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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Preliminary Cost Estimates Using Probabilistic Simulation for Highway Bridge Replacement Projects</title>
      <link>https://trid.trb.org/View/2164472</link>
      <description><![CDATA[To improve the accuracy and efficiency of highway budgeting estimation has been an important research focus in the industry and is the objective of this paper. Useful data were extracted from the Texas Department of Transportation (TxDOT) to develop an alternative to achieve the research objective. Heuristic simulation models pertaining to highway bridge replacement projects were developed to guide engineers to reduce estimation variability before the beginning of planning authorization. The proposed simulation models include independent, correlated, and Latin Hypercube sampling approaches that specifically consider major work items, roll-up work items, and project-level engineering contingency. The charts of cumulative density functions (CDFs) are derived as a handy tool for decision makers to consider project finance initiation, project risk and uncertainty assessment. The systematic procedure can be expanded to other project types and to develop lane-km (lane-mile) cost distributions when ample historical project data are available.]]></description>
      <pubDate>Mon, 05 Oct 2026 21:48:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2164472</guid>
    </item>
    <item>
      <title>The price of resilience and the cost of equity in a budget-centric framework for humanitarian logistics</title>
      <link>https://trid.trb.org/View/2692828</link>
      <description><![CDATA[Humanitarian supply networks must simultaneously achieve operational efficiency, ensure equitable distribution across vulnerable populations, and maintain service continuity under disruptions; yet few frameworks jointly quantify these trade-offs in actionable budget terms. We address this gap by developing a hierarchical optimization pipeline that integrates three objectives in a principled sequence: (i) budget-constrained service maximization via a multi-commodity network flow model, (ii) distributional equity analysis using a proportional service floor with a closed-form threshold, and (iii) adversarial resilience assessment through validated k-interdiction. The term “adversarial” refers not solely to malicious actors but to worst-case disruption scenarios—including natural hazards, infrastructure failures, and conflict-induced damage—that humanitarian planners must anticipate as a matter of prudent risk management. We benchmark our greedy interdiction heuristic against candidate-set exact enumeration over a restricted arc set, achieving 0% optimality gap (within the candidate set) for k ≤ 2 and only 0.87% gap at k=3 while running 620 ×  faster. Applied to a national-scale Colombian network (55 nodes, 124 arcs, six commodity groups), the model identifies a knee budget of $491 M delivering 9,911 service units. We derive a critical equity threshold τ*=0.63 that delineates a costless equity region—where fairness improvements impose no efficiency loss—from the true trade-off region. Under worst-case three-arc interdiction, greedy attack degrades service by 44% versus 29% under flow-ordered removal, revealing 52% higher relative damage that conventional heuristics miss. The Price of Resilience metric translates continuity targets into budget terms: recovering baseline service after a single adversarial failure requires an additional $1.06 B in budget (a 217% increase), while recovery from three coordinated failures demands an additional $1.66 B (a 337% increase). A parametric sensitivity analysis across 28 scenarios confirms that while the numerical value of τ* is instance-dependent—varying from 0.03 to 0.99 with demand heterogeneity as the dominant driver—the structural two-regime property persists across all tested scenarios. A seven-scenario uncertainty analysis under  ± 20% perturbations to demand, supply, and cost shows that the Price of Resilience ranges from 2.87 ×  to 4.62 ×  baseline budget at k=3, while the cost of equity remains below 0.6% across all scenarios, confirming that both metrics are robust to plausible parameter uncertainty. Benchmarking against weighted-sum scalarization demonstrates that the hierarchical pipeline achieves Pareto-competitive outcomes while producing actionable decision rules—the equity threshold, the Price of Resilience, and protect-versus-pay guidance—that simultaneous scalarization cannot generate. These policy-facing quantities translate abstract trade-offs into implementable rules for budgeting, infrastructure hardening, and contingency planning.]]></description>
      <pubDate>Wed, 30 Sep 2026 16:23:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692828</guid>
    </item>
    <item>
      <title>Budget Optimization for a Postearthquake Regional Road Network Considering Connectivity Reliability</title>
      <link>https://trid.trb.org/View/2714442</link>
      <description><![CDATA[The connectivity between earthquake-affected areas and unaffected regions directly affects rescue efficiency and resource allocation speed following seismic events. Therefore, reinforcing critical road units in road networks before disasters is essential to ensure postdisaster connectivity. This study models road networks as topological graphs, assigning binary states (connected or interrupted) to road units for simulating postseismic damage scenarios. The integration of the virtual edge method with Monte Carlo simulation facilitates the quantification of connectivity reliability between unaffected and disaster-affected zones, thereby enabling the identification of critical locations exhibiting low connectivity reliability. Subsequently, a budget-optimized model is formulated. Through the process of sensitivity analysis, a critical subset of road units is identified, and an effective algorithm is developed to solve the model. This approach results in a cost-optimized strategy that minimizes total retrofit costs for road units while ensuring the minimum connectivity reliability threshold is maintained in disaster-affected zones. The technical viability of the proposed methodology is validated by case studies.]]></description>
      <pubDate>Wed, 16 Sep 2026 11:21:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714442</guid>
    </item>
    <item>
      <title>Comparing public investments across sectors with CBA-based impact information and participatory budget choices</title>
      <link>https://trid.trb.org/View/2711691</link>
      <description><![CDATA[This paper proposes a hybrid decision-support framework that integrates cost–benefit analysis (CBA) with participatory budgeting (PB) to inform public-sector portfolio choices. To highlight the approach, we assume that CBA has been conducted to evaluate twelve independent infrastructure and service projects, establishing their economic viability. Subsequently, PB is employed to elicit community preferences regarding the same projects, ensuring alignment with public values. The combined framework aims to reconcile technical efficiency, understood here as welfare-economic appraisal implemented through standard modelling and valuation conventions, with democratic legitimacy, captured through direct, budget-constrained citizen prioritisation. Our findings show that respondents gave the strongest average support to health care and utilities projects, with education also performing relatively well, while public transportation and road infrastructure were preferred to transport-electrification initiatives. In contrast, public projects associated with private vehicle and freight vehicle electrification attracted comparatively weak support, and public transportation electrification was supported less strongly than conventional public transport investment. More broadly, respondents tended to favour projects that delivered larger consumer-surplus and environmental benefits and projects located in, or relevant to, their own area.]]></description>
      <pubDate>Wed, 16 Sep 2026 11:21:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711691</guid>
    </item>
    <item>
      <title>National Highway Traffic Safety Administration: FY 2000 Budget in Brief</title>
      <link>https://trid.trb.org/View/2742702</link>
      <description><![CDATA[The FY 2000 Budget Request by the National Highway Traffic Safety Administration reflects the priority placed on highway safety programs by the Secretary and the Administration. Motor vehicle crashes account for 94 percent of the deaths and 99 percent of the injuries in U.S. transportation. The funding levels presented include staffing, administrative, and program costs. All funding is proposed from the Highway Trust Fund.]]></description>
      <pubDate>Mon, 07 Sep 2026 10:57:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742702</guid>
    </item>
    <item>
      <title>Performance-Based Management Approaches for Maintenance: A Guide</title>
      <link>https://trid.trb.org/View/2772578</link>
      <description><![CDATA[This report presents a guide for assessing the readiness of performance-based management approaches to support maintenance budgeting activities and personnel. The development of this guide was based on a methodology that incorporated stakeholder interviews, case studies, and a peer review workshop. This guide will be of immediate interest to highway maintenance engineers, asset managers, and performance managers seeking to address decision-making challenges associated with maintenance quality assurance programs.]]></description>
      <pubDate>Sat, 05 Sep 2026 11:31:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2772578</guid>
    </item>
    <item>
      <title>Pavement Markings: Balancing Safety, Liability, and Maintenance Budgets</title>
      <link>https://trid.trb.org/View/2742790</link>
      <description><![CDATA[Pavement markings serve as fundamental traffic control devices, supplementing signs and signals to effectively convey regulations, warnings, and guidance to all road users. These markings are critical for improving safety for motorists, bicyclists, and pedestrians alike. The initial objective of this research was to address the “guidance gap” for medium-volume roadways—specifically those with traffic counts higher than typical low-volume local roads but falling below the 6,000 Average Daily Traffic (ADT) threshold where markings are strictly mandated. The goal was to help local agencies navigate decision-making for these intermediate corridors where standard high-volume guidance might be considered excessive or fiscally unsustainable. However, a 2025 statewide survey of 80 Minnesota local agencies revealed a significant operational reality: approximately 86% of counties already apply longitudinal pavement markings (centerlines and edgelines) to all paved roadways under their jurisdiction. This near-universal application is influenced by State-Aid rules and a commitment to systemic safety. In contrast, cities were found to be much more selective, typically marking only 18% to 33% of their paved systems, focusing primarily on collectors and arterials.]]></description>
      <pubDate>Mon, 10 Aug 2026 08:59:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742790</guid>
    </item>
    <item>
      <title>Aviation Cybersecurity: FAA and TSA Are Collaborating on Cybersecurity but Need to Address Key Shortfalls</title>
      <link>https://trid.trb.org/View/2730684</link>
      <description><![CDATA[Commercial flight operations rely on interconnected systems that reside onboard an aircraft and on the ground in the National Airspace System. Given this interconnectivity, these systems are inherently more vulnerable to exploitation and are at an increased risk of being targeted by malicious actors. The Federal Aviation Administration (FAA) and Transportation Security Administration (TSA) are the primary federal agencies leading security and resilience efforts in the aviation subsector. The FAA Reauthorization Act of 2024 includes a provision for the Government Accountability Office (GAO) to evaluate FAA and TSA efforts to manage their roles and responsibilities for aviation cybersecurity. This report examines (1) the extent to which FAA and TSA defined their current roles and responsibilities for aviation cybersecurity; (2) the budget requests for the FAA entities responsible for implementing its Cybersecurity Strategy, and the extent to which they meet relevant Office of Management and Budget (OMB) reporting requirements; (3) the extent to which the FAA’s Cybersecurity Strategy incorporates key federal and industry practices to address cybersecurity risks and vulnerabilities for avionics and ground systems; and (4) the extent to which FAA implemented its Cybersecurity Strategy to mitigate cybersecurity risks to its systems and networks. To address these objectives, GAO compared FAA and TSA strategies and supporting documentation to determine how the agencies defined separate roles and responsibilities for aviation cybersecurity and compared them against the National Institute of Standards and Technology (NIST) Cybersecurity Framework 2.0 guidance on roles, responsibilities, and authorities. GAO also reviewed the fiscal year 2024 through 2026 President’s budget requests for FAA and evaluated the agency’s budget data and associated process to determine if the agency comprehensively reported its cybersecurity spending in accordance with OMB’s reporting requirements. Additionally, GAO compared the FAA Cybersecurity Strategy as of February 2026 and associated processes for aircraft certification, system security authorization, and zero trust implementation against key practices GAO identified for mitigating risks and vulnerabilities for avionics and ground systems. Further, GAO evaluated documentation demonstrating FAA’s implementation of its Cybersecurity Strategy’s goal and associated objectives to protect and defend its networks and systems against risks. Lastly, GAO interviewed or collected written responses from FAA, TSA, and selected aviation stakeholders representing industry groups, avionics manufacturers, domestic airlines, and a research organization. GAO selected these aviation stakeholders based on a review of prior work, a literature search, and recommendations obtained from stakeholders interviewed during prior related work.]]></description>
      <pubDate>Thu, 23 Jul 2026 16:13:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730684</guid>
    </item>
    <item>
      <title>A novel approach for railway maintenance budgeting using a hybridization of machine learning and integer programming</title>
      <link>https://trid.trb.org/View/2694574</link>
      <description><![CDATA[The balance between budgeting and retaining the optimum performance of railway infrastructure has gained significant importance in recent years. Due to the expansion of railway networks, high maintenance costs, and limited budgets, prioritizing maintenance operations takes time and effort. On the other hand, derailments are one of the most essential types of rail accidents worldwide. Derailments typically result from track conditions, machinery issues, human error, etc. One approach to railway track maintenance budgeting is to allocate the available budget with the purpose of minimizing the financial consequences of derailments considering the accidents' occurrence probability. In this regard, the probability of accident occurrence must be calculated, and the financial consequences of derailment must be estimated. Then, the maintenance plan could be determined by using optimization methods and considering related constraints. In this paper, to calculate the probability of track-caused derailment accident occurrence, the Track Performance Index (TPI) presented by Janatabadi et al. (2020) is employed. The TPI metric is calculated for each block based on the track geometric data of curves in the railway network. Then, various Machine Learning (ML) models are trained and tested in order to estimate the mentioned consequences and the best one with highest precision is selected. The proposed ML model estimates the financial consequences based on the blocks' characteristics with a Normalized Root Mean Square Error (NRMSE) of 18.2%. In the next step, the Branch and Bound (B&B) method is utilized to optimize railway track renewal budget allocation in order to minimize the total probable consequences of accidents in the railway network. To validate the efficiency of the presented method, it is implemented on Iran's railway network. Compared to other methods, the results indicated that the proposed method decreased the network loss more and saved an amount of the maintenance budget.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:50:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2694574</guid>
    </item>
    <item>
      <title>Strategic Analysis of Maintenance Funding and Standard for the Trans-African Highway Network Using HDM-4</title>
      <link>https://trid.trb.org/View/2671494</link>
      <description><![CDATA[African governments and the multilateral development partners engaged in the development of the road transport sector in Africa have understood the importance of the Trans-African Highway (TAH) network and are contributing significantly to funding the construction of the missing links of the network. However, the same cannot be said for the operation and maintenance of the completed sections of the network. Moreover, the budget constraint in funding road maintenance and the considerably differing maintenance standards in individual countries across the continent make it a huge challenge to have a regionally as well as a continentally acceptable level of service (LOS) on the network. In this research, the Highway Development and Management Model (HDM-4 Version-2) was used to conduct several levels of strategy analysis on various maintenance budget scenarios and the maintenance standards in use across West Africa. The objective is to find an applicable maintenance funding scenario using a regionally appropriate maintenance standard. Using these scenarios, the study established that funding the TAH ECOWAS network through the Regional Maintenance Fund – Full Budget, which envisioned as a contribution from individual countries based on the percentage of ownership, insured an NPV of 1.761 trillion, a EIRR of 144% and NPV/CAP of 15.4. This will also keep the corridor at an IRI below 5. But this is possible only if a TAH maintenance fund is established at the regional level and a synchronized maintenance standard is used.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:05:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671494</guid>
    </item>
    <item>
      <title>Risk Based Management of Bridges in Ireland</title>
      <link>https://trid.trb.org/View/2671091</link>
      <description><![CDATA[The purpose of this paper is to present an overview of the state of the art in terms of Bridge Management Systems (BMS’s) and the application of risk-based approaches to the management of bridges. In this regard a review of international best practice in the development of BMS’s is presented along with the types of functionality which they can offer and the direction they are taking in state-of-the-art asset management. Significantly, the enhanced functionality of BMS’s is demonstrated to build upon existing/traditional information and data set structures to facilitate decision making around intervention strategies and budgeting. It is demonstrated that at their core, BMS’s make use of processes such as Markovian Processes (which can be homogenous or non-homogeneous) to predict condition as a function of time horizon. This has been the case for the past couple of decades with many international examples of successful implementation documented. Indeed, one such example is presented in an Irish context where the Markovian formulation is developed using available datasets. As such it is demonstrated that there are no operational barriers to implementing these processes formally to enhance BMS functionality and facilitate decision making around optimal intervention strategies and budgeting. Best practice internationally is demonstrated to be moving to asset lifecycle management which has risk evaluation at its core. Current examples are presented from international organisations to highlight this move. Risk based decision frameworks offer the possibility to work with the enhanced functionality of a BMS to provide for consideration of inspection frequencies for bridges/structures in different risk groups, and moreover for budget allocation decisions to be made based on risk from safety, economic, sustainability and resilience perspectives.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671091</guid>
    </item>
    <item>
      <title>Electric vehicle charging as a monthly budget: portfolio preferences across working Americans</title>
      <link>https://trid.trb.org/View/2714843</link>
      <description><![CDATA[We examine electric vehicle (EV) charging location preferences by investigating how drivers allocate monthly charging sessions across home, workplace, and public locations. In contrast to earlier studies that treat charging location as a one-time, discrete choice, we examine preferences for combinations of all three locations over a monthly period. We employ a multiple discrete–continuous extreme value (MDCEV) model using stated preference data from 881 employed EV drivers across the United States. Results show that 88.9% of charging decisions involve multiple locations. Home charging is preferred overall, followed by workplace and public. Drivers with private driveways, single-family homes, or solar panels, as well as older adults have higher home charging preferences, though battery storage moderates the pull of solar toward home. Urban residents rely more on public charging, while workplace charging is highly price-elastic, offering employers a demand management lever. Our study underscores the importance of examining charging behavior as a portfolio allocation decision.]]></description>
      <pubDate>Mon, 29 Jun 2026 09:13:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714843</guid>
    </item>
    <item>
      <title>Network-Level Maintenance and Rehabilitation Budget Planning Based on the Reliability of Large-Scale Pavement Networks</title>
      <link>https://trid.trb.org/View/2673013</link>
      <description><![CDATA[Performing cost-effective maintenance and rehabilitation (M&R) budget planning is crucial for any large-scale pavement network. This paper presents a novel model to maximize the reliability of large-scale pavement networks to obtain M&R options for their segments. The weight of pavement segments, composed of service and spatial weights, plays a major role in the reliability of the pavement network. Service weight can be defined using the traffic performance index, which comprehensively represents the level of congestion in a pavement network. Additionally, a dual network that describes the topological connection relationship among roadways of the pavement network is applied to generalize the spatial weight of pavement segments that constitute the pavement network. A case study was conducted using the networks of the Dongcheng and Chaoyang districts in a large city in China to demonstrate the applicability of the proposed methodology. The results demonstrated the optimal marginal reliability rule, and the inflection point was identified. The increase in marginal reliability induced the generation of efficient M&R options after the inflection point. The budget was applied to implement the M&R options by employing the optimal marginal reliability. Furthermore, the M&R options of the pavement network shifted from light rehabilitation to preventive maintenance. Sensitivity analysis of weight coefficient 𝜃 in the integrated M&R budget framework for large-scale pavement networks shows higher 𝜃 (prioritizing spatial weights) achieves maximum reliability benefit with less budget, verifying spatial weights’ value in enhancing budget efficiency. The study findings provide valuable insights to transportation agencies in terms of implementing different M&R options under various budget conditions.]]></description>
      <pubDate>Wed, 24 Jun 2026 13:22:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673013</guid>
    </item>
    <item>
      <title>Budget feasible strategy-proof mechanism design for elastic mobile service in vehicle computing</title>
      <link>https://trid.trb.org/View/2614567</link>
      <description><![CDATA[In the context of the Internet of Things, edge computing can no longer fully meet the needs of the diversified task requirements; hence, vehicle computing has been developed. Concerning the new feature of intelligent vehicles (IVs) mobility, a novel elastic mobile service model is proposed for vehicle computing, where vehicle computing dynamically changes computing power according to the demands. This paper considers the elastic mobile service in two communication scenarios. The first is that IVs from different areas quickly move to the area with insufficient computing power, and the second is that IVs move to the specified area by the user. Owing to the heterogeneous costs of IVs, the pricing is based on the auction. Our goal is to maximize the total value, which is the sum of the values of all tasks running on the IVs. The problem is formulated as an integer linear program and proven NP-hard. Then, a budget-feasible strategy-proof mechanism is proposed to allocate IVs one by one based on the marginal contribution. We first show that the proposed mechanism achieves strategy-proofness, individual rationality, consumer sovereignty, and budget balance, which drives the system into equilibrium. The approximation ratio of the proposed mechanism is analyzed. The experimental results show that under budget constraints, the proposed mechanism not only approaches the optimal performance in terms of total value but also effectively allocates tasks to provide the elastic mobile service.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:59:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2614567</guid>
    </item>
    <item>
      <title>Reliability-based crash risk analysis for prioritizing safety projects</title>
      <link>https://trid.trb.org/View/2652397</link>
      <description><![CDATA[Social crash costs and the limitations of allocated highway safety budgets are two key factors influencing the prioritization of highway safety projects. To ensure the efficient use of these budgets, expenditures must be optimized to achieve the highest possible impact. This study presents a framework that uses the Empirical Bayesian (EB) method to develop probabilistic models of social crash costs. The framework calculates the exceedance probability of crash costs for various collision types, including rare events, through the Monte Carlo method, a technique within reliability analysis. The framework is applied to Highway 36 in Iran, which spans 186 km. Utilizing a reliability-based risk analysis, all highway segments—comprising 34 tangent and 30 horizontal curve segments—were prioritized for safety improvements. A key outcome of this study, beyond project prioritization, is the creation of exceedance probability curves for social crash costs across different collision types. These curves offer a valuable foundation for informed decision-making in risk mitigation.]]></description>
      <pubDate>Thu, 26 Mar 2026 16:59:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652397</guid>
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