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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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    <item>
      <title>Analysis on the Technical Path and Engineering Application of Ship
     Carbon Capture</title>
      <link>https://trid.trb.org/View/2706273</link>
      <description><![CDATA[This study focuses on the engineering application and performance evaluation of                     shipboard carbon capture systems. A process combining amine absorption and                     membrane separation was constructed, and the combined process was applied to a                     typical 7000 TEU container ship. After sea trials, the average carbon dioxide                     capture efficiency achieved by the system exceeded 87%, and the power                     consumption was maintained within an acceptable range. The integrated system                     greatly improved the EEXI and CII index levels and verified its economic                     feasibility in the medium and high carbon price scenario. The payback period of                     the investment costs was reduced to five years. After port coordination tests,                     the operability of ship-shore carbon dioxide transfer was verified, which                     promoted future scalability. The engineering layout, energy recovery design, and                     operation data worked together to provide a practical solution for maritime                     decarbonization. This study provides a valuable technical reference for the                     implementation of the International Maritime Organization (IMO) carbon reduction                     strategy, and also lays a solid foundation for subsequent legislation and system                     standardization.]]></description>
      <pubDate>Tue, 02 Jun 2026 11:09:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706273</guid>
    </item>
    <item>
      <title>City street landscape strategy with the consideration of urban wind corridors for mitigating traffic-generated PM₂.₅ effect in pedestrian spaces</title>
      <link>https://trid.trb.org/View/2672016</link>
      <description><![CDATA[Urban wind corridors are proven to improve outdoor thermal environments and have been gradually applied to urban planning recently. However, they may also lead to pollutants flowing throughout cities. Additionally, traffic-related air pollution remains a significant issue in Taiwan. Therefore, this study proposes to create microscale air quality zoning by street landscape. A series of CFD simulations is executed to evaluate the impact of trees and shrubs on the traffic-generated fine particles (PM2.5) distribution in roadside pedestrian areas. The results show that strategic tree placement with denser spacing can control PM2.5 to be concentrated in roadway areas while simultaneously forming air quality zoning. Shrubs are effective at blocking pollution from roadways and retaining cleaner air within pedestrian spaces. In this study, optimally spaced trees achieved an impressive 88% reduction in PM2.5 concertation in pedestrian spaces, while shrubs improved by 30% compared to scenarios without green planting.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672016</guid>
    </item>
    <item>
      <title>Refined synergistic optimization control method for mitigating congestion near bottleneck via deep reinforcement learning in a connected environment</title>
      <link>https://trid.trb.org/View/2673150</link>
      <description><![CDATA[Traffic congestion near bottleneck areas poses a serious threat to the efficiency, safety, and sustainability of highways. Existing active control strategies primarily employ variable speed limits (VSL), ramp metering (RM), or a combination of both. However, VSL often faces the dilemma of overcontrol, leading to a decline in traffic efficiency. Moreover, there is still a lack of efficient approaches near the on-ramp bottleneck to synergize lane-level VSL (LVSL) and RM effectively. To address these gaps, this study proposes a refined synergistic optimization control (RSOC) method based on deep reinforcement learning in a connected environment. Firstly, the critical components of RSOC are defined, including a fine-grained lane-level spatial segmentation of the road near the on-ramp bottleneck to enable precise traffic state representation. A fusion action is constructed, incorporating the speed limit scheme of the continuous LVSL (CLVSL) control, the ramp metering rate of RM, and their synergistic control scheme. An integrated reward is developed to balance local efficiency and safety at the bottleneck with the overall system-wide travel time. Then, an actor-critic framework is adopted for the first time to dynamically and flexibly adjust combinations of RM and CLVSL with different control lengths in response to evolving spatio-temporal traffic dynamics. Next, the soft actor-critic (SAC) algorithm is used to train the actor and critic networks of the RSOC, leveraging its superior capability in handling continuous action spaces. Finally, the proposed RSOC method is validated using a real-world on-ramp bottleneck scenario from the US101-S highway, supported by a custom simulation platform that models the synergistic control environment. The experimental results indicate that the proposed RSOC method: (1) can significantly mitigate congestion waves in various scenarios, even in heavily congested lanes; (2) significantly reduces total travel time in both the overall area and the bottleneck area, while improving traffic safety; and (3) shows notable improvements in traffic safety and efficiency under scenarios with different penetration rates of connected automated vehicles.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673150</guid>
    </item>
    <item>
      <title>How to promote sustainable aviation fuel: Is flexibility beneficial to quota policies?</title>
      <link>https://trid.trb.org/View/2673134</link>
      <description><![CDATA[As sectoral emissions rebound post-COVID, decarbonizing aviation has become a pressing priority, and sustainable aviation fuel (SAF) is widely regarded as the most practical short- to medium-term option. To accelerate deployment, many jurisdictions have adopted SAF blending quotas, while some policies now allow flexible quotas by averaging SAF usage across multiple airports rather than meeting the quota at each airport individually. This paper evaluates the operational and network performance implications of such flexibility in a multi-airport, multi-airline setting. Using an analytical game-theoretic model that captures airline competition, economies of scale in SAF production, logistics, transportation costs, and airport-specific SAF co-benefits, the study finds that flexibility enhances network efficiency by lowering SAF costs, increasing total traffic, and facilitating SAF uptake. However, these gains are not uniform across the network: airports and airlines near SAF production facilities benefit the most, while remote or smaller airports may face declining traffic, especially under weak scale economies or strong local SAF incentives. Extensions with asymmetric market and plant locations reveal that mismatches between SAF production sites and demand centers can amplify disparities; in some cases, small airports located near these facilities act primarily as “quota-fulfillment tools” yet still see diminished activity. Furthermore, the Book-and-Claim mechanism maximizes system-wide efficiency by decoupling logistics, but concentrates co-benefits at the hub, depriving remote airports of local incentives. Overall, while flexibility supports cost-effective SAF adoption, it also risks aggravating regional inequalities, which highlights the need for targeted support and coordinated policy design to ensure a balanced and equitable transition.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673134</guid>
    </item>
    <item>
      <title>How does urban land use and transportation spatial configuration affect carbon exacerbation and mitigation?</title>
      <link>https://trid.trb.org/View/2664096</link>
      <description><![CDATA[Urban emissions remain a critical global challenge, yet the role of spatial planning in mitigation is poorly quantified. This study aims to clarify how urban form and transportation networks influence carbon emissions by introducing a new metric — the Bidirectional Carbon-Emission Discrepancy Coefficient (BCDC) — which captures the difference between ground-based and satellite-observed emissions to reveal spatial impacts. Focusing on the Wuhan Metropolitan Area, we combined a Bayesian-optimized LightGBM model with SHAP analysis to identify nonlinear effects and thresholds. We find that urban compactness improves emissions up to a threshold of 0.23, beyond which benefits diminish. A U-shaped relationship emerges between carbon efficiency and both ecological land share and average travel distance, indicating optimal ranges for mitigation. Spatial analysis shows distinct patterns: emission hotspots need targeted industrial relocation, while coldspots benefit most from expanding blue-green infrastructure (>30 %) and decentralizing transport networks (15–20 % centrality reduction). These results provide actionable, location-specific strategies for urban decarbonization. By linking carbon data with spatial analytics, this framework advances climate-responsive urban planning, offering a scalable toolkit for tailored, evidence-based interventions that move beyond one-size-fits-all approaches.]]></description>
      <pubDate>Thu, 28 May 2026 09:06:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664096</guid>
    </item>
    <item>
      <title>The Impact of Zero-Carbon Fuels on CO2 Emissions Reduction
          from the Long-Haul Heavy-Duty Truck Fleet in Mainland China</title>
      <link>https://trid.trb.org/View/2706184</link>
      <description><![CDATA[The decarbonization of heavy-duty trucks (HDTs) is a crucial path for China to                     achieve its “dual-carbon” goals and transition to decarbonized freight                     transport. Zero-carbon fuels are key alternatives to fossil fuels for these                     high-emission vehicles. This study develops an integrated scenario analysis                     framework to quantify the theoretical CO₂e emission trajectories of China’s                     long-haul HDT fleet from 2020 to 2060. Functioning as a macro-level stress test,                     the model derives theoretical equivalent stock from anticipated logistics                     turnover demand, integrating them with well-to-wheel (WTW) emission factors                     under six distinct policy stringencies (Projects 1 through 6), representing                     varying paces of fossil fuel vehicle phase-out. The results demonstrate that                     policy stringency primarily governs the timing and depth of emission reductions,                     while fuel technology defines the minimum achievable emission level.                     Three-dimensional visualization analysis reveals a nonlinear “emission cliff”                     under aggressive policies, marked by accelerated HDT fleet renewal and                     exponentially growing mitigation benefits. This cliff is more pronounced for the                     green hydrogen pathway and demonstrates its superior potential for deep                     decarbonization. In Project 1, CO₂e emissions reach a mid-term peak in 2035.                     Compared to the diesel baseline, the green hydrogen and green ammonia transition                     pathways reduce peak CO₂e emissions by 158 and 137 million tons, corresponding                     to reductions of 10.0% and 8.6%, respectively, under the modeled theoretical                     boundaries. In contrast, the aggressive Project 6 policy suppresses this peak,                     triggers the “cliff” effect much earlier, and achieves an extremely low                     stabilization level by 2040—15 years ahead of Project 1. This study provides a                     macro-theoretical quantitative decision-support tool for policymakers. It                     demonstrates that transparent and aggressive phase-out policies are essential to                     accelerate fleet turnover, trigger the “emission cliff,” and firmly cap total                     cumulative emissions.]]></description>
      <pubDate>Tue, 26 May 2026 17:03:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706184</guid>
    </item>
    <item>
      <title>Climate change and global energy transformation: The role of renewable energy and electric vehicles</title>
      <link>https://trid.trb.org/View/2668702</link>
      <description><![CDATA[The energy and transportation sectors are the primary sources of greenhouse gas emissions; studies have largely examined renewable energy (RE) and electric vehicles (EVs) as separate solutions rather than as interdependent technologies. This review addresses this gap by providing a holistic assessment of their combined role in climate change mitigation. Drawing on peer-reviewed literature and case studies (2018–2025), this synthesis analyzes how research addresses global trends, technological advancements (e.g., vehicle-to-grid (V2G) systems, AI-based grid management, and solid-state batteries), lifecycle emissions, infrastructure requirements, and policy landscapes. While existing studies highlight significant progress in RE and EV deployment, the literature also identifies critical barriers, including grid integration, charging infrastructure gaps, supply chain constraints for critical minerals, and fragmented policy environments. This review's primary contribution is a cross-sectoral synthesis of the literature that demonstrates the interdependence of clean energy and transport, addressing a gap where prior research has examined these technologies largely in isolation. The review synthesizes evidence showing that the integrated deployment of RE and EVs presents a viable, though challenging, pathway to achieving the Paris Agreement's 1.5 °C target. The study offers targeted recommendations to overcome these barriers and accelerate a low-carbon energy transition.]]></description>
      <pubDate>Tue, 26 May 2026 11:56:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2668702</guid>
    </item>
    <item>
      <title>Integration of Environmental Requirements into Contractor Consultations: Exchange of Feedback between the Project Owner and Project Manager on Asset Management Operations</title>
      <link>https://trid.trb.org/View/2668480</link>
      <description><![CDATA[In a context where environmental requirements are a key factor in the acceptability of road projects, setting sustainable development objectives is a major challenge for project owners (POs) and project managers (PMs), starting from the design phase but especially during the consultation phase with construction contractors. As part of pavement maintenance and renewal operations on operational motorways, it is crucial to reconcile the requirements of sustainable asset management with growing environmental concerns. There are multiple challenges: ensuring regulatory compliance, securing timelines and costs, but above all, making sure that the environmental measures adopted are clearly understood and effectively taken on board by the contractors that will perform the works. In this context, the preparation of the tender documents is a key phase: the project owner’s environmental commitments must be translated in a clear and practical way. The partnership between the project owner, which defines the project’s environmental commitments, and the project manager, which technically translates them into contractual provisions in the specifications, thus plays an essential role.]]></description>
      <pubDate>Tue, 26 May 2026 09:41:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2668480</guid>
    </item>
    <item>
      <title>Linking string stability and traffic hysteresis: implications for oscillation absorption in vehicle longitudinal control</title>
      <link>https://trid.trb.org/View/2667131</link>
      <description><![CDATA[While the fundamental mechanisms of traffic flow remain elusive—especially under non-steady or oscillatory conditions—existing research has shown that Automated Vehicles (AVs) have the potential to suppress traffic oscillations. However, this often depends on aggressive deceleration and large headways, raising concerns about real-world applicability. To address this gap, this study theoretically analyzes the relationship between traffic hysteresis and string stability in AV control laws. A concise condition is derived to determine the direction of traffic hysteresis, offering a practical indicator of control law stability. Based on this, we propose the Hysteretic Parameter Adaptation Framework (HyPAF), which converts time-invariant control laws into time-varying systems. HyPAF reduces oscillation propagation by slowing ego vehicle responses to upstream fluctuations, while constraining parameter adjustments within stability-preserving bounds. Simulation results demonstrate that the relationship identified in this study between traffic hysteresis and string stability depends solely on the control law, implying that time delays simultaneously influence both phenomena. Moreover, simulations confirm the theoretical findings and show that, under both periodic oscillations and real-world trajectories, HyPAF can significantly reduce oscillation amplitudes and reduces energy consumption, at the cost of a slight increase in risk that remains within acceptable safety margins. These findings offer new insights into the evolution of non-equilibrium traffic flow, provide a practical guideline for parameter tuning in vehicle control systems, and may offer a new perspective for understanding human driving behavior under non-steady conditions.]]></description>
      <pubDate>Tue, 26 May 2026 09:40:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2667131</guid>
    </item>
    <item>
      <title>Climate change: trends and their effect on seaport activity and infrastructure: insights from major ports of India</title>
      <link>https://trid.trb.org/View/2666407</link>
      <description><![CDATA[Seaborne transport plays a crucial role in local, national, and global economies, helping to shift manufacturing from regional to global levels. However, international trade is susceptible to the impacts of changing climate patterns. This paper examines how climate disruptions affect India’s international trade by analysing the seaport traffic of eight major Indian ports from 1982 to 2021. To that effect, using Principal Component Analysis, we create a climate index consisting of wind speed, temperature, relative humidity, and precipitation variables and we show that the index variables significantly impact port activities. Additionally, our analysis also accounts for variables such road and railway infrastructure, since this directly affects cargo flows, port traffic and regional incomes. Moreover, in the context of our analysis, we consider that robust road and rail infrastructure improves resilience against extreme weather events by ensuring better connectivity, quicker recovery, and sustained economic stability. We employ several econometric techniques, and diagnostic checks to draw empirical inferences. Moreover, the analysis distinguishes between east and west coast ports of India, given their markedly different climatic and economic conditions. India’s position as a climate change hotspot heightens the vulnerability of its ports. The methods and findings discussed here provide steps for policymakers to prioritise training, revise insurance policies, upgrade infrastructure, promote stakeholder collaboration, and adopt green solutions to mitigate climate impact.we]]></description>
      <pubDate>Tue, 26 May 2026 09:40:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666407</guid>
    </item>
    <item>
      <title>Sectoral contributions to CO2 emission reduction in Osaka City, Japan: Emphasis on transportation’s social and behavioral dimensions</title>
      <link>https://trid.trb.org/View/2694592</link>
      <description><![CDATA[This research provides an in-depth examination of CO2 emissions from construction, transportation, power generation, and manufacturing in Osaka City, Japan, aiming to identify tailored strategies for substantial emission reductions, with particular emphasis on transportation’s social and behavioral dimensions in a transit-oriented urban context. Utilizing a formula-based model (E = A × EF × [1 − R]), where E denotes emissions, A represents activity levels, EF indicates emission factors, and R reflects reduction factors, the authors incorporate sector-specific activity data and emission intensities. Projections for 2025 reveal power generation as the dominant contributor at ∼55%, followed by manufacturing at ∼32%, with transportation at ∼12% and construction at ∼1%. Despite its moderate absolute share, transportation exhibits high relative reduction potential through electrification and societal interventions (e.g., modal shifts, congestion pricing, and equity-focused incentives), driven by Osaka’s dense, transit-oriented urban structure that fosters public acceptance of sustainable modes. Four policy scenarios were analyzed: renewable energy expansion, transport electrification, industrial efficiency improvements, and a hybrid approach combining all three. The hybrid scenario, integrating moderate advancements across sectors, achieves a 24% reduction (∼4.13 million metric tons) by 2030, supporting Japan’s national 46% GHG reduction target (from 2013 levels) and Osaka’s local ambition of 50% reduction by 2030 (from 2013 levels) toward net-zero by 2050. This strategy balances economic costs, technological feasibility, and societal impacts, prioritizing cost-effective transport measures with co-benefits for public health, equity, and livability, offering a scalable framework for urban decarbonization. The findings emphasize the need for sector-specific policies, grid decarbonization, and public–private partnerships to support Osaka’s net-zero ambition by 2050. This methodology and its outcomes provide a blueprint for other industrialized cities pursuing rapid, cost-effective emission reductions.]]></description>
      <pubDate>Tue, 19 May 2026 15:12:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694592</guid>
    </item>
    <item>
      <title>Synergy of industrial wastes in eco-friendly, air-cured alkali activated pavement concrete composites: properties, embodied carbon and energy assessment and modelling</title>
      <link>https://trid.trb.org/View/2663612</link>
      <description><![CDATA[Eco-friendly, air-cured alkali-activated slag concretes (AASC) were developed using recycled concrete aggregate (RCA) and waste foundry sand (WFS) as partial replacements for natural aggregates. Alkali activation was achieved through a sodium silicate–sodium hydroxide solution with a controlled activator modulus of 1.25. Mechanical assessment indicated optimal performance of the mix (50% RCA, 20% WFS) achieved high compressive strength (over 65 MPa at 28 days), along with satisfactory split tensile strength, flexural strength, modulus of elasticity, density, and reduced water absorption, fulfilling rigid pavement requirements. Life Cycle Assessment (LCA) revealed reductions of approximately 76% in embodied carbon and 43% in embodied energy compared to similar Ordinary Portland Cement pavement concretes. Machine learning (ML) regression models were developed to predict compressive strength, highlighting the influence of RCA and WFS with Linear-regression achieving the premier accuracy. The results confirm that RCA-WFS-based AASC composites present a viable, high-performance, and low-carbon alternative for sustainable pavement applications.]]></description>
      <pubDate>Thu, 14 May 2026 17:04:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663612</guid>
    </item>
    <item>
      <title>NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning</title>
      <link>https://trid.trb.org/View/2663722</link>
      <description><![CDATA[The transportation sector accounts for nearly one-quarter of global greenhouse gas (GHG) emissions. Emerging technologies-such as eco-driving, connected vehicle control, and others-offer significant potential for emission reduction; however, officially validated, yet optimization-ready emission models are essential for guiding their design, deployment, and evaluation. The U.S. EPA’ Motor Vehicle Emission Simulator (MOVES) is the validated regulatory and industry standard for vehicle emissions in the U.S. Yet, its complexity, macroscopic focus, and high computational demands make it unsuitable and incompatible with control and optimization applications, and burdensome even for traditional analyses. Furthermore, its reliance on location-specific inputs limits its applicability beyond the U.S. As a result, researchers often resort to alternative models, leading to emission estimates that are neither comparable nor officially validated. To address this gap, we introduce NeuralMOVES, an open-source, lightweight surrogate model for CO₂ emissions with near-MOVES fidelity. NeuralMOVES transforms MOVES from a multi-software system requiring specialized expertise and hours of computation into a 2.4 MB Python package that runs in milliseconds and integrates seamlessly into optimization frameworks. Developed by reverse-engineering MOVES through over 200 million batch queries to generate a comprehensive microscopic emission dataset (MOVES_RE, 9.89 GB), NeuralMOVES uses machine learning to compress this dataset by over 4,000ˣ while enabling continuous, differentiable, and real-time emission estimation. An extensive validation shows a mean absolute percentage error of 6.013% across over two million test scenarios, each representing a complete driving trajectory evaluated under specific environmental and vehicle conditions. We demonstrate NeuralMOVES in a dynamic eco-driving case study, showing that it integrates seamlessly into optimization pipelines, leads to different trajectories than alternative models, and captures parameter sensitivities that alternative models overlook. NeuralMOVES enables regulatory-grade, microscopic emission modeling for emerging transportation technologies worldwide and is available at: https://github.com/edgar-rs/neuralMOVES.]]></description>
      <pubDate>Thu, 14 May 2026 17:04:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663722</guid>
    </item>
    <item>
      <title>A Description and Analysis of the FAA Onboard Oxygen Analysis System</title>
      <link>https://trid.trb.org/View/2691553</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) is planning a series of ground and flight tests with Airbus to prove the concept of a simplified fuel tank inerting system, which has been developed by the FAA. The FAA has also developed an onboard oxygen analysis system to measure the oxygen concentration in the aircraft fuel tank during the testing. To help ensure smooth integration and the safety of the testing, the FAA has documented the system description, interfaces, operation, and has performed a failure mode effects criticality analysis. This analysis attempts to identify the failure modes of each system component and assess the effects of these failures on the component, system, and aircraft. The analysis also applies a hazard category to each hazard as well as some hazard probability when it was deemed necessary by the author. Hazard controls are also listed. All relevant system information has been summarized to allow for the system to be properly integrated into the proposed flight test aircraft. The results of the analysis indicated that most failure modes had no effect on the aircraft or other secondary systems. The few hazards with potential aircraft effects have significant controls in place to reduce the likelihood of the hazard and mitigate any potential hazard exposure.]]></description>
      <pubDate>Mon, 04 May 2026 11:05:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691553</guid>
    </item>
    <item>
      <title>Climate-friendly mobility: A possibility for nurses?</title>
      <link>https://trid.trb.org/View/2659511</link>
      <description><![CDATA[Compact city strategies and public transport are important climate change mitigation solutions that may increase the availability of climate-friendly mobility but also the cost of living in the city. An in-depth understanding of housing choices and climate-friendly mobility is key for the potential of mitigation strategies. This study explores 28 nurses’ daily mobility and their climate-friendly possibilities in Oslo. For climate-friendly mobility, Oslo is a critical case offering both ambition and success but also incurring high costs of living in the city. Nurses are middle class; while they cannot work from home and have varied shift schedules. In the study, this position is used to explore whether climate-friendly mobility is for everyone. I use spatial capital as a concept to discuss how nurses balance climate-friendly mobility and car use. This exposes dilemmas of climate change mitigation solutions and how they are differently available to people. Nurses’ access to climate-friendly mobility, as well as their competence and appropriation, is shaped by personal residential choices and is structured by policy and economy. Thus, climate change mitigation solutions should consider diverse life situations and mobility aspects beyond mere access.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659511</guid>
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