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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>Wildlife crossing hotspot analyses for major highways in Wisconsin, USA</title>
      <link>https://trid.trb.org/View/2673045</link>
      <description><![CDATA[In this report we explore where and how to enhance road safety in Wisconsin through reducing collisions with large wild mammals on state-maintained routes, while also ensuring safe crossing opportunities for wildlife. We identified and prioritized road sections in Wisconsin along state-maintained routes that have a relatively high concentration of collisions involving large wild mammals, mostly with white-tailed deer. We used the large wild mammal crash and carcass data to conduct cost-benefit analyses to identify road sections where the implementation of mitigation measures may be less expensive than doing nothing and letting these types of collisions continue to occur. We also identified 36 species of conservation concern in Wisconsin. The species of conservation concern, as defined for this report, included 4 amphibian species (3 frog species, 1 salamander species), 20 reptile species (3 lizard species, 13 snake species, 4 turtle species), and 12 mammal species (1 insectivore species, 5 rodent species, 1 mustelid species, 1 canid species, 2 felid species, 2 ungulate species). We identified road sections, or counties, where species of conservation concern have been observed. Road sections that would need to be prioritized for reducing collisions with common large mammals (i.e., mostly white-tailed deer) are mostly in the eastern and southeastern parts of Wisconsin. Areas where a relatively high number of species occur that are of conservation concern are predominantly in the southwestern parts of Wisconsin. This illustrates that there would be benefits to having a two-track system of policy, funding mechanisms and implementation programs; one that is rooted in human safety through reducing collisions with large wild mammals that are common, and another that is rooted in biological conservation. We also identified measures for both large wild mammals and small animal species that are aimed at reducing wildlife-vehicle collisions and associated direct road mortality of the animals, and at reducing the barrier effects of roads and traffic to wildlife.]]></description>
      <pubDate>Tue, 03 Mar 2026 17:12:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673045</guid>
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    <item>
      <title>Applications of WRM Performance Models for Evaluating the Implications of Varying Service Standards</title>
      <link>https://trid.trb.org/View/2635953</link>
      <description><![CDATA[This report describes the result of a study aiming at illustrating how models of winter road maintenance (WRM) performance measures can be applied to investigate the implications of different winter road maintenance level of service (LOS) standards under specific winter weather conditions. The study introduces a cost-benefit framework integrating the two primary cost and benefit components associated with winter road maintenance services, namely, material costs, safety and mobility benefits. Various maintenance input, output and outcome models are developed using five seasons of event-based data. The expected cost of maintaining a given highway route is captured by a salt application model, which relates the amount of salt used over a snow event to various event characteristics as well as the LOS class of the highway. The benefit from WRM for a highway route is quantified on the basis of the expected safety improvements, i.e., reduction in the number of collisions, and, the expected mobility improvements, i.e., increase in trip making utility and reduction in travel time. A case study is conducted to determine the optimal traffic threshold for demarcating the Class 1 and 2 highways in Ontario. The study has demonstrated the feasibility of applying the proposed quantitative approach when assessing alternative service standards under different climate conditions. Lastly, future research directions are highlighted at the concluding section.]]></description>
      <pubDate>Mon, 02 Mar 2026 16:12:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635953</guid>
    </item>
    <item>
      <title>Effect of Video Camera-Based Remote Roadway Condition Monitoring on Snow Removal-Related Maintenance Operations</title>
      <link>https://trid.trb.org/View/2636020</link>
      <description><![CDATA[Remote monitoring through the use of cameras is widely utilized for traffic operation but has not been utilized widely for roadway maintenance operations. The Utah Department of Transportation (UDOT) has implemented a new remote monitoring system, referred to as a Cloud-enabled Remote Video Streaming (CRVS) camera system for snow removal-related maintenance operations in the winter. The purpose of this study was to evaluate the effectiveness of the use of the CRVS camera system in snow removal-related maintenance operations. This study was conducted in two parts: opinion surveys of maintenance station supervisors and an analysis on snow removal-related maintenance costs. The responses to the opinion surveys mostly displayed positive reviews of the use of the CRVS cameras. On a scale of 1 (least effective) to 5 (most effective), the average overall effectiveness given by the station supervisors was 4.3. An expedition trip for this study was defined as a trip that was made to just check the roadways if snow-removal was necessary. The average of the responses received from surveys was calculated to be a 33 percent reduction in expedition trips. For the second part of this study, an analysis was performed on the snow removal-related maintenance cost data provided by UDOT to see if the installation of a CRVS camera had an effect in reducing expedition trips. This expedition cost comparison was performed for 10 sets of maintenance stations within Utah. It was difficult to make any definitive inferences from the comparison of expedition costs over the years for which precipitation and expedition cost data were available; hence a statistical analysis was performed using the Mixed Model ANOVA. This analysis resulted in an average of 14 percent higher ratio of expedition costs at maintenance stations with a CRVS camera before the installation of the camera compared to the ratio of expedition costs after the installation of the camera. This difference was not proven to be statistically significant at the 95 percent confident level but indicated that the installation of CRVS cameras was on the average helpful in reducing expedition costs and may be considered practically significant. It is recommended that more detailed and consistent maintenance cost records be prepared for accurate analysis of cost records for this type of study in the future.]]></description>
      <pubDate>Mon, 02 Mar 2026 16:12:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636020</guid>
    </item>
    <item>
      <title>A cost model for road public transport sensitive to the operating program</title>
      <link>https://trid.trb.org/View/2630683</link>
      <description><![CDATA[Most models for estimating the cost per kilometer of local public transport (LPT) do not include variables attributable to the service operating program (SOP), that is the document showing lines, routes, stops, rides and related timetables. Therefore, by these tools it is not possible to take into account the impact, on the unit cost, of the different use of drivers and vehicles resulting from the number and time of the rides performed. This work, to overcome this important limitation proposes a modification, applicable to most existing models already including the other variables that most affect the cost. In particular, a statistical relationship has been built as a function of the descriptive variables of the SOP known to all, capable of providing a factor 𝘒 that, multiplied by the value of the cost derived from any model, allows it to be corrected as a result of the specific characteristics of the SOP. The methodology developed is of general validity. The model built for the calculation of 𝘒 has been calibrated on a regional LPT service offered in an area with weak demand. A specific recalibration would allow to use it in areas different in size, type and characteristics of transport demand and supply.]]></description>
      <pubDate>Mon, 02 Mar 2026 08:56:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630683</guid>
    </item>
    <item>
      <title>Integrated approach for operations in robotic mobile fulfillment centers under order uncertainty</title>
      <link>https://trid.trb.org/View/2659488</link>
      <description><![CDATA[The rapid growth of e-commerce has significantly increased the complexity of warehouse operations, particularly in robotic mobile fulfillment centers (RMFCs), where decision-making under uncertain customer demand poses substantial challenges. This study proposes an integrated two-stage stochastic optimization model that jointly addresses item-to-pod assignment, pod positioning, order allocation, pod selection, and sequencing decisions. Item shortages are explicitly incorporated into the model to enhance operational robustness under demand uncertainty.To manage the resulting computational complexity, we develop a prioritization-based item assignment strategy combined with a clustering-oriented order allocation mechanism, embedded within a tailored heuristic algorithm. Computational experiments show that the proposed heuristic achieves near-optimal performance on small-scale instances, with solution gaps of approximately 9–14% relative to exact solutions. For large-scale instances, the heuristic consistently outperforms the solver’s incumbent solutions by 9–29% and yields substantially better results than established metaheuristic benchmarks, including genetic algorithms and simulated annealing, whose deviations increase to 45–56% as problem size grows, while maintaining practical computation times.Sensitivity analyses further demonstrate that increasing pod capacity and improving replenishment center placement can reduce robot travel distances by up to 30%. In addition, lower demand dispersion and structured item assignment significantly mitigate shortages and enhance overall system efficiency. Comparative experiments against sequential planning approaches confirm that the integrated stochastic framework delivers up to 20% reductions in robot travel under high demand variability, albeit at moderately higher computational cost.From a managerial perspective, these improvements translate into substantial operational and economic benefits. Industry benchmarks suggest that even moderate reductions in robot travel distance (15–20%) can yield annual cost savings ranging from several hundred thousand dollars in medium-scale facilities to multi-million-dollar savings in large-scale RMFC deployments. Overall, the results highlight the strong practical value of integrated stochastic planning for improving efficiency and resilience in robotic fulfillment systems.]]></description>
      <pubDate>Fri, 27 Feb 2026 17:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659488</guid>
    </item>
    <item>
      <title>Delay Overrun in Road Maintenance Projects in Syria</title>
      <link>https://trid.trb.org/View/2665612</link>
      <description><![CDATA[Road maintenance project delays present serious obstacles to the development of infrastructure, especially in nations where political and economic instability are prevalent. This study focuses on the key reasons why road repair projects in Syria took longer than expected between 2019 and 2022. Insufficient construction material supply and late contractor payments are the most important delay issues identified by the research, which is based on official records overseen by the Public Establishment of Road Communications. The study illustrates the intricate relationship between emergency repairs, fuel shortages, administrative inefficiencies, and governmental requirements through a correlation analysis of several projects. To reduce future delays in Syria's road infrastructure sector, the findings are intended to assist stakeholders in enhancing project planning, resource management, and execution techniques.]]></description>
      <pubDate>Thu, 26 Feb 2026 17:01:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665612</guid>
    </item>
    <item>
      <title>Review and Evaluation of Concrete Pavement Design Method in Alabama</title>
      <link>https://trid.trb.org/View/2669651</link>
      <description><![CDATA[This research was undertaken to evaluate opportunities for enhancing Alabama’s concrete pavement design practices to achieve a better balance between structural reliability, durability, and economy. The primary objectives were to: (1) review ALDOT’s current design parameters, specifically reliability and terminal serviceability indices, and assess their influence on pavement thickness; (2) compare the cost-effectiveness of widened lanes (13–14 ft) with non-tied shoulders against conventional 12-ft lanes with tied shoulders; and (3) assess the feasibility of adopting the AASHTO 1998 Supplement to the Guide for Design of Pavement Structures (Part II: Rigid Pavement Design & Joint Design) and, if appropriate, develop a computational spreadsheet to support ALDOT implementation. Across all evaluated conditions, results indicated that the AASHTO 1998 method yielded thicker pavement slabs than the AASHTO 1993 method by approximately 10–37%, depending on the selected reliability level, terminal serviceability index, and location. Consequently, construction costs derived from AASHTO 1998 were 7–46% higher per mile than those computed using AASHTO 1993. Designs employing widened lanes with non-tied shoulders required 1–2% thinner slabs and demonstrated 11–20% cost savings, depending on site conditions and design assumptions. Note that a load transfer coefficient (J) value of 2.9 was consistently used for all pavement types in this study. The selection of ALDOT-specific J values may help reduce conservative over-design or mitigate the risk of under-performance. These findings suggest that certain geometric configurations can partially offset the higher costs associated with more mechanistic design methods.]]></description>
      <pubDate>Thu, 26 Feb 2026 17:01:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669651</guid>
    </item>
    <item>
      <title>Data Sharing Mechanism among Intelligent Transportation Infrastructure Stakeholders: Based on the Data Value Chain Perspective</title>
      <link>https://trid.trb.org/View/2625834</link>
      <description><![CDATA[In the context of digital economy, intelligent transportation infrastructure (ITI) as an important node of the intelligent transportation system (ITS) is of great significance in accelerating the high-quality construction of smart cities. However, due to the privacy concerns of all stakeholders, it is difficult to balance the benefits and risks associated with the flow of data resources. Previous research has not provided a clear solution to the data sharing dilemma of ITI. Thus, based on the data value chain theory, this paper constructed a tripartite evolutionary game model involving the users, the owners, and the governments. Subsequently, the evolutionarily stable strategies and corresponding conditions of each participant were examined, and the critical factors on stakeholder decision-making were discussed using numerical simulation analysis. The results show that (1) building a harmonious and unified data-sharing environment is the consensus of all stakeholders, without interference from the initial strategy; (2) the changes in benefits and the learning costs have a more significant impact on user decisions than the loss changes; (3) on the contrary, the owners are more sensitive to the additional costs of facilitating data sharing than to the value it brought; (4) for governments, imposing penalties is a more effective way to promote data security than offering subsidies. This paper can not only promote the relevant research of ITI, but also provide an important reference for governments to promote data sharing and the development of digital economy.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625834</guid>
    </item>
    <item>
      <title>MHA Nation Drone Project: Planning and Protocol Development</title>
      <link>https://trid.trb.org/View/2666687</link>
      <description><![CDATA[The MHA Drone Project: Planning and Protocol Development Project Team developed a comprehensive plan for the use of drones to serve the Tribal members of the Three Affiliated Tribes (TAT) of the Fort Berthold Reservation (otherwise known as the Mandan Hidatsa Arikara (MHA) Nation) to increase access to medical care and equipment, and potentially other use cases with opportunities for application for Stage 2 funding. The Fort Berthold Reservation, a federally recognized Indian Tribe, is in north-central North Dakota (ND), within a rural, rugged landscape with heavy oil production, rough roads, and unforgiving weather. The proposal goals and objectives were accomplished including: (1) identified additional use cases, which included completion of two surveys of stakeholder needs and perceptions and a summary report with the findings of six listening sessions that were shared broadly with key Tribal stakeholders; (2) developed a blueprint for a safe, efficient, and scalable network for use of drones on our Tribal lands, which was accomplished by conducting a beyond visual line of sight (BVLOS) demonstration of delivery of medication that provided the opportunity to gather data to monitor the airspace system; (3) developed and implemented a robust workforce engagement plan, by finalizing an aeronautics articulation agreement between two educational grant partners with the primarily online program to begin in August 2025, offering three Drone Camps in 2023/2024/2025, and teaching over 200 youth at remote MHA Nation schools through a Drones in School effort; (4) ensured comprehensive community engagement and partnerships to support government to government relationships, by assembling and hosting monthly MHA Drone Advisory Board to guide efforts and testifying before the MHA Tribal Business Council to secure required resolutions including a corridor for drone delivery between two remote communities; and (5) explored the economic feasibility of drone use at-scale by completing a comprehensive economic analysis of costs and benefits.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:00:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666687</guid>
    </item>
    <item>
      <title>Loading and multi-trip routing problem using hierarchical ant colony optimisation algorithm</title>
      <link>https://trid.trb.org/View/2624103</link>
      <description><![CDATA[In this paper, we formulate the loading and routing problem as a new mixed-integer programming model with multi-trip routing and loading constraints. The objective is to minimise the total costs of delivery and outbound cross-docking operations and delivery. We also modify an ant colony optimisation algorithm to a so-called four-level ant colony optimisation heuristics (FLACO) to search for the best loading and routing solution in hierarchical levels of trips, trucks, periods, and routes. At each level, the ACO parameters are updated iteratively to process the problem constraints. The case of a large dairy company in Vietnam is used to validate the proposed model and FLACO. The FLACO could give as close as about 2.46% to the optimal solution and outperform the genetic algorithm for small-sized and large-sized problems, respectively.]]></description>
      <pubDate>Mon, 23 Feb 2026 11:23:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2624103</guid>
    </item>
    <item>
      <title>Leveraging Radial Basis Function Regression and Bootstrapping for Price Adjustments in Road Contracts</title>
      <link>https://trid.trb.org/View/2562127</link>
      <description><![CDATA[Price escalation, the upward movement of costs, is managed in long-term road construction contracts through Price Adjustments. These adjustments mitigate fluctuations in input costs such as materials, labor, and equipment, preventing financial strain on contractors and ensuring project continuity. Typically, price adjustments rely on cost indices with assigned weightings. However, road agencies often incur higher-than-anticipated costs, necessitating optimized weighting determination. This paper explores Radial Basis Function (RBF) regression combined with bootstrapping to refine weightings in price adjustment formulas using historical price index data. RBF regression models the non-linear relationships between price index ratios and weightings, while bootstrapping enhances robustness by reducing the influence of outliers and quantifying variability. By averaging results over multiple iterations, this method improves reliability and provides contracting agencies with confidence in the adjustment process. Integrating bootstrapping with RBF regression offers a data-driven, flexible approach to setting price adjustment weightings. This enhances financial planning for contractors and road agencies, reducing risks and ensuring fair compensation in long-term construction projects.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2562127</guid>
    </item>
    <item>
      <title>Logistics Demand Forecasting in Shaanxi Province Using a Hybrid GM-RR Model</title>
      <link>https://trid.trb.org/View/2613181</link>
      <description><![CDATA[Logistics demand forecasting is crucial for optimizing resource allocation, reducing operating costs, improving service efficiency, and supporting decision-making. This paper uses a Hybrid GM-RR forecasting model to predict the logistics demand in Shaanxi. Firstly, using grey correlation analysis, six factors with the highest grey correlation degree were selected from nine influencing factors as independent variables, and freight volume as dependent variables. Secondly, in order to solve the problem of multicollinearity and improve the accuracy of prediction, the ridge regression prediction method combined with the grey prediction model is used to predict the impact indicators related to logistics demand. Finally, the prediction results are introduced into the ridge regression model as input variables to obtain stable and accurate prediction results. The research results show that this improved ridge regression model can effectively predict logistics demand and provide a scientific basis for logistics planning and decision-making.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613181</guid>
    </item>
    <item>
      <title>Hybrids in the middle: PHEVs as bridge or lock-in to policy balance</title>
      <link>https://trid.trb.org/View/2663875</link>
      <description><![CDATA[Battery electric vehicles (BEVs) are central to transport decarbonization, yet the fiscal and environmental efficiency of government subsidies remains uncertain, particularly when they share the market with plug-in hybrid electric vehicles (PHEVs). This study develops an agent-based model with evolutionary dynamics to examine how PHEVs influence market equilibrium behavioral adaptation and policy effectiveness within different fiscal frameworks. Two subsidy structures, a five-year unlimited budget and a ten-year gradually declining one, are simulated to explore how policy design shapes consumer and investor decisions. PHEVs may act as transitional technologies that support BEV diffusion or as competing alternatives that slow full electrification. At low subsidy levels, emissions remain about 23% higher than in a BEV-only market. Well calibrated fiscal support, however, may reverse this effect, achieving up to a 28% improvement in emission reduction. Predictable front-loaded policy design strengthens environmental performance and fiscal stability, guiding future policy decisions.]]></description>
      <pubDate>Fri, 20 Feb 2026 14:15:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663875</guid>
    </item>
    <item>
      <title>A comparison of cost-sharing models in horizontal cooperative routing</title>
      <link>https://trid.trb.org/View/2649634</link>
      <description><![CDATA[We develop and compare several cost-sharing models for cooperative vehicle routing problems formulated under various objectives and constraints. Our study is motivated by a real-world case involving smallholder farmers in the Province of Quebec. We examine the issues of fairness and stability in cooperative routing, and we show that coalitions served by single routes are sufficient to impose stability conditions. To evaluate equity, we use the Gini coefficient to measure the dispersion of individual savings. Hence we can analyze the trade-offs between fairness and stability. We demonstrate that widely used fairness proxies do not necessarily yield equitable outcomes. We test our methodology on randomly generated instances and on a Quebec-based case study.]]></description>
      <pubDate>Thu, 19 Feb 2026 10:53:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2649634</guid>
    </item>
    <item>
      <title>Cost allocation in a robust two-stage resource allocation game: Fairness and robustness</title>
      <link>https://trid.trb.org/View/2649630</link>
      <description><![CDATA[This paper considers a two-stage resource allocation game within a cooperative game framework from a platform perspective, where the customers’ demands are uncertain. To incentivize all customers (players) into the grand coalition for joint cost sharing in resource allocation, a critical issue for the platform is determining a fair and robust cost allocation solution. To address the challenge, we introduce the concept of the strict robust core to the operations research (OR) game with constraints and propose the Two-stage Resource Allocation-Robust Cost Sharing Problem (TRA-RCSP). Our approach integrates distributionally robust optimization (DRO) and distributionally favorable optimization (DFO) to improve computational tractability. By leveraging the polyhedral ambiguity set to model demand uncertainty, we calculate the worst-case cost for grand coalition and the best-case costs for subcoalitions. Additionally, we develop an iterative constraint generation algorithm to mitigate the exponential growth of constraints in TRA-RCSP. Numerical experiments demonstrate that our algorithm achieves excellent computational efficiency and the strict robust core significantly outperforms the cost allocation of SAA model across both robustness performance metrics, ensuring the formation of the grand cooperation and its long-term stability under uncertain demands.]]></description>
      <pubDate>Thu, 19 Feb 2026 10:53:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2649630</guid>
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