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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Implementation of Seal Coat Project Selection Guidelines</title>
      <link>https://trid.trb.org/View/2727313</link>
      <description><![CDATA[The Performing Agency shall assist the Receiving Agency with implementing the guidelines for seal coat project selection and the draft ball penetration test method developed in research project 0-7106 “Quantify Maximum Accumulated Seal Coat Layers for Stability“. The Performing Agency shall then use the findings and data generated from this implementation project to develop and teach implementation workshops for the Receiving Agency.]]></description>
      <pubDate>Fri, 10 Jul 2026 12:40:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727313</guid>
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    <item>
      <title>Self-sensing evaluation of carbon nanotube-reinforced ultra-high-performance alkali-activated concrete for automated road monitoring: Verification using road accelerated loading equipment</title>
      <link>https://trid.trb.org/View/2687290</link>
      <description><![CDATA[To address the growing demand for automated road monitoring, the carbon nanotube (CNT) reinforced ultra-high-performance alkali-activated concrete (UHPAAC) was developed in this study. The microstructure was analyzed by scanning electron microscopy (SEM) coupled with X-ray energy dispersive spectrum (EDS) and mercury intrusion porosimetry (MIP) test. The workability, setting time and strength were evaluated through flow table, Vicat, compressive and flexural tests. The electrical properties were measured using a data acquisition and recording system (DARS). A novel evaluation framework was established to evaluate the piezoresistive behavior by a universal testing machine coupled with DARS. The piezoresistive performance was verified using road accelerated loading equipment. Results show that the tubular carbon nanotubes are mainly dispersed within the hydration products (C-A-S-H, N-A-S-H, C-(N)-A-S-H), which constitute the matrix of UHPAAC along with irregular shaped aggregates, rod shaped steel fibers, and spherical unreacted particles. An optimal CNT content of 0.3 wt% ensures uniform dispersion of CNTs in UHPAAC, which minimizes porosity and refines pore structure, making flowability, setting time, compressive and flexural strength, as well as resistivity and polarization time reach a best balance. Moreover, a 0.3% CNT content yields the optimal piezoresistive response in linearity, sensitivity, hysteresis, repeatability, and response time. The verification results based on accelerated loading equipment confirm that the CNT-reinforced UHPAAC has the potential for automated road monitoring applications. These findings establish a fundamental understanding of the composition-structure–property relationship in CNT-reinforced UHPAAC and provide valuable guidance for the design and application of self-sensing UHPAAC in automated infrastructures.]]></description>
      <pubDate>Fri, 10 Jul 2026 09:42:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2687290</guid>
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    <item>
      <title>Learning from Healthcare: A Perspective Review on Incorporating Soft Constraints into Aviation Maintenance Scheduling</title>
      <link>https://trid.trb.org/View/2724638</link>
      <description><![CDATA[A key consideration in effective aviation maintenance scheduling is the satisfaction of maintenance personnel in relation to allocating tasks and work scheduling. Research that reflects the satisfaction of aviation maintenance staff is limited. Studies focusing on soft constraints in aviation maintenance are nearly non-existent. Soft constraints encompass flexible factors such as employee preferences, workload distribution, and work environment, which significantly impact employee satisfaction and job performance. Aircraft maintenance optimisation needs to consider both hard and soft constraints. Soft constraints have been extensively studied in healthcare and, as this perspective review argues, this can provide valuable insights for aviation maintenance scheduling management. Specifically, aviation maintenance requirements, such as task-based scheduling, necessitate the development of tailored tools to efficiently accommodate the sector’s particulari-ties. This perspective review of aviation maintenance scheduling literature was focused on identifying gaps in the consideration of soft constraints. While there are some studies on incorporating soft constraints into an effective fatigue management system, there is a paucity of research in this area in aviation maintenance. Conversely, the reviewed literature reveals that hard constraints have received greater attention in modelling. This perspective review proposes the development of designated soft constraints to measure the satisfaction of aviation maintenance personnel.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:32:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724638</guid>
    </item>
    <item>
      <title>Time-use behaviour in the United Kingdom: a comparative analysis of pre-COVID19 and during COVID19</title>
      <link>https://trid.trb.org/View/2662685</link>
      <description><![CDATA[The COVID-19 pandemic triggered profound shifts in daily activity patterns and time allocation, providing a unique opportunity to study behavioural adaptations during unprecedented disruptions. This paper examines changes in time-use behaviour in the United Kingdom by comparing pre-pandemic and pandemic periods using data from the UK Time Use Survey (UKTUS) for 2014–2015 and 2020–2021. A Multiple Discrete-Continuous Extreme Value (MDCEV) model is employed to analyse how individuals allocate time across different activities and locations. The findings highlight significant increases in participation and duration of in-home activities, particularly work, shopping, and leisure, while out-of-home activities, such as work, study, and travel, experienced notable declines. The marginal utility analysis reveals that in-home work and shopping surpassed their out-of-home counterparts, reflecting adaptations to pandemic restrictions. Moreover, generational differences in time-use patterns diminished, indicating more uniform behavioural adjustments across age groups. The study identifies challenges faced by larger households in accommodating remote work and study, exacerbated by space constraints and competing demands. Persistent gender disparities are also observed, with women disproportionately engaged in home care and personal care activities, constraining their participation in remote work. On average, women spent 66–71 more minutes per day on home care and 7–13 more minutes per day on personal care than men across both periods.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:32:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2662685</guid>
    </item>
    <item>
      <title>Bootstrapping the Malmquist indexes for Italian airports</title>
      <link>https://trid.trb.org/View/2690136</link>
      <description><![CDATA[This paper uses data envelopment analysis to assess the operational performance of 28 Italian airports during the period of 2000 through 2006. Recent developments in bootstrapping techniques are used to correct total factor productivity estimates for bias and to assess the uncertainty surrounding such estimates. This study found that the Italian airport industry experienced a significant technological regress, with few airports achieving an increase in productivity led by improvements in efficiency. Moreover, the paper shows that the form of ownership (public majority vs. private majority) of an airport management company does not significantly affect performance. In contrast, this type of the concession agreement has positive and significant effects on airport productivity. Finally, the paper highlights the existence of a productivity gap between airports located in the North-Central part of the country and those located in the south.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2690136</guid>
    </item>
    <item>
      <title>An analysis of the literature on the use of fuzzy QFD in logistics strategies</title>
      <link>https://trid.trb.org/View/2688600</link>
      <description><![CDATA[The importance of choosing push and pull logistics strategies in the logistics field is often overlooked by those unfamiliar with logistics, resulting in confusion in the decision-making process regarding logistics operations and the design of the logistics environment. The quality function deployment (QFD) and fuzzy sets techniques have been shown to be suitable methods for the delineation of logistics systems based on previous research, and this paper examines the approaches that have been used to apply fuzzy sets and QFD techniques to logistics strategies. The intention of this research is to unravel the confusion about the concepts of push and pull logistics by supporting it with the development of a new scientific methodology, which is created by combining fuzzy and QFD methods. The aim of this literature review and analysis is to provide an overview of the publications written in the last decade on logistics strategies using QFD and fuzzy methods.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688600</guid>
    </item>
    <item>
      <title>Challenges of adoption digital technologies in Logistics 4.0: a holistic study using the technological determinism theory</title>
      <link>https://trid.trb.org/View/2688599</link>
      <description><![CDATA[Technological development such as blockchain, the internet of things (IoT), and big data is already having significant impacts on workers and businesses in many industries globally. This study aims to find out the main critical challenges in adopting digital technologies in Logistics 4.0 in Oman, to determine the driving factors of digital technology adoption and identify the techno-digital trends positively impacting Oman's logistics companies. Results reveal that the key factors driving digital technologies' adoption and the main challenges companies in Oman include blockchain, big data, IoT, wireless communication technologies and augmented reality. The findings vindicate that the implementation cost, lack of digital skills among the current labour force, cybersecurity, and cultural change were the main obstacles. Consequently, the study discusses the policy implications of Logistics 4.0 and recommends possible solutions for regulators, policymakers, and other stakeholders using the technological determinism theory.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688599</guid>
    </item>
    <item>
      <title>Performance analysis with structural equation modelling among food cold chain operators in Ibadan</title>
      <link>https://trid.trb.org/View/2688597</link>
      <description><![CDATA[This research provides insight into how the utilisation of supply chain management concepts and nascent technologies aided the achievement of cold supply chain performance (CSCP) among retailers of protein (fish and meat) in Ibadan, a Sub-Saharan Africa metropolis. Research hypotheses investigating the possibility of the causal effects between identified SCM concepts [achievement of standardisation in quality (AOS), financial system practices (FSP), internet of things (IoT), internal supply chain practices (ISP), just-in-time (JIT), ownership structure (OS), quality control system (QCS)], and CSCP are formulated and tested using a structural equation modelling approach. A systematic random sampling technique was used to choose four categories of retailers of protein in the study area (hypermarkets, supermarkets, franchisees, and cold room operators). The results showed that there were statistically significant impacts of AOS, FSP, JIT, and, OS on CSCP. The research emphasised the role of corporate governance in the achievement of CSCP among FCC retailers.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688597</guid>
    </item>
    <item>
      <title>Dealing with resilience in supply chain: an integrated Markov chain modelling approach</title>
      <link>https://trid.trb.org/View/2688595</link>
      <description><![CDATA[Recently, supply chain disruptions have occurred all over the world. An evident example is the global pandemic, which is COVID-19. Such a pandemic exposes vulnerable points in the supply chain networks and causes prolonged recovery periods. Therefore, developing resilience in the supply chain is essential to deal with disruptions. This study derives a continuous-time Markov chain model to help analyse the sustainability, vulnerability, and recoverability of a supplier who might experience disruptive events. The forward Kolmogorov's equations are employed to help determine the transition probabilities of all system states. Also, the limiting probabilities of the states are determined to quantify the proportion of time that the system will be in the normal, absorbing, and disrupted states in the long run. This approach is a new way of examining sustainability, vulnerability, and recoverability, which are the key components of the supply chain's resilience.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688595</guid>
    </item>
    <item>
      <title>Multimodal container slot allocation and pricing optimization with overbooking strategies</title>
      <link>https://trid.trb.org/View/2688669</link>
      <description><![CDATA[In the face of uncertain and diverse market demands, maximizing revenue for multimodal transport operators in limited circumstances is a critical challenge. This paper addresses the joint decision-making process of container slot allocation and dynamic pricing, incorporating an overbooking strategy based on revenue management theory from the perspective of multimodal transport operators. We formulate a two-stage stochastic programming model for this problem. Numerical experiments validate the model’s effectiveness, showing that overbooking resolves the conflict between limited capacity and revenue goals, significantly increasing operator revenue. Unlike previous studies, this work introduces a novel modeling framework that integrates overbooking into joint decision-making, offering a more realistic and comprehensive approach. These findings provide a viable solution for multimodal transport operators to increase their revenue and offer theoretical and practical insights for effective resource allocation in the market.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688669</guid>
    </item>
    <item>
      <title>Optimizing battery electric bus allocations: an integrated approach to cost minimization and evolutionary game theory</title>
      <link>https://trid.trb.org/View/2688665</link>
      <description><![CDATA[High capital costs and vehicle allocation challenges impede urban public transport electrification. This paper presents an integrated optimization framework for battery electric bus (BEB) fleet scheduling under both opportunity and depot charging conditions, simultaneously optimizing battery capacity, dispatch frequency, and fleet size to minimize total annualized system cost. A hybrid heuristic algorithm achieves high-quality solutions within practical runtimes. An evolutionary game model captures dynamic interactions between operators and passengers under alternative allocation strategies. The framework is validated through a case study in Harbin, China. Results demonstrate that the optimal configuration reduces annualized system cost by approximately 17.8% (≈266 million CNY) relative to the baseline and identifies cost-effective combinations of key decision variables. Sensitivity analyses confirm robustness across varying wireless charging facility scenarios. These findings provide actionable insights for electric bus planning and sustainable fleet management in cold-climate urban environments.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688665</guid>
    </item>
    <item>
      <title>Collaborative planning of transportation routes and timetables under the cold chain multi-service mode: considering service attribute preferences</title>
      <link>https://trid.trb.org/View/2688663</link>
      <description><![CDATA[Cold chain logistics refers to a special supply chain system with a high demand for low-cost, on-time transportation, high reliability, and environmental friendliness. This study proposes a fuzzy integer nonlinear programming model for the collaborative planning of cold chain transportation routes and timetables, considering service attribute preferences and the uncertainty of the transport cost coefficient, transport time, inventory time, and capacities. Numerical experiments are conducted based on the New Land-Sea Trade Corridor in southwest China. The cold chain multi-service mode achieves a balance between the total cost, reliability, and travel time. Different departure times have a significant impact on transportation plans intended to avoid violating service connection constraints. Preferring particular service attributes does not necessarily increase total transportation costs, enabling improved service quality without increasing total costs.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688663</guid>
    </item>
    <item>
      <title>Electric automobile route scheduling with time setting using machine learning methods</title>
      <link>https://trid.trb.org/View/2688658</link>
      <description><![CDATA[Electric automobiles transform urban mobility by offering a clean and eco-friendly alternative to traditional internal combustion vehicles. Planning and optimizing electric automobile (EA) travel routes involve considering energy consumption, battery range, and the availability of charging stations. By optimizing routes that account for delivery deadlines and charging outlet availability, the Electric Automobile Path Planning with Time Frame (EAPPTF) aims to reduce travel time and energy consumption. While decision tree models forecast and optimize energy consumption and charging stops, route planning uses Dijkstra’s algorithm to identify the shortest path. Using real-time data from Indian cities, this article enhances electric automobile routing by providing insights into traffic flow and charging station availability, thereby enabling efficient travel and energy management. Data from Bengaluru and Hyderabad demonstrate that the proposed methods effectively address the routing challenges for electric automobiles, resulting in shorter trips and lower energy consumption, thereby promoting sustainable urban mobility. By improving autonomous driving technologies and charging infrastructure, these algorithms can also boost urban mobility and sustainability. This strategy supports optimal vehicle operation while addressing pressing issues in emerging nations.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688658</guid>
    </item>
    <item>
      <title>From Ports to Projects: Estimating the Impact of Supply Chain Volatility and Trade Policy Changes on Construction Material Prices</title>
      <link>https://trid.trb.org/View/2688606</link>
      <description><![CDATA[Construction material markets are often reliant on imported commodities. Import tariffs and temporary trade barriers disrupt supply chains, presenting stakeholders with uncertainties regarding how such disruption impacts construction material prices. Despite the plethora of research efforts that examine the effects of economic conditions on construction material prices, the impacts of the import quantities remain understudied. This paper fills this knowledge gap usig a multistep methodology. First, the prices of major construction materials and the quantities of the relevant imported commodities are retrieved. Second, the stability of their historical trends was assessed using econometrics-based tests. Third, a nonlinear autoregressive distributed lag (NARDL) framework is employed to investigate the potentially asymmetric impacts of increases and decreases in import quantities on the construction material prices. The framework is demonstrated using the prices of 15 construction materials in the United States and import quantities from Canada, Mexico, China, and world total. For the 15 materials, prices respond asymmetrically to import shocks; increases and decreases in import quantities have unequal effects for at least one source country. Mexican hot-rolled steel surges are followed by a 2.5% rise in US prices in the long term, while a 10% increase in Canadian fabricated metal imports is accompanied by a short-term price decline of 0.66% at a five-month lag. The results indicate that local production capacity of cement and concrete and crude oil prices drive cement-dependent material prices more than import flows. Due to construction supply chain effects, the prices of prefabricated structural wood members increase by 18.1% in the long run when global lumber imports decline. By modeling how import shocks propagate through upstream and downstream prices, the NARDL framework facilitates prescient procurement strategies of construction materials amid persistent supply chain volatility and evolving trade policies. Owners, contractors, and other associated stakeholders can simulate a shift in steel, cement, or lumber inflows months ahead, identify vulnerable supply lines, and adjust budgets, bids, and contracts proactively.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688606</guid>
    </item>
    <item>
      <title>Towards continuous and on-time operation of electric shared autonomous vehicles with dynamic wireless charging</title>
      <link>https://trid.trb.org/View/2686715</link>
      <description><![CDATA[Dynamic wireless charging (DWC) technology is rapidly emerging as a promising solution to alleviate range anxiety in electric shared autonomous vehicles (SAVs). However, SAVs’ service quality depends not only on efficient charging but also on adherence to service time windows. Existing routing strategies for static charging typically treat charging and time-window scheduling as independent processes, failing to capture their spatiotemporal interdependence under dynamic charging scenarios. To address the SAV’s Pick-up, Delivery and Dynamic Charging Problem with Time Windows (SPDCP-TW), this study proposes a Spatio-Temporal Heterogeneous Deep Reinforcement Learning (STH-DRL) strategy that minimises route costs and stabilises battery state-of-charge levels while ensuring on-time service. Specifically, we introduce a Spatio-Temporal Heterogeneous Attention mechanism to explicitly encode time-window features and an adaptive multi-constraint masking mechanism to distinguish between early, on-time, and late arrival scenarios. A comprehensive simulation platform, incorporating real-world road networks, traffic flows, and taxis’ travel data, has been developed to evaluate multiple time-window-related metrics. Experimental results across three cities and multiple scales show that, compared with heuristic and state-of-the-art DRL methods, our proposed strategy consistently achieves superior performance in terms of total cost, on-time ratio, and battery state stability. Experiments across three cities and multiple operational scales demonstrate that our approach consistently outperforms heuristic and state-of-the-art DRL methods in terms of total cost, on-time ratio, and battery charging state stability. In 24-h continuous operation tests, the proposed strategy maintains on-time ratios of 90-99% while optimising charging schedules. Furthermore, analysis using real taxi datasets reveals that 9–29 continuously operating SAVs can replace 115 conventional taxis. Finally, sensitivity analysis provides practical insights for DWC deployment and battery capacity optimisation, showing that with 5.5% DWC road coverage, a 25-50 kW power range achieves a balanced trade-off, halving battery capacity, and significantly reducing route costs.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686715</guid>
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