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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Investigation of hit-and-run crash severity through explainable machine learning</title>
      <link>https://trid.trb.org/View/2633412</link>
      <description><![CDATA[This study investigates factors influencing the severity of hit-and-run crashes using explainable machine learning techniques. A 5-year dataset from Victoria, Australia, was analyzed with CatBoost algorithms and SHAP values to highlight key severity factors. The presence of police at the crash scene emerges as the most critical determinant, underscoring the importance of law enforcement in mitigating severe crash outcomes. Crashes involving passenger vehicles and those on weekends were also linked to higher severity. The number of vehicles and total persons involved showed non-linear effects, with both low and high values associated with lower severity. Alcohol-related crashes and speed limit zones, while moderately important, revealed complex roles in severity prediction. These novel findings offer valuable insights for targeted interventions and policy-making to mitigate the impact of severe hit-and-run crashes and enhance road safety. In this way, policymakers can develop more effective strategies to reduce the impact of these phenomena.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:56:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633412</guid>
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    <item>
      <title>Hydrogen as an aviation fuel: Safety concerns and mitigation strategies</title>
      <link>https://trid.trb.org/View/2628244</link>
      <description><![CDATA[The aviation industry is gradually transitioning towards net zero carbon emissions by addressing its primary source of emissions: aircraft fuel. Among alternative fuels, hydrogen has emerged as a promising solution, offering strong potential to support net zero targets while remaining viable for use in aircraft engines. However, it is imperative to understand its safety challenges and mitigation strategies to ensure this transition occurs safely. Despite growing research on hydrogen in aviation, few studies have focused specifically on hydrogen safety. This study addresses that gap by systematically synthesising both risks and mitigation strategies from publications spanning 2015, when hydrogen safety research began to accelerate, through to 2025, providing a comprehensive overview of current knowledge on hydrogen fuel safety in aviation. Our findings highlight key risks associated with hydrogen storage, leakage, flammability, and material compatibility, while also noting emerging strategies in hydrogen storage and handling. This includes advanced leak detection systems to manage leakage risks, boil off recovery technologies to address hydrogen loss during refuelling, improved insulation for cryogenic tanks to reduce heat transfer, and pressure build up. Reviewing these areas clarifies what is known, identifies where further work is needed, and provides practical recommendations for academics and industry stakeholders. We recommend future research to refine risk assessment models to account for hazards such as boil off gas venting, leakage during refuelling, and the spatial and operational interactions that arise with hydrogen and kerosene fuelled aircraft operate in proximity, including their implications for safety exclusion zones and ground handling.]]></description>
      <pubDate>Thu, 26 Feb 2026 14:51:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628244</guid>
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    <item>
      <title>Systematic analysis of vulnerability and resilience in road networks: A study of critical components and recent trends</title>
      <link>https://trid.trb.org/View/2627403</link>
      <description><![CDATA[The systematic literature review conducted addresses vulnerability in road networks, highlighting the relevance of this topic for urban mobility and the economy. The main findings of this review reveal that vulnerability is directly associated with concepts such as resilience, robustness, and reliability of road networks. The analyses indicate that vulnerability is not limited to physical failures in infrastructures but also includes disruptive events that impact the accessibility and recovery capacity of these networks. Through a bibliometric analysis of over 12,000 documents from three databases (SpringerLink, SCOPUS, and TRID), four primary keywords were identified: vulnerability, resilience, robustness, and reliability. For instance, the vulnerability of road networks was predominantly related to reduced accessibility in adverse event situations, underscoring the importance of mitigation and adaptation strategies. Resilience was frequently associated with the ability of networks to maintain functionality following disruptive events, while robustness was linked to the structural resistance of road infrastructure. Reliability, on the other hand, addressed the predictability of the transportation system, focusing on the consistency of travel times and the overall performance of the network. One of the central findings of the review is the increasing importance of considering vulnerability in future studies, given its connection to accessibility and the resilience of networks. This becomes crucial for urban planning and the formulation of public policies that promote sustainable and safe mobility. Furthermore, the study suggests that new approaches, such as the use of intelligent technologies and predictive analysis, may enhance vulnerability management and strengthen the resilience of road networks, contributing to a more robust and efficient infrastructure. Considering vulnerability is essential for developing road networks that are more resilient and capable of withstanding adverse events, ensuring effective mobility and minimizing economic impacts.]]></description>
      <pubDate>Thu, 26 Feb 2026 09:14:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2627403</guid>
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    <item>
      <title>Accomplishing the airport’s safety performance targets: A case study</title>
      <link>https://trid.trb.org/View/2627807</link>
      <description><![CDATA[This paper examines the application of Safety Performance Management (SPM) as part of the Safety Management System (SMS) at the case-study airport, over the period from 2014 to 2024. An SMS is a structured and proactive framework for managing aviation safety risks, aligned with international regulations. Central to effective SMS is the monitoring of Safety Performance Indicators (SPIs), which are used to assess whether safety objectives are being met. Each SPI includes a defined Safety Performance Target (SPT) and three alert thresholds that indicate abnormal trends and potential risks. At the case-study airport, two SPIs were monitored: Foreign Object Debris (FOD) presence and Wildlife occurrences. Monthly data were collected and analyzed over an eleven-year period. Results show that the achieved SPI values consistently remained below their respective targets, with no activation of alert thresholds. Even in challenging conditions, such as a temporary increase in wildlife activity in 2017, the airport maintained acceptable safety performance. These findings highlight the airport’s effective use of safety data, timely mitigation actions, and adherence to international safety standards, demonstrating a strong commitment to continuous improvement and proactive safety management.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2627807</guid>
    </item>
    <item>
      <title>Navigating Southeast Alaska with Interagency Collaboration</title>
      <link>https://trid.trb.org/View/2652032</link>
      <description><![CDATA[An illegally constructed cabin was found on Deer Mountain near Ketchikan in Southeast Alaska, disrupting the area's remote and ecologically pristine environment. Removing the cabin required cooperation between the U.S. Forest Service’s Law Enforcement and Investigations unit, the Ketchikan-Misty Fjords Ranger District, and Coast Guard Air Station Sitka. After months of planning and multiple weather-related cancellations, the mission was successfully completed on September 27, 2024. Along with removal of the cabin to the landfill in Ketchikan, the project included an additional goal of area familiarization for the two Coast Guard command members and the Forest Service Special Agent conducting the mission. Area familiarization is required for search-and-rescue readiness among servicemembers. The joint operation between the Forest Service and Air Station Sitka showcased the enhanced capabilities achieved through effective interagency collaboration.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652032</guid>
    </item>
    <item>
      <title>Establish Bridge Blast and Fire Damage Mitigation and Design Consideration</title>
      <link>https://trid.trb.org/View/2658327</link>
      <description><![CDATA[The research team will investigate fire and blast damage to bridges to develop design and mitigation strategies to enhance structural resilience. Fires and blasts from vehicular collisions, hazardous spills, and encampments beneath bridges pose significant threats to structural integrity and serviceability. To address these significant threats, the researchers will conduct full-scale experimental testing, by constructing a representative bridge, incorporating components aligned with Texas Department of Transportation's (TxDOT’s) practices. The researchers will explore mitigation strategies such as fire-resistant materials, protective coatings, and retrofitting methods to improve bridge performance. The research findings will be contributed to design guidelines addressing fire and blast hazards, reducing economic losses and service disruptions while ensuring bridges can better withstand extreme events.]]></description>
      <pubDate>Fri, 23 Jan 2026 16:09:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658327</guid>
    </item>
    <item>
      <title>Multi-Method Investigation of Pedestrian Safety Impacts of Right-Turn Lanes</title>
      <link>https://trid.trb.org/View/2651490</link>
      <description><![CDATA[The impact of dedicated right-turn lanes at signalized intersections on pedestrian safety has been relatively understudied, particularly for urban areas. The authors reviewed the research literature and pedestrian crash data analysis on right-turning vehicles, performed a field  study with both in-person observation and video recordings of sites with dedicated right-turn lanes and right-turn through lanes in Saint Paul, MN, and conducted an urban driving simulation study with participants driving and turning through both simulated lane types. The  results indicated that (1) lane count and traffic volume were significantly associated with risk to pedestrians from right-turning vehicles, (2) higher-volume intersections with dedicated right-turn lanes were riskier to pedestrians in terms of yielding rates, (3) the dedicated right turn lanes at lower-volume sites were safer than their right-turn through-lane counterparts in terms of yielding likelihood, (4) dedicated  right-turn lanes were associated with fewer high-speed turns, and (5) right-turn through lanes were associated with wider turns in both the  field data and simulation data. Taken together, intersections with dedicated right-turn lanes could pose some risk to pedestrians at higher volume intersections for stopping rates, while dedicated right-turn lanes were likely safer than right-turn through-lane counterparts at lower-volume intersections in terms of pedestrian safety. Future research should examine these findings with a wider range of traffic volumes and intersection types.]]></description>
      <pubDate>Fri, 09 Jan 2026 14:37:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2651490</guid>
    </item>
    <item>
      <title>Assessment of the stopping for right-turning large vehicles policy in Nanjing: Effectiveness and determinants</title>
      <link>https://trid.trb.org/View/2604565</link>
      <description><![CDATA[This study evaluates the effectiveness of Stopping for Right-Turning Large Vehicles Policy in Nanjing, designed to mitigate accidents attributed to blind spots and delayed braking of large trucks at intersections. Using high-resolution conflict data from four signalized intersections in Jiangning District, collected via unmanned aerial vehicles (UAVs) and roadside video, the research employs K-means clustering for conflict severity classification and binomial Logit regression to identify critical determinants. Results reveal the policy exhibited limited statistical significance in reducing severe conflicts (p > 0.05). Regression analysis quantified four critical determinants: absence of motorized/non-motorized segregation (OR=1.82, + 81.6% severity odds), elevated stop-line speeds (OR=1.32, + 31.9%), failure to yield (OR=2.45, + 145%), and crossing the street within the zebra crossing (OR=0.19, -81.0%). The analysis demonstrates that infrastructural deficiencies and behavioral non-compliance outweigh the policy's standalone impact. Based on these findings, the study proposes a holistic optimization framework integrating physical separation measures, enhanced signage, dynamic traffic signal adjustments, and data-driven enforcement strategies. Methodologically, this study innovatively combines unsupervised learning for conflict categorization, providing a scalable framework for evaluating urban traffic policies. This research underscores the necessity of multi-dimensional interventions-spanning infrastructure, enforcement, and public education-to achieve sustainable improvements in intersection safety. The findings offer actionable insights for policymakers to refine regulatory measures and enhance road safety in rapidly urbanizing environments.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604565</guid>
    </item>
    <item>
      <title>Investigating the Impact of Hazard Management Training on Young Novice Drivers’ Speed Management Skills and Vice Versa: A Driving Simulator Study</title>
      <link>https://trid.trb.org/View/2632060</link>
      <description><![CDATA[A lack of Hazard Management (HM) and Speed Management (SM) skills have been identified as a leading factor in young novice drivers’ road crash involvement. Despite the success of individual training programmes targeting these two skills, their generalizability to one another remains unclear. Hence, the aim of the present research was to address this limitation. Ninety young novice drivers were randomly divided into five different training groups, and following training, their HM and SM skills were assessed on two different occasions in a fixed-based driving simulator. The result revealed that HM and SM training improved their targeted skill; however, no generalization of training was evident. These findings emphasise the need for a new training technique that could improve these two critical road safety skills among young novice drivers.]]></description>
      <pubDate>Wed, 17 Dec 2025 09:40:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2632060</guid>
    </item>
    <item>
      <title>Barrier-Function-Enabled Control for Vessel Systems Under Dynamic Event-Triggered Protocols: The ADP Approach</title>
      <link>https://trid.trb.org/View/2598787</link>
      <description><![CDATA[In this paper, a constraint-aware suboptimal control scheme under adaptive dynamic programming (ADP) is investigated for nonlinear vessel systems characterized by dynamic event-triggering mechanisms (DETMs) and state constraints. A relaxed barrier function (RBF) is designed as a penalty term in the cost function to replace the inequality constraints, thus achieving constraints on the system state. By resorting to neural network (NN) approximation of the nonlinear dynamics, an optimal control framework is established via the dual method, combined with the Lagrange multipliers on the RBF. Within this framework, the Lagrangian multipliers are employed to balance the optimisation of control performance and state constraints. The convergence of value iteration algorithms is revealed through rigorously mathematical analysis. Furthermore, by using the Lyapunov stability theory, the desired observer gain is calculated via a set of matrix inequalities, and sufficient conditions for the relevant parameters and learning rates are derived such that the weight estimation errors of both the observer's NNs and the actor-critic NNs are ultimately bounded. Finally, simulations of both vessel systems and numerical examples are used to validate the effectiveness of the proposed method.]]></description>
      <pubDate>Mon, 08 Dec 2025 17:05:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2598787</guid>
    </item>
    <item>
      <title>Qualitative risk assessment for hydrogen and battery locomotives</title>
      <link>https://trid.trb.org/View/2598441</link>
      <description><![CDATA[Railway companies in Canada are examining the proposition of using hydrogen and battery locomotives for railyard switching, long-haul freight and passenger rail applications. A system-level risk assessment of hydrogen and battery locomotive (hydrail) technology was undertaken to categorize the hazards, list potential causes, effects, and consequences, provide recommended mitigations, and assess the risks. The methodology outlined herein is applicable and can be iteratively implemented in scenarios involving the planning of novel hydrogen and battery applications.]]></description>
      <pubDate>Mon, 24 Nov 2025 15:30:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2598441</guid>
    </item>
    <item>
      <title>Evaluation of Mitigation Strategies for High-Severity Derailments with Hazardous Materials</title>
      <link>https://trid.trb.org/View/2628304</link>
      <description><![CDATA[The transportation of hazardous materials (HAZMAT) by rail is a safe mode of transport and events with high-severity and/or high consequences from HAZMAT releases are rare. However, when high-profile events occur, they result in significant public pressure to modify the existing transportation practice and strengthen regulations to improve safety. The most recent example is the derailment on February 3, 2023, in East Palestine, Ohio that resulted in both a significant release HAZMAT and fires. As a result of the derailment, and subsequent National Transportation Safety Board and Federal Railroad Administration investigations, there is a renewed interest in evaluating and improving the safety of transporting HAZMAT in tank cars. The past regulatory responses to safety concerns for HAZMAT transport in railroad tank car safety have focused primarily on the tank car design and developed requirements for strengthening the tank shell. However, regulations that upgrade the tank structure are disruptive to the industry and expensive since it requires the replacement of a significant portion of the tank car fleet. This study investigates alternative mitigation strategies for high-severity railroad events involving HAZMAT transported in tank cars. In particular, the effects of the derailment speed on the release probability and consequences for tank car punctures are investigated. In addition, the effects of modifying the loading conditions to increase the outage volume (vapor space above the lading) are evaluated as a less costly alternative to increasing the tank car thickness to achieve an equivalent reduction in HAZMAT releases.]]></description>
      <pubDate>Mon, 24 Nov 2025 15:07:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628304</guid>
    </item>
    <item>
      <title>A Risk Assessment Method for Mid-Air Collisions in Urban Air Mobility Operations</title>
      <link>https://trid.trb.org/View/2591890</link>
      <description><![CDATA[This paper proposes a method to systematically assess the risk of mid-air collisions in Urban Air Mobility (UAM) operations, considering unique flight characteristics, mission requirements, and the evolving airspace dynamics. The method encompasses three pivotal phases: the encounter leading to collision, the loss of control post-collision, and the resulting harm to third parties on the ground or in the air. Instead of focusing solely on the collision risk, this method quantifies potential harms, introducing the metric of “fatalities per flight hour” akin to conventional aviation. Three main barriers, strategic mitigation, tactical mitigation, and collision avoidance, are modelled to calculate the probability of mid-air collisions. The gas model evaluates the probability of strategic mitigation failure, while an encounter timeline concept determines the probability of tactical mitigation failure. This paper concludes with Monte Carlo simulations validating the proposed model and a real-world case study demonstrating its applicability for regulators, operators, and stakeholders in ensuring the safety and efficiency of future UAM operations.]]></description>
      <pubDate>Fri, 07 Nov 2025 14:20:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2591890</guid>
    </item>
    <item>
      <title>Identification and Mitigation of Per- and Polyfluoroalkyl Substance Contamination in Highway Construction: Current and Future Practices</title>
      <link>https://trid.trb.org/View/2620581</link>
      <description><![CDATA[Per- and polyfluoroalkyl substances (PFAS) are persistent contaminants that pose risks to human health and the environment. PFASs can spread far from their sources, which include, but are not limited to, fire training areas, manufacturing sites, and landfills. PFAS regulation includes recently adopted federal mandates and a patchwork of state-level measures. This study analyzes state department of transportation (DOT) practices for identifying and mitigating PFAS contamination in highway construction and maintenance. We captured the state of the practice through a practitioner survey and case interviews. While 39% of responding states have formal or informal PFAS-related policies within state agencies, only 23% have such measures within their DOTs. In addition, 27% of responding states have PFAS action plans, but fewer than half of those were developed with DOT involvement. Most interviewees articulated concern about the cost of disposing PFAS-contaminated soil in landfills. Landfill restrictions would add transportation and disposal costs to many projects with unclear benefits for the environment. This study highlights the need for comprehensive guidance to aid DOTs in developing policies for PFAS impact mitigation. It identified states that have already adopted standard practices that could serve as models for such guidance. The results also highlight the need for interagency collaboration to address challenges in identifying and mitigating PFAS contamination. With recent (April 2024) designation of PFASs as hazardous substances, this paper uses state of the practice data and findings to inform concerns with respect to the potential impacts of this designation to DOT construction and maintenance operations.]]></description>
      <pubDate>Fri, 07 Nov 2025 11:30:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2620581</guid>
    </item>
    <item>
      <title>Identifying Hotspots in Natural Gas and Oil Pipeline Networks and Understanding Incident Risk Factors: An Integrated Spatial Analysis and Machine Learning Approach</title>
      <link>https://trid.trb.org/View/2578860</link>
      <description><![CDATA[Pipeline networks are crucial for transporting natural gas and oil but are vulnerable to significant safety and environmental risks. Previous studies have primarily focused on identifying overall incident causes without examining how spatial variations contribute to incident risk and have largely overlooked the differences in risk factors between natural gas and oil pipelines pipeline networks. A few studies often address broader geographic regions, such as states or counties, overlooking intricate spatial dynamics within pipeline networks. This study aims to bridge this gap by identifying hotspot areas within pipeline networks, areas with a high concentration of incidents compared to surroundings, using incident data from the Pipeline and Hazardous Materials Safety Administration and pipeline network data from the US Energy Information Administration. Leveraging spatial analysis techniques such as global Moran’s 𝐼, Getis-Ord Gi*, Anselin local Moran’s 𝐼, and spatiotemporal analysis, this study identified statistically significant pipeline hot spots, prominently in California and Ohio. After identifying hot spots using spatial analysis, different machine learning algorithms, such as random forest (RF), were employed to assess the factors contributing to these hotspots. The RF model achieved the highest accuracy, with 82% on the testing data for natural gas pipelines and 94% for oil pipelines, with standard deviations of 0.010 and 0.012, respectively, from K-fold cross validation to ensure robustness and accuracy. The analysis revealed distinct geographical variations driven by spatial and operational factors, such as pipeline intersections and operating pressure. Natural gas pipelines are more prone to operational errors, while oil pipelines are more susceptible to corrosion. This study enhances the detection of localized incident clusters, enabling more effective interventions compared to broader area-based analyses.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2578860</guid>
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