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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>
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      <link>https://trid.trb.org/</link>
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      <title>Polymer Concrete Overlay on SH 51 Bridge Deck</title>
      <link>https://trid.trb.org/View/2657966</link>
      <description><![CDATA[This report discusses Oklahoma's first polymer concrete bridge deck overlay. The objective of this project was to place a thin resinous overlay on a sound bridge deck and evaluate its performance over one year using various physical tests. The evaluation will show how well the overlay protects the reinforcing steel from corrosion due to deicing salts. The steps leading to the construction of the overlay are detailed as well as the actual placing of the overlay. The results of various physical tests are reported for both before and after the overlay. The protection of a bridge deck with a polymer concrete overlay appears to be a rather complicated procedure. Besides constraints of weather, temperature, aggregate and resin availability, machinery needs to be developed that can accurately and efficiently mix and lay polymer concrete.]]></description>
      <pubDate>Mon, 09 Mar 2026 11:53:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657966</guid>
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    <item>
      <title>Safety Assessment of New England Roadways During the COVID-19 Pandemic</title>
      <link>https://trid.trb.org/View/2669639</link>
      <description><![CDATA[Safety assessment of roadway facilities is a critical task to maintain the system operational efficiency of transportation infrastructure. The comprehensive stay-at-home orders implemented in response to the COVID-19 pandemic have resulted in massive reductions in traffic volumes, especially on major highways. Motorists have responded to these greatly reduced volumes by increasing their travel speeds; the result of this behavioral response has been an increase in the rate and incidence of fatal crashes. There is a clear need to analyze speeding during and after the duration of stay-at-home orders. In addition, the rate of severe injury and fatal crashes continued to remain high in 2021 and 2022, even when the traffic volume returned to the pre-pandemic condition. This project employed an innovative approach to use traditional data archived from permanent count stations, as well as new data sources (i.e., probe data) to develop models to better understand the impact of pandemic on New England roadways. Particularly, this research developed models to analyze speeding during and after COVID-19 stay-at-home orders in Maine and Connecticut. This research also developed models to better understand the impact of pandemic on crashes in 2021, and 2022, and explore if any factors other than speed, also impacted the increase in rate of severe and fatal crashes in years after the stay-at-home order in Maine.]]></description>
      <pubDate>Mon, 02 Mar 2026 13:24:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669639</guid>
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      <title>From neighborhoods to streetscapes: Pandemic-era shifts in built-environment effects on pedestrian mobility</title>
      <link>https://trid.trb.org/View/2631011</link>
      <description><![CDATA[Understanding how pedestrian behavior responds to disruptions is essential for not only for enhancing urban resilience and risk preparedness, but also for informing effective urban regeneration strategies. Addressing existing limitations in pedestrian mobility research, particularly regarding feature selection, data precision, and spatial scale, this study develops a pedestrian flow prediction framework driven by neighborhood-level, street-level, and temporal-weather datasets within Melbourne's Central Business District. By examining interactions and evolutionary trends between pedestrian mobility and the built environment across pre-pandemic, pandemic, and post-pandemic periods, our analysis highlights three key findings: (1) Deep neural networks demonstrated the highest predictive accuracy among seven tested machine learning models, particularly under unstable travel conditions. (2) A notable shift was observed in pedestrian mobility's reliance on built environment features, evolving from a pre-pandemic emphasis on neighborhood-scale attributes to a post-pandemic predominance of street-scale characteristics, accompanied by intensified cross-scale feature interactions. (3) The pandemic induced enduring changes in pedestrian mobility patterns and preferences, including reduced dependence on public transportation and heightened preference for greener, open, and walkable spaces. By integrating urban analytics, spatial adaptation, behavioral resilience, and mobility justice, this research provide empirical insights to advance more inclusive and future-oriented urban planning, resilient and spatial renewal strategies.]]></description>
      <pubDate>Wed, 18 Feb 2026 13:22:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2631011</guid>
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    <item>
      <title>LPI Implementation Guidelines in Phoenix, Arizona: A Data-Driven Approach</title>
      <link>https://trid.trb.org/View/2666573</link>
      <description><![CDATA[The City of Phoenix, Arizona, commissioned a project to develop data-driven, public-facing Leading Pedestrian Interval (LPI) implementation guidelines, informed by a literature review, crash analysis, and before/after study of pedestrian-vehicle interactions with and without an LPI.  The project was intended to address the issue of pedestrian safety and to understand where and when to most effectively implement countermeasures that help prevent pedestrian crashes, injuries, and fatalities. This article discusses the project and the resulting guidelines,]]></description>
      <pubDate>Tue, 17 Feb 2026 13:11:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666573</guid>
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    <item>
      <title>A Methodology of Quantifying Precipitation Exposure for Wet-Weather Collisions and Evaluating Effectiveness of Open-Grade Asphalt Concrete as a Countermeasure</title>
      <link>https://trid.trb.org/View/2628386</link>
      <description><![CDATA[Weather-related crashes represent a significant concern in roadway safety. Wet collisions have often resulted in injuries or fatalities, at a ratio higher than collisions that occur in dry roadway conditions. Therefore, it is of strong interest to identify and manage the locations where collisions are prone to happen under wet pavement surface or adverse weather conditions. This paper introduces a method to estimate precipitation exposure of roadway segments by linking weather station data to the collision database. Subsequently, the corresponding crash rate for a subject location is calculated based on the concept of conditional probability. The method is then applied to quantify and compare the wet collision rates of some study sites before and after pavement projects of installing Open Graded Asphalt Concrete (OGAC), a pavement countermeasure commonly adopted for wet collision reduction. The findings demonstrated that OGAC offered the reduction of wet collisions at a large fraction of the study sites.]]></description>
      <pubDate>Mon, 09 Feb 2026 15:58:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628386</guid>
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    <item>
      <title>Effects of Lime-Cement Soil Stabilization against Train Induced Ground Vibrations</title>
      <link>https://trid.trb.org/View/2200128</link>
      <description><![CDATA[At low frequencies (around 20 Hz) the maximum level of train-induced ground vibration is highly dependent on train weight as well as train speed. This limits the axle loads and speed allowable for train traffic. Stabilization of the soft soils under the track by for example lime-cement columns is one of the methods that can be used for reducing the level of vibrations. This method has been successfully adopted at Ledsgård, a site in south-western Sweden in order to solve the problem of extensive ground vibrations due to the passage of X2000 high-speed trains. Using result from measurements both before and after the countermeasure and a 3-D FEM model, the effectiveness of the method in mitigating train induced ground vibrations on soft soil is discussed in this paper.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:53:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2200128</guid>
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    <item>
      <title>Effectiveness of Automated Speed Enforcement in School Zones and Guidance for Continuous Usage in Georgia</title>
      <link>https://trid.trb.org/View/2663131</link>
      <description><![CDATA[One of the growing concerns for transportation agencies is speed management in school zones, as it is vital to children's safety. Automated Speed Enforcement (ASE) is one of the measures to address speed management concerns. As of January 2024, approximately 286 schools across Georgia were equipped with ASE cameras, aiming to improve traffic safety in school zones. This research project was carried out to quantitatively evaluate the effect of ASE on safety in school zones. A comprehensive crash analysis was performed to estimate Crash Modification Factors (CMFs) using two approaches: (1) a before-and-after study with the EB approach, only considering treated schools and (2) a before-and-after study using the comparison-group method. A speed study was performed to collect speed data at schools with and without ASE, estimate key parameters, determine the percentage of drivers who exceeded school zone speed limits, and perform relevant statistical tests to compare speed variance distributions and speed distributions. A road user survey was conducted, and responses were analyzed through descriptive statistics and cross-classification. The results of the crash study indicated that, after implementing ASE cameras, total crashes have been reduced by 10 percent and 9 percent within the school zones at on-system and off-system treated schools, respectively. Also, speeding-related crashes have been reduced by 35 percent and 54 percent at on-system and off-system schools, respectively. Overall, ASE was found to be effective in reducing total crashes and speeding-related crashes in school zones, resulting in CMFs below 1.0 across all scenarios considered in this study. The results of the speed study indicated that treated schools experienced lower speed variances, higher driver compliance, and lower mean, 50th percentile, and 85th percentile speeds than control schools. At treated schools, the percentage of drivers exceeding school zone speed limits by more than 10 mph was 36 percent lower compared to control schools. At a 95 percent confidence level, the observed speed variance and speed distribution curves at treated schools were significantly lower than that at control schools. In summary, ASE was found to be an effective enforcement practice for speed management, resulting in improved safety in school zones]]></description>
      <pubDate>Thu, 05 Feb 2026 09:18:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663131</guid>
    </item>
    <item>
      <title>Evaluation of the California Child Passenger Safety Initiative</title>
      <link>https://trid.trb.org/View/2635340</link>
      <description><![CDATA[Motor vehicle injuries are a leading cause of injury and fatality to children. Child restraint systems can reduce injury, and their use has been a long-time focus of policy and programmatic work. During this time, there has been a marked increase in the number of children restrained in vehicles and a steady decline in vehicle-related injuries and fatalities to children. However, data reveal that children of color, compared to white children, are at greater risk of injury in motor vehicle crashes. To address needs of “the children left behind” from safety advances, the California Child Passenger Safety Initiative (CPSI) was launched in 2002 for 18 months. The CPSI was an innovative program designed to increase use and decrease misuse of child restraint systems among the most vulnerable children in California; i.e., children of color and children living in poverty. The CPSI was designed to: increase use of child safety seats among families who use public medical services at selected sites; decrease the rate of child safety seat misuse among these families; and increase knowledge of the then-new California child passenger safety seat law. This study compared survey and observation data for two samples of families with children age six and younger: a pre-intervention sample, and a post-intervention sample. Although the results of this study were mixed, dramatic increases in the use of certain child restraints and decreases in the misuse of others were observed. Implications for program replication are discussed.]]></description>
      <pubDate>Sat, 31 Jan 2026 16:28:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635340</guid>
    </item>
    <item>
      <title>Treatment Effectiveness Evaluation of Mandatory Pre-Right-Turn Stops for Large Vehicles at Signalized Intersections: Combining Causal Inference with the Wasserstein Generative Adversarial Network with Gradient Penalty Method</title>
      <link>https://trid.trb.org/View/2663047</link>
      <description><![CDATA[In China, more than 30% of intersection traffic crashes are related to right-hand turns, with large vehicle crashes consistently being the most prevalent. Novel countermeasures termed mandatory pre-right-turn stops for large vehicles at signalized intersections were widely implemented. Understanding their effects is critical for improving road safety. Traditional statistical approaches are affected by confounding bias, and because of the problem of overfitting, causal machine learning methods often fail to produce accurate results in small sample size . To overcome these challenges, a novel treatment effect evaluation system that combines a causal inference method with a data generation method is proposed in this paper. The Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is used to generate additional control group data, thereby increasing the sample size. Findings demonstrate that the WGAN-GP-generated data closely match real data. The effects of countermeasures are evaluated using doubly robust estimation with neural networks (DR-NNs). This method effectively models nonlinear relationships between variables and addresses confounding bias. Both the combination of a right-turn stop sign for large vehicles and right-turn danger zones, and the right-turn stop sign alone, significantly reduce right-turn crashes, with crash modification factors (CMFs) of 0.53 and 0.56, respectively. The analysis of heterogeneous treatment effects indicates that the combination is less effective at skewed intersections, and intersections without bicycle lanes show higher CMFs for the right-turn stop sign alone. These results underscore the importance of bicycle lanes and highlight the need for improved implementation of right-turn danger zones at skewed intersections.]]></description>
      <pubDate>Fri, 30 Jan 2026 09:03:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663047</guid>
    </item>
    <item>
      <title>COVID crisis-aware maritime risk assessment: A Bayesian network analysis</title>
      <link>https://trid.trb.org/View/2623339</link>
      <description><![CDATA[Maritime transportation is a vital component of global trade, yet maritime accidents pose significant risks with far-reaching consequences, including human casualties, economic losses, and environmental damage. The high-risk nature of this sector calls for in-depth, data-driven analysis to enhance risk assessment and accident prevention. While traditional approaches such as probabilistic risk analysis have advanced the understanding of maritime safety, they often overlook the evolving nature of risk under global crises, such as the COVID-19 pandemic (2020), the Ever Given blockage in the Suez Canal (March 2021), ongoing geopolitical conflicts (e.g., Russia-Ukraine since 2022), and the recent Red Sea crisis (2024). To overcome this critical research gap, this study proposes a crisis-aware maritime risk assessment framework based on Bayesian Network (BN), operationalised through a Tree-Augmented Naïve Bayes (TAN) model, using the COVID-19 pandemic as a case study. By analysing maritime accident patterns before and after the pandemic, the model reveals shifts in accident dynamics and emerging risk factors. The BN approach enables objective, interpretable analysis of how underlying causes and safety interventions have evolved in response to the crisis. Additionally, this study indirectly assesses the effectiveness of safety measures implemented during the pandemic and highlights areas for improvement to enhance future resilience. The findings provide actionable insights for policymakers, regulators, and industry stakeholders, supporting the development of more adaptive and robust maritime safety strategies to address future global disruptions.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623339</guid>
    </item>
    <item>
      <title>Oakland Chinatown Pedestrian Scramble: An Evaluation</title>
      <link>https://trid.trb.org/View/2628401</link>
      <description><![CDATA[In 2002, the City of Oakland, California implemented a scramble signal, at the intersection of 8th Street and Webster Street. Scrambles are a type of traffic signal that give pedestrians exclusive access to an intersection by stopping vehicular traffic on all approaches, allowing pedestrians to cross diagonally or conventionally. The primary objective of this evaluation was to determine whether the installation of the pedestrian scramble at this location increased pedestrian safety. An analysis was conducted of pedestrian-vehicle conflicts and pedestrian violations occurring at the intersection before and after the signal was modified, and pedestrians were surveyed to ascertain public attitude toward and comprehension of the change. The modification to scramble signal phasing at the intersection resulted in a statistically significant decrease in conflicts between pedestrians and vehicles, and a statistically significant increase in pedestrian violations. In general, pedestrians understood the change in the way the intersection operated, and were accepting of the change to scramble signalization. These results suggest that the scramble has been effective overall in improving safety conditions at the site. The increased number of violations occurring despite decreased conflicts is in part due to a proportion of pedestrians who cross illegally on the "safe side" crosswalk (i.e. the crosswalk parallel to moving traffic where there are no opportunities for conflicts). It is important that the scramble signal be monitored over time in order to quantify the extent to which reduced vehicle-pedestrian conflicts associated with the scramble translate into measurable reductions in pedestrian injuries and fatalities.]]></description>
      <pubDate>Sat, 03 Jan 2026 17:07:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628401</guid>
    </item>
    <item>
      <title>Review of City-Wide 30 km/h Speed Limit Benefits in Europe</title>
      <link>https://trid.trb.org/View/2643342</link>
      <description><![CDATA[To date, more and more European cities are systematically working to expand the proportion of their street network with a speed limit of 30 km/h. This paper endeavored to assess the effectiveness of city-wide 30 km/h speed limits in Europe. In an effort to condense research outputs, a quantitative approach along with qualitative assessments were implemented. This study described the changes in safety, environment, energy, traffic, livability, and health before and after the phased implementation of city-wide 30 km/h speed limits. The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Results from 40 different cities across Europe, including Brussels, Paris, and Zurich, indicated that reductions in speed limits improved road safety by decreasing the likelihood of crash risk and the severity of crashes that do occur. On average, the implementation of 30 km/h speed limits in European cities demonstrated a 23%, 37%, and 38% reduction in road crashes, fatalities, and injuries, respectively. Lower speed limits also yielded environmental benefits, with emissions decreasing on average by 18%, noise pollution levels by 2.5 dB, and fuel consumption by 7%, indicating enhanced fuel efficiency and reduced environmental impact. Encouraging citizens to embrace walking, cycling and utilizing public transit services can further contribute to a safer and environmentally sustainable urban environment.]]></description>
      <pubDate>Tue, 30 Dec 2025 17:10:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643342</guid>
    </item>
    <item>
      <title>Can speed cameras make streets safer? Quasi-experimental evidence from New York City</title>
      <link>https://trid.trb.org/View/2642313</link>
      <description><![CDATA[Each year, approximately 40,000 people die in vehicle collisions in the United States, generating $340 billion in economic costs. To make roads safer without expanding police contact, many cities have turned to automated traffic enforcement, cameras that detect and fine speeding motorists. Does automated enforcement reduce vehicle collisions and injuries? Many previous studies are limited to correlational evidence. By contrast, this study estimates the causal effect of automated enforcement on road safety in a difference-in-differences design. We exploit the staggered rollout of 2,000 speed cameras across New York City between 2014 and 2023, combining data on 700,000 collisions and 200,000 injuries with data on 18 million tickets issued. We find that cameras reduce collisions and injuries by 5 and 2.5% per month on average, respectively. Cumulatively, over the seven months following their introduction, collisions declined by 30% and injuries by 16%.]]></description>
      <pubDate>Tue, 30 Dec 2025 08:57:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642313</guid>
    </item>
    <item>
      <title>Influence of Operations Strategies on Third Performance Management Rulemaking (PM3) and Other Travel Time-Based Measures Primer Part Two—Nonrecurring Congestion Strategies</title>
      <link>https://trid.trb.org/View/2636026</link>
      <description><![CDATA[The purpose of this Primer is to apply an evaluation methodology previously developed by the Federal Highway Administration to six real-world case studies, and to provide examples for successful application of the methodology and highlight relationships to third performance management rulemaking measures. The methodology uses empirical data to track changes in travel times, as well as influencing factors: incidents, weather, and demand. The six case studies include two that address incident management; three that address adverse environmental events (snow and ice storms, dust storms, and rain); and one that addresses work zone management. Where indicated, traffic modeling was used to control for large variations in the influencing factors. Application of the methodology to six case studies revealed that, for the type of nonrecurring strategies implemented, little change in performance was observed using the empirical approach. The reason for this condition is that, by definition, nonrecurring strategies are narrowly focused on infrequent disruption events. In contrast, strategies that deal with recurring congestion will have an effect just about every day. As a result, travel time-based performance measures that accrue over an entire year may not be able to detect the infrequent effect of these strategies. Also, the effect of confounding by influencing factors for congestion—demand, crashes, and weather events—could mask the changes. To address this issue, modeling was used to hold these influencing factors constant for the before and after periods. Three of the case studies were used as examples and showed a highly positive net present value when the modeling results were obtained.]]></description>
      <pubDate>Mon, 22 Dec 2025 09:52:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636026</guid>
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      <title>Influence of Operations Strategies on Third Performance Management Rulemaking (PM3) and Other Travel Time-Based Measures Primer Part One Recurring Congestion Strategies</title>
      <link>https://trid.trb.org/View/2636025</link>
      <description><![CDATA[The purpose of this Primer is to: (1) summarize previous methods used to evaluate operations strategies, (2) document the recurring congestion operational strategy implementation evaluation methodology developed for the project, including the performance measures needed to characterize benefits and costs and how to relate to third performance management rule (PM3) measures; (3) report the results of the seven real-world evaluations conducted with the methodology; and (4) provide examples for successful application of the methodology and highlight their relationship to PM3 measures. The methodology uses empirical data to track changes in travel times and influencing factors: incidents, weather, and demand. Where indicated, traffic modeling is used to control large variations in the influencing factors. Application of the methodology to seven case studies revealed that six cases achieved a notable improvement in performance; in the seventh case, congestion in the “before” period was marginal, so little change was noted. Depending on the conditions of each case, the PM3 measures will not always track with traditional congestion mobility measures. In several instances, traditional measures showed a performance improvement, but no improvement manifested in the PM3 measures for two reasons: (1) the binary nature of the PM3 measure (reliable/not reliable); and (2) components of the PM3 metric changing at different rates from the before period to the after period (e.g., the 50th and 80th percentile travel times in the level of travel time reliability metric).]]></description>
      <pubDate>Mon, 22 Dec 2025 09:52:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636025</guid>
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