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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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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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    <item>
      <title>Implementing the Safe System Approach for Speed Management in Utah</title>
      <link>https://trid.trb.org/View/2685460</link>
      <description><![CDATA[Speed management is central to reducing fatal and serious injury crashes. The Safe System Approach, an emerging roadway safety paradigm in the United States, recognizes human error and vulnerability and focuses on minimizing crash severity through coordinated policy, design, and operational strategies. This research examines how Safe System Approach principles can be applied to speed management, with a focus on identifying practical countermeasures and implementation strategies relevant to the Utah Department of Transportation (UDOT). A compendium of practice was conducted to evaluate speed management countermeasures and document how cities and state Departments of Transportation are implementing Safe System Approach-based strategies. Thirty-two countermeasures were identified, including policy-based programs, automated enforcement, and roadway design treatments such as road diets, roundabouts, curb extensions, and gateway features. Findings show that implementing multiple, coordinated strategies is more effective than isolated interventions. The use of high-quality, context-sensitive speed and safety data supports proactive alignment of speed limits, roadway design, and safety goals. Establishing a clear Safe System Approach vision, supported by available federal and state tools, provides agencies with clear guidance for implementation. Based on the results of this research, several recommendations were provided for UDOT, including continuing to implement countermeasures for speed management in speed limit setting policies, evaluating current policies related to speed safety cameras in the state, incorporating Safe System Approach practices in the Strategic Highway Safety Plan, creating a speed management action plan, and placing a strong emphasis on community education tied to speed management.]]></description>
      <pubDate>Fri, 08 May 2026 17:09:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685460</guid>
    </item>
    <item>
      <title>Developing Digital Tools to Enhance Visual Inspection of Bridges During Extreme Climate Events</title>
      <link>https://trid.trb.org/View/2580062</link>
      <description><![CDATA[Compared to the development of low carbon emission technologies such as EV, the adaptation of existing transport infrastructure to increase its ability to absorb and recover from the effects of climate change is relatively unexplored. Bridges form a critical link in our transport systems, and many have a design life exceeding 100 years. Therefore, they are one of the key climate-change relevant elements that needs to be considered when future proofing our transport networks. With substantial maintenance backlogs worldwide and limited budgets, the bridge management process is becoming increasingly critical to support connectivity across our regions. Existing bridge management systems have significant limitations. They often operate in isolation from other asset management tools and lack interoperability with geographical, societal, and climate-related data sets. These systems have limited capability to incorporate data from sensors, leaving engineering judgment as the primary decision-making factor within constrained time and financial resources. To address these challenges, it is essential to develop comprehensive bridge management systems that integrate with various data sources. This paper provides an overview of the current bridge management process in Northern Ireland and presents a number of interventions to improve the robustness of the decision-making process including enhanced interoperability with other data sources and improved inspector training using virtual reality.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580062</guid>
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    <item>
      <title>Hardening the Economical Acquisition of Intersection Data to Improve System Integrity</title>
      <link>https://trid.trb.org/View/2694451</link>
      <description><![CDATA[Modern traffic management systems increasingly depend on real-time Signal Phase and Timing (SPaT) data generated by Traffic Signal Controllers (TSCs) to support safety, mobility, and emerging connected-vehicle applications. The applications of SPaT outputs require timely and reliable access to such data from the traffic signal controllers. However, these controllers are safety-critical infrastructure and exposing them to external networks introduces significant cybersecurity and operational risks. Thus, there is a need for mechanisms that provide secure, low-latency access to SPaT data without compromising controller integrity. The information flow methods that are used traditionally for connected and automated vehicle (CAV) environments have several security weak points. There exists a need for new communication protocols through which new system implementation paradigms can be evaluated at higher levels of information security. Two previous Center for Connected and Automated Transportation (CCAT) projects addressed this need by developing and testing a hardware-enforced data diode architecture and device that enable strictly one-directional extraction of SPaT data from traffic signal cabinets. The system prevents any inbound communication to the controller while allowing real-time data dissemination over existing network paths, requiring no new communication infrastructure. The current study was motivated by the potential use of systems engineering and model-based design to reduce development complexity and cost. The Cubicon design methodology, a new graphical language that translates high-level system behavior into executable software, improving maintainability and architectural clarity, was adopted. The phase of the project implemented a lightweight communication protocol with differential SPaT updates to reduce bandwidth usage and improve scalability. Together, these contributions demonstrate a more secure, efficient, and cost-effective approach for extracting and disseminating SPaT data, supporting both current traffic operations and future connected transportation systems. The research product can have profound and far-reaching impacts. For the hundreds of thousands of signalized intersections that currently exist in the United States, the economical and secure acquisition of SPaT information facilitates critical traffic management functions including red-light violation warnings, signal priority, and trajectory planning.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694451</guid>
    </item>
    <item>
      <title>Coordinated thermal–energy management for battery energy storage systems in hybrid electric vehicles: Architecture, modeling, control strategies, and engineering validation</title>
      <link>https://trid.trb.org/View/2694632</link>
      <description><![CDATA[Hybrid electric vehicles (HEVs) can reduce fuel use and emissions, but coordinated thermal–energy management is increasingly constrained by the traction battery, whose feasibility depends on state-of-charge (SoC) bounds, temperature-dependent power capability, and charge acceptance under auxiliary thermal loads. Many studies still treat the thermal management system (TMS) and energy management system (EMS) separately, which weakens simultaneous achievement of fuel economy, emissions compliance, comfort, and storage durability under real-world variability. This review summarizes coordinated TMS–EMS strategies from a battery-energy-storage-centric perspective. Battery-relevant thermal paths and their interactions with power split and SoC regulation are first clarified, including links to power electronics, waste-heat utilization, and cabin HVAC or heat pumps that reshape recuperation effectiveness and operating margins. Representative control families are then compared in terms of constraint enforcement and deployability, covering rule-based supervision, optimization-based methods (DP and ECMS), receding-horizon MPC, and learning-based control. Finally, engineering gaps and research needs are discussed, including electro–thermal–ageing modeling across time scales, online computational budgeting, and validation through model-in-the-loop (MiL), software-in-the-loop (SiL), hardware-in-the-loop (HiL), and vehicle–cloud co-simulation. Storage-centric benchmarking and charging-aware thermal preconditioning are highlighted as practical directions.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694632</guid>
    </item>
    <item>
      <title>Understanding Human Error in Military Aviation Maintenance: The role of Performance Shaping Factors, Cognitive Workload and Error Orientation</title>
      <link>https://trid.trb.org/View/2664371</link>
      <description><![CDATA[Human error remains a major source of reliability and safety risk in aviation maintenance, particularly in military operations where task complexity and operational pressure are unavoidable. Despite continued advancements in technical reliability, the mechanisms through which working conditions and cognitive demands translate into maintenance error, remain insufficiently understood. In particular, the combined influence of systemic factors, cognitive workload, and individual differences has received limited empirical attention. This study examines the effect of Performance Shaping Factors (PSFs) on human error in military aviation maintenance, considering cognitive workload as a mediating mechanism and Error Orientation (EO) as a moderating factor. Survey data from 282 military aviation maintenance personnel were analyzed using structural equation modeling. The results show that adverse PSFs significantly increase both cognitive workload and the likelihood of maintenance error. Cognitive workload partially mediates this relationship, indicating that increased mental demand is a key pathway through which unfavorable system conditions degrade maintenance reliability. Error Orientation moderates both direct and indirect effects. Personnel with lower EO are more susceptible to workload-related error. These findings extend human reliability analysis by explaining when and why maintenance errors are most likely to occur. The results support integrated safety management strategies that combine system design improvements, workload control, and targeted personnel development to enhance reliability in high-risk aviation maintenance environments.]]></description>
      <pubDate>Fri, 01 May 2026 14:31:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664371</guid>
    </item>
    <item>
      <title>Electric bus system design reliable against stochastic power grid load shedding and uncertain charging efficiency</title>
      <link>https://trid.trb.org/View/2664356</link>
      <description><![CDATA[To develop sustainable and livable cities, public transit systems such as buses worldwide are undergoing rapid electrification. This introduces new challenges as external factors can influence the operation of an electric bus (eBus) system, leading to delays and disruptions. This study addresses multiple energy supply uncertainties, namely, power grid load shedding and charging efficiency uncertainty, and proposes a framework to simultaneously design a reliable eBus system and its charging schedule. The framework is modeled as a hybrid robust-stochastic mixed integer linear program, in which the power grid load shedding is modeled stochastically and the charging efficiency uncertainty using a robust formulation. Considering time-varying electricity prices, energy storage systems (ESS) are installed at the terminals to reduce costs and increase reliability. A case study is presented on a bus network of Delhi, India. The framework was able to account for multiple sources of energy supply uncertainty with a marginal cost increment from a deterministic design for the same network. The results indicated that charging efficiency uncertainty primarily requires changes to the charging infrastructure, whereas load shedding results in extensive changes in battery capacity of the eBus fleet. Benchmarking of eBus system designs revealed that the hybrid approach can deal with increasing uncertainty probability very effectively. This framework will help transit agencies cost-optimally design and schedule a reliable electric bus system against the threat of power grid load shedding and charging efficiency uncertainty.]]></description>
      <pubDate>Fri, 01 May 2026 14:31:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664356</guid>
    </item>
    <item>
      <title>Risk and damage assessment of ship-offshore wind turbine collisions under multi-source uncertainty</title>
      <link>https://trid.trb.org/View/2697588</link>
      <description><![CDATA[With the expansion of offshore wind farms into deeper waters, the increased density and number of turbines have elevated the collision risk between ships and offshore wind turbines. Traditional risk assessment methods, based on historical data and expert judgment, struggle to address the multi-source uncertainties involved. This study develops an integrated probability-consequence assessment framework for ship-offshore wind turbine collisions under multi-source uncertainty. A three-layer risk model incorporating human, ship-related, and environmental factors is developed using accident statistics and expert elicitation. The Fuzzy Analytic Hierarchy Process (FAHP) is employed to quantify the weights and occurrence probabilities of basic events, which are then used as prior probabilities in a Bayesian Network (BN) to estimate collision probability and identify key risk factors. Collision scenarios are simulated using an added-mass approach with an explicit dynamic finite element model of a jacket-type offshore wind turbine impacted by a 10,000 DWT bulk carrier. Results indicate an annual collision probability of 2.626 × 10−3 year−1 in the study area, with untimely lookout, navigation equipment failure, and high traffic density as the main contributors. The proposed framework provides engineering-relevant support for offshore wind farm risk control, traffic management, and collision-resistant design.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:39:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697588</guid>
    </item>
    <item>
      <title>Future directions for data-driven approaches in pipeline integrity management: Risk assessment, in-line inspection, and machine learning</title>
      <link>https://trid.trb.org/View/2664295</link>
      <description><![CDATA[Gas pipeline failure continues to be a serious hazard for people in the vicinity of gas pipelines, particularly given the increase in urban development and aging infrastructure. This study critically reviews the current state and potential of data-driven approaches in pipeline integrity management systems (PIMS) for most critical threats. In addition to a purely theoretical discussion, three illustrative case studies are used to highlight the main limitations in the following areas: a) third-party damage assessment, b) the quality of in-line-Inspection (ILI) data and c) machine learning-based external corrosion evaluation. A quantitative risk analysis was performed to analyze shortcomings in context of current prevention practices. Research gaps lie in the evaluation of probability of failure insufficiently dependent on the gas pipeline location but in practice on pipeline design. A new GIS-based, probabilistic approach was proposed to assess TPD using available environmental data. Secondly, published ILI data was analyzed, which reveals a large amount of corrosion detected over pipeline route, but low replicability from one ILI run to another - limiting usage in PIMS and data driven modelling. Thirdly, a hybrid support vector regression model was trained to predict external corrosion, but its performance proved unstable: prediction accuracy dropped by 27% during cross-validation, highlighting the practical risks of model overfitting. This study highlights the need for more robust, context-sensitive models and outlines potential advancements to improve pipeline safety and system reliability using data-driven strategies.]]></description>
      <pubDate>Thu, 30 Apr 2026 11:28:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664295</guid>
    </item>
    <item>
      <title>Resilience assessment and enhancement of urban transportation interdependent network under cascading failure</title>
      <link>https://trid.trb.org/View/2664296</link>
      <description><![CDATA[Urban transportation systems are essential for sustaining urban growth and ensuring efficient resource allocation. Existing studies primarily focus on evaluating network resilience after system disturbances, with insufficient attention paid to the response mechanisms during disturbances and the enhancement of resilience afterward. Therefore, we propose a cascading failure model that considers passenger transfer impedance, and design a recovery priority strategy for failed nodes to maximize the resilience of the urban transportation interdependent network (UTIN). Specifically, based on traffic sensing data, we construct a station-centric UTIN to assess structural resilience under various disruption scenarios and different transfer distances. By combining impedance function and flow redistribution, passenger behavior and node load update are considered. Additionally, the recovery priority strategy for failed nodes is discussed. The results indicate: 1) UTINs with longer transfer distances exhibit stronger resistance to risks. When considering impedance costs, the optimal transfer distance is 800 m. 2) During cascading failure propagation, optimizing flow distribution effectively lowers the critical capacity threshold required for system stability, thereby enhancing network resilience. 3) During the recovery phase, different recovery strategies exhibit significant differences in their effectiveness in restoring system resilience. The research findings provide valuable references for disaster prevention, emergency response, and post-disaster recovery in urban transportation systems.]]></description>
      <pubDate>Thu, 30 Apr 2026 11:28:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664296</guid>
    </item>
    <item>
      <title>Effect of Land Use Pattern on Bus Blockage Duration at Curb Side Bus Stops</title>
      <link>https://trid.trb.org/View/2581535</link>
      <description><![CDATA[A bus stop is a strategic location considering congestion and delay in an urban road network. The influence of a bus stop on the traffic stream is generally characterised by the average dwell time. However, dwell time alone cannot be a complete measure of the influence of a stopping bus on the traffic stream. The duration of the bus to decelerate and accelerate to the required stream speed needs to be taken into consideration. The bus blockage duration that takes these factors into consideration gives a better picture of the effect of a bus on the stream. Again, the dwell time is usually correlated to the number of boarding/alighting. However, the other factor that influence passenger behaviour is the activity around the vicinity of the bus stop. These activities influence the passenger behaviour and the bus frequency and are a good measure of a combination of these various factors. Thus, in this study, the various factors influencing bus stops are studied in detail based on bus arrivals, departures and dwell time data collected from 1651 buses along 11 bus stops in the Mumbai region. The land use activity near the bus stop and its influence on the bus blockage duration is the prime contribution of this paper.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581535</guid>
    </item>
    <item>
      <title>Exploring PageRank Algorithm and Voronoi Diagrams for Dynamic Network Partitions Facilitating Feedback Linearization-Based Control</title>
      <link>https://trid.trb.org/View/2581519</link>
      <description><![CDATA[This paper explores a novel approach to dividing a traffic region (network) into sub-regions for efficient traffic control among the areas. The macroscopic flow diagram (MFD) in each of these sub-regions, referred to as sub-MFD, can then be used to determine the macro-state of that sub-region and subsequently design controllers. The region division is based on the theory of complex networks. We exploit the inherent network characteristics through the PageRank centrality algorithm to identify the most significant nodes in the traffic network. We use these significant nodes as the seeds for a Voronoi diagram-based partitioning mechanism of the network. A feedback linearization-based controller is then presented, which controls the traffic flow between the sub-regions. A case study is performed for the Manhattan area in New York City to demonstrate the network partitioning approach; the control approach is demonstrated through a toy example containing two sub-regions.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581519</guid>
    </item>
    <item>
      <title>Empirical and Optimization-Based Solutions for Thermal Behavior of Newtonian Fluids in Rough Pipes</title>
      <link>https://trid.trb.org/View/2657931</link>
      <description><![CDATA[The increasing demand for alternative energy has driven the integration of geothermal operations into the oil and gas industry, presenting engineering challenges due to high formation temperatures in geothermal wells. Effective thermal management is crucial, as temperature fluctuations can affect drilling fluid properties and downhole equipment performance. This study tackles these challenges by using a flow loop with 2 7/8″ tubing to study thermal behavior under transient conditions. Additionally, the study develops an empirical equation to investigate how the friction coefficient varies with temperature by considering the changes of temperature over time. To achieve the best fit between the empirical equation and experimental data, three methodologies—the interior-point algorithm, minimax algorithm, and particle swarm optimization algorithm—were employed. The analysis demonstrated that all predicted values fell within a 90% confidence interval, confirming the model’s reliability and practical applicability in drilling operations. The absolute average percentage error for the applied methods was approximately 4%. The key findings of this study provide practical insights for geothermal and oil drilling operations by enabling improved management of time-dependent thermal effects in wellbore systems. The proposed model allows for reliable estimation of friction factor evolution using easily measurable dimensionless parameters such as Reynolds and Prandtl numbers, along with duration. This predictive capability supports more accurate evaluation of pressure losses and heat transfer behavior in dynamic flow environments. Overall, this study contributes to enhancing the simulation of thermal–fluid behavior, supporting industrial applications and advancing scientific understanding of transient thermal–fluid interactions.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657931</guid>
    </item>
    <item>
      <title>Towards Digital Twins: Technology and Challenges in Bridge Information Modeling (BIM)</title>
      <link>https://trid.trb.org/View/2640350</link>
      <description><![CDATA[The concept of the Digital Twin has recently gained prominence in construction projects, offering substantial improvements over traditional methodologies by mirroring real-world structures in a dynamic virtual model. Digital twins rely critically on the accuracy, reliability, and timely availability of data throughout the lifecycle of the infrastructure. Building Information Modeling (BIM) is an essential technology in bridge construction that supports the Digital Twin concept by enabling the creation of detailed 3D intelligent models. These models provide precise graphical and numerical representations of design drawings and enhance design quality, constructability, and collaborative efforts across various construction phases. However, applying these advanced technologies to real-world bridge projects presents numerous challenges. Bridge engineers often struggle to effectively utilize the extensive data generated by their structural models throughout the bridge’s lifecycle. Additionally, contractors and inspectors require access to a 3D model post-design phase, updated continually with information relevant to ongoing construction activities and inspections. This paper discusses the challenges and available technologies for generating, managing, and enriching the Bridge BIM model with intelligent information from design through the construction and inspection phases. It highlights the need to adapt current data exchange standards, such as Industry Foundation Classes (IFC), to suit bridge projects better, ensuring that BIM and Digital Twin technologies can be fully exploited to improve bridge infrastructure’s predictive maintenance and lifecycle management.]]></description>
      <pubDate>Tue, 28 Apr 2026 12:18:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640350</guid>
    </item>
    <item>
      <title>Towards Trustworthy Road Digital Twins: A State-of-the-Art Review</title>
      <link>https://trid.trb.org/View/2640346</link>
      <description><![CDATA[Digital twins have been recognized as a powerful tool for whole-life management of road infrastructure in an intelligent, sustainable, and resilient manner. On the way forward, however, the road infrastructure stakeholders are still faced with the challenge regarding how to ensure the digital twins work trustily. An untrustworthy digital twin would produce inaccurate information and decision-making, resulting in high financial costs, inefficient road management, and safety concerns. To address this challenge, this paper analyzes the current state of the digital twin paradigm and classifies the potential factors that will impact the trustworthiness of digital twins. The analysis and classification take into consideration the functionality layers of digital twins and the operational requirements in road infrastructure management. Accordingly, the practical approaches that can be adopted to resolve the identified trustworthiness issues are thoroughly reviewed and systematically integrated into a framework designed to ensure the appropriate and trustworthy use of a road digital twin. Specifically, the developed trustworthy framework is underpinned by three key pillars: precision, transparency, and cybersecurity. It is strongly envisioned that this developed framework will serve as valuable guidance for the design and construction of robust and trustworthy digital twins, helping mitigate risks and enhance the overall effectiveness of road infrastructure management.]]></description>
      <pubDate>Tue, 28 Apr 2026 12:18:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640346</guid>
    </item>
    <item>
      <title>Why cities struggle with sustainable urban logistics: Cognitive misalignment in municipal work systems</title>
      <link>https://trid.trb.org/View/2686813</link>
      <description><![CDATA[To meet urban sustainability goals city authorities need to understand and influence urban logistics in planning and operations, but this is difficult in practice. To explain these difficulties researchers have emphasized governance-level factors such as limited leadership attention and weak strategic direction. This study shows that they can also be understood at operational level, as misalignment between municipal work systems and the cognitive demands of understanding and influencing complex logistics ecosystems. A cognitive systems engineering perspective was used to structure interviews with 16 practitioners from four Norwegian city authorities. Participants described how work-system challenges related to operational strategy, coordination, and tools/data constrained staff’s ability to: (i) develop understanding of logistics systems; (ii) anticipate the effects of municipal measures on commercial behavior; (iii) identify levers for influence across distributed actors and constraints; (iv) justify measures and learn from outcomes; (v) plan holistically; and (vi) build learning and develop processes. Practitioner accounts included ways to adapt to these constraints, including making urban logistics challenges more visible for decision-makers, organizing informal coordination forums, improvising information-gathering on ongoing logistics issues, and experimenting with dynamic regulatory tools. Such adaptations can act as “design seeds” for strengthening municipal work systems. The findings suggest that formal Sustainable Urban Logistics Plans should not presuppose municipal work systems that support understanding and learning on urban logistics by staff. Strengthening coordination, tools, metrics, feedback, competence and other elements of strategic capacity at operative level could be as important as high-level political commitment and strategy in accounting for urban logistics in sustainability.]]></description>
      <pubDate>Tue, 28 Apr 2026 11:18:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686813</guid>
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