction is not a trivial task given that the duration of an incident is influenced by various factors, some of which are difficult to measure or not measured at all. Such constraints in the data might limit the accuracy of the models developed for predicting clearance time. Over the past decades, researchers have employed various statistical methods and machine learning approaches to overcome these limitations and improve the accuracy of the incident clearance time prediction models. While these efforts have successfully improved the overall accuracy of models, very few studies have focused on assessing and improving the generalization ability of incident clearance time prediction models. This paper proposes the hierarchical classification-regression (HiClassR) framework to improve the predictive performance of common machine-learning algorithms in predicting incident clearance time. HiClassR is a framework for developing a bi-level model in which the incidents are first assigned to an incident class; then, a class-specific model estimates the incident clearance time. While the HiClassR method is expected to improve error measures such as the RMSE over the entire dataset, it is also expected to improve the model’s generalization ability across various incident scenarios. In a case study, the HiClassR method was applied to six conventional predictive methods to develop incident clearance time prediction models for St. Louis, MO, USA. The case study results indicate that the HiClassR model consistently outperforms the conventional base models and effectively generalizes the overall prediction power of the model to various incident categories of different conventional predictive methods. On average, the preferred HiClassR model reduced the RMSE from 22.7 to 17.6 min for the random forest model, from 22.5 to 19 min for Bayesian regularization neural networks, from 23.7 to 16.9 min for support vector machines, from 25.2 to 21.1 min for K-nearest neighbors, from 24.5 to 19.7 min for XGB, and from 23.9 to 18.3 min for neural networks.]]></description>
      <pubDate>Thu, 22 Aug 2024 15:11:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389983</guid>
    </item>
    <item>
      <title>Community Public Mobility Using On-Demand, Low-Speed Electric Vehicles: A Case Study in Downtown St. Louis, Missouri</title>
      <link>https://trid.trb.org/View/2410527</link>
      <description><![CDATA[Legacy fixed-route transit systems designed to serve commuters struggle to provide efficient and effective service for short neighborhood trips and for population groups unable to access and egress transit stops using active modes (e.g., elderly, disabled). Neighborhood on-demand transit (ODT) services using low-speed electric vehicles (LSEVs) are an innovative technological solution that could help fill this gap in service (e.g., short, high-frequency trips) for diverse populations and trip types. This study evaluated user characteristics and travel behavior for a neighborhood ODT service (using LSEVs) in downtown St. Louis, MO, using responses from a community survey (n?=?244), ridership data, and vehicle trajectory information. A comparative analysis between neighborhood ODT, fixed-route transit, and transportation network companies (TNCs) was also conducted from the perspectives of total travel time, cost, and greenhouse gas emissions. Ultimately, the goal of the analysis was to motivate and inform holistic public mobility systems where different services are optimized to meet specific community needs. Findings indicate that the neighborhood ODT was effective at reaching diverse populations (elderly [20%], lower income [27%], and households with limited access to private vehicles [34%]). ODT reduced total travel time by 32% compared with fixed-route transit, produced 2.4 to 4.3 times less greenhouse gas emissions per passenger mile (compared with transit and TNCs), and was more affordable (free to users) than alternative options ($1 for transit, $10 to $12 for TNCs). Overall satisfaction rates were high, with 80% of respondents rating the service a 4 or 5 out of 5.]]></description>
      <pubDate>Fri, 02 Aug 2024 08:43:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2410527</guid>
    </item>
    <item>
      <title>Identification of a Response and Rescue Network for the St. Louis Region</title>
      <link>https://trid.trb.org/View/2397665</link>
      <description><![CDATA[Emergency preparedness and response are crucial for mitigating the impact of natural disasters such as earthquakes. The St. Louis metropolitan region is vulnerable to earthquakes in the New Madrid and Wabash Valley Seismic Zones. This study focuses on understanding and addressing transportation impacts of an earthquake in the St. Louis region. An online survey conducted across eight counties in the St. Louis region gathered data on citizen preferences, travel patterns, and vehicle usage during an evacuation. The research team employed transportation simulation tools, including macroscopic and mesoscopic approaches, to assess regional traffic impacts. The research evaluated the effects of a magnitude 6.7 earthquake, considering infrastructure damage estimates from the United States Geological Survey (USGS) ShakeCast model. Performance measures like average vehicle speed and operating speed-to-speed limit ratio were gathered from the simulation to determine congestion across the road network. Twelve evacuation scenarios were assessed using simulation. The scenarios varied based on the level of damage to the road network, evacuation demand, and timing of the earthquake. Results showed that morning earthquakes resulted in the worst traffic impacts. Mesoscopic models confirmed severe congestion on MO 100 and identified bottlenecks on I-170 and US 67. A tabletop exercise was conducted with key emergency response stakeholders in the St. Louis region to better understand coordination and communication needs during an earthquake response. This study aims to equip stakeholders with tools for effective response, aiding emergency responders, urban planners, and policymakers in minimizing the impact of earthquakes.]]></description>
      <pubDate>Wed, 03 Jul 2024 17:13:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2397665</guid>
    </item>
    <item>
      <title>Extracting driving volatility from connected vehicle data in exploring Space-Time relationships with crashes in the city of Saint Louis</title>
      <link>https://trid.trb.org/View/2349829</link>
      <description><![CDATA[The analysis of factors that influence the occurrence of roadway crashes within a specified locality have historically been reliant on the assessment of physical infrastructure, historical crash frequency, environmental factors and driver characteristics. The consensus over the years has been drawn to the idea that human factors, specifically regarding driving behaviors, account for the majority of crash outcomes on roadways. With the emergence of connected vehicle data in the last few years, the capacity to analyze real time driving behavior has become a possibility for safety analysts. Driving volatility has emerged as a valuable proxy for driving behavior and indicator of safety. In this study, evidence of the spatial relationship between driving volatility and historical crash hotspots is uncovered. Utilizing an entropy-based analysis, this study discovered generally strong positive spatial relationships between locations of volatile driving events and historical crashes, with R2 values ranging from 0.015 to 0.970 and a mean of 0.612 for hard accelerations, and 0.048 to 0.996 and a mean of 0.678 for hard decelerations. Including temporal context presented insights showing that the relationships are significant for over 60 % of the coverage area usually between the hours of 7 am to 7 pm, with average R2 values of 0.594 for hard accelerations, and 0.629 for hard decelerations.]]></description>
      <pubDate>Thu, 04 Apr 2024 16:58:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2349829</guid>
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