<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <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>
    </image>
    <item>
      <title>Intelligent Optimization for Designing Resilient Transit Networks Under Multiple Objectives</title>
      <link>https://trid.trb.org/View/2579498</link>
      <description><![CDATA[The European Commission emphasizes mass transit system resilience for a successful shift to sustainable mobility, urging specific actions. Urban resilience, emphasizing public transport performance amid various hazards, prioritizes redundancy through network restructuring to enhance disruption resilience. This study aims to design efficient transit networks, while also enhancing resilience against link failures by maximizing alternative paths for passengers. In the multi-objective setting considered, the goal is to obtain non-dominated solutions, considering two distinct objectives: maximizing path redundancy and minimizing passenger inconvenience, captured by a weighted score of average travel time and transfer shares. To obtain high-quality results, this study leverages reinforcement learning (RL) and multi-objective Particle Swarm Optimization (MOPSO), under the novel concept of intelligent optimization, where a learning component is used to guide the search. The proposed MOQLPSO exploits an adaptive search mechanism, with particles acting as self-interested agents within the solution space, incorporating dominance rules within the RL reward function. Benchmarking against a naive MOPSO version on two literature-based networks reveals the proposed approach's superiority. Results highlight trade-offs between efficiency and resilience, demonstrating denser and higher-quality pareto fronts in less computational time. The study underscores the importance of the reward function and emphasizes benchmarking as crucial for advancing the proposed concept.]]></description>
      <pubDate>Wed, 12 Aug 2026 17:07:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579498</guid>
    </item>
    <item>
      <title>Transport Network Planning and Analysis Decision-Support Tool for South Asia</title>
      <link>https://trid.trb.org/View/2671824</link>
      <description><![CDATA[A versatile tool is being developed to support climate resilience investment planning in the transport sector for South Asian countries. The tool utilizes readily available datasets, incorporates rapid hazard mapping, integrates multiple infrastructure modelling perspectives, combines methods of varying sophistication, and facilitates large-scale assessment of socio-economic indicators. It has been designed to offer a tailored decision-making experience, accommodating different strategic risk management priorities, decision styles, and risk appetites. Applicable to diverse geographical regions and hazard environments, it aids in identifying vulnerability hotspots within a transport network, enabling prioritized interventions. It also assists in estimating climate adaptation funds, analyzing post-disaster network performance, and planning for redundancies. Ultimately, it supports users in planning network-level upgrades for climate resilience, while minimizing the expected losses and ensuring cost-efficiency in the decision-making process.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671824</guid>
    </item>
    <item>
      <title>A Review of Tools and Guidance for Undertaking Climate Change Risk Assessments for the Transport Sector in Britain</title>
      <link>https://trid.trb.org/View/2671821</link>
      <description><![CDATA[This paper provides a review of resources available for undertaking climate change risk assessments for the transport sector in Britain. The authors undertook research to identify tools and guidance currently available, and used by, all parts of the British transport sector in assessing the risks from climate change to transport infrastructure and operations. Through gathering evidence, expert opinion, and stakeholder engagement a comprehensive list was prepared that covered both physical and transition risks to transport. The review was undertaken in March–July 2023. The authors are aware this is a fast-moving area and anticipate that new tools and guidance may be available at the time of publication. No one tool or guidance was identified that provided output that could be considered best practice for all transport sectors (rail, highways, aviation and ports). However, this paper lays out which items are potentially useful for British transport organisations at different stages and levels of maturity. The paper also highlights where there are gaps in the understanding, usage or existence of tools and guidance and provides recommendations on how these gaps may be filled.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671821</guid>
    </item>
    <item>
      <title>Identification of Strategic Vulnerabilities In The National Freight Network</title>
      <link>https://trid.trb.org/View/2703933</link>
      <description><![CDATA[This report investigates vulnerabilities in New Zealand’s strategic road network that could cause disruptions. The project identifies critical vulnerabilities that impact the national freight network and strategic supply chains, incurring significant costs to end users, and identifies mitigation activities to reduce these vulnerabilities. The analysis includes crucial nodes and linkages, predicting the impact of their unavailability on supply chains. The report highlights the importance of competition in the freight sector, noting that an oligopolistic structure often drives inefficiencies and increased costs. We identify short-term (up to 1 day), medium-term (up to 1 month) and long-term (3 months or longer) closure timeframes as defined by users, outlining their respective impacts and contingency plans. In short-term closures, contingency plans typically involve dynamic decisions, carrying safety stock and delaying shipments. Medium-term closures see a shift towards using rail and sea transport and offshore storage in containers for warehousing. Long-term closures emphasise sea transport and adaptive decision making even more, with significant variations in response based on the specific business and level of uncertainty involved. We use economic impact computable general equilibrium modelling and stakeholder engagement to inform the need to strengthen or build redundancy into the freight system, focusing on road transport. Findings indicate regional variations in freight cost impacts and suggest the importance of adaptive planning for deeply uncertain events. The report emphasises economic impacts, not financial costs, and provides insights into contingency plans and their effectiveness in different scenarios.]]></description>
      <pubDate>Tue, 02 Jun 2026 11:02:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703933</guid>
    </item>
    <item>
      <title>Optimizing Alternative Air Traffic Service Routes for Airport Disruption Contingency Management</title>
      <link>https://trid.trb.org/View/2665619</link>
      <description><![CDATA[Flight disruptions due to destination airport unavailability present significant challenges for air traffic management and airline operations. These situations may lead to cascading delays, increased fuel consumption, and reduced passenger satisfaction. A key response strategy is the timely identification of alternative air traffic services (ATS) routes to suitable diversion airports while ensuring flight safety and operational continuity. However, existing diversion approaches often rely on static contingency plans or real-time decisions by air traffic controllers, which may not perform well under dynamic conditions. To address this, a robust multi-objective optimization model based on the A-star algorithm is proposed to dynamically identify optimal alternative air traffic services routes when the planned destination becomes inaccessible. The model accounts for multiple objectives, including route efficiency, safety, and operational feasibility, across pre-tactical and tactical phases of air traffic flow management. By integrating airspace constraints and traffic flow considerations, the model supports adaptive, data-informed decision-making. Simulation results demonstrate the model’s ability to reduce network disruptions and support safe, efficient diversions under various traffic scenarios. This study contributes to enhancing the resilience of the air transportation system and provides a foundation for future integration into intelligent air traffic management tools and decision support systems.]]></description>
      <pubDate>Fri, 27 Feb 2026 17:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665619</guid>
    </item>
    <item>
      <title>Research on Ground Public Transport Transfer Strategies under the Failure of Key Stations in Urban Rail Transit Networks</title>
      <link>https://trid.trb.org/View/2613210</link>
      <description><![CDATA[With the continuous development of urban public transportation, rail transit networks are becoming more integrated. However, emergencies that damage key stations, which connect multiple lines and handle large passenger flows, can paralyze the entire system, severely disrupting travel. This study focuses on the Xixian New Area rail network. A node importance evaluation model based on topology and passenger flow characteristics is developed, incorporating objective weighting and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for station ranking. The paper also simulates failure scenarios of key stations and proposes a bidirectional multi-mode transfer model. Compared to traditional single-mode transfer models, the multi-mode approach reduces overall costs by 6.44%, optimizing the bus transfer strategy. This work provides scientific support for improving the resilience of critical stations in urban rail networks.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613210</guid>
    </item>
    <item>
      <title>Exploring the effects of space weather-caused satellite navigation failure on fuel consumption and aircraft emissions: A simulated study</title>
      <link>https://trid.trb.org/View/2612939</link>
      <description><![CDATA[Satellite navigation provides aircraft with precise positioning and navigation services. However, space weather can induce ionospheric irregularities and elevate the total electron content in the ionosphere, causing satellite navigation failure. Consequently, aircraft will navigate using ground aids and be disabled to fly along Great Circle Routes, increasing flight distance, fuel consumption, and aircraft emissions. To explore the effects of satellite navigation failure on flight operation, this study simulates satellite navigation failure scenarios and proposes Air Traffic Management (ATM) solutions. Specifically, the first step designs the ground aid-based shortest path using the Dijkstra algorithm, followed by the calculations of fuel consumption and aircraft emissions using the Base of Aircraft Data (BADA) and the aircraft Engine Emissions Databank (EEDB), respectively. Based on the collected 11,037 U.S. flight plans on 5 February 2024 (UTC), simulations show that a single-day satellite navigation failure can result in an increase of flight distances by 2,371,777 km, fuel consumption of 7176 tons, and CO₂ emission of 22,604 tons. While this study focuses on simulations in the U.S., the findings have a broad implication and can serve as a framework to address space weather effects on aviation in other regions of the world.]]></description>
      <pubDate>Wed, 14 Jan 2026 17:40:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2612939</guid>
    </item>
    <item>
      <title>Pre-disaster evacuation transport network design under uncertain demand and connectivity reliability: A novel bi-level programming model</title>
      <link>https://trid.trb.org/View/2587278</link>
      <description><![CDATA[Evacuation transport network design plays a critical role in the efficiency of emergency response. This research proposes a novel bi-level nonlinear programming model for the pre-flood evacuation transport network design. The model considers both uncertainties of demand and network connectivity reliability. An upper-level model is developed with the minimum total evacuation time and maximum network connectivity reliability, while the lower-level model is a traffic assignment model that describes people’s evacuation route choice behavior. For the uncertain network connectivity reliability, an approach to quantify it based on percolation theory is proposed. For the uncertain demand, an approach to transform it into a solvable form based on Robust Optimization (RO) is proposed. Furthermore, the lower-level model introduces the regret-risk utility function as its objective function and proves its applicability. An equilibrium condition is proposed to improve the Logit model based on the regret-risk utility function. For the solution of this model, an Improved Genetic Algorithm combined with Non-dominated Sorting Genetic Algorithm II(IGA-NSGA-II) is designed. Then, the Nguyen-Dupuis network is used to demonstrate that the approach developed in this paper can be used to solve the bi-level nonlinear programming model and to obtain a satisfactory design solution. Further, a parameter sensitivity analysis is shown to study the impact of the risk aversion parameter and regret aversion parameter in the regret-risk utility function. Finally, the Central Coast region of New South Wales, Australia is used as a case study, and the research output will help government authorities to plan and design a pre-flood evacuation transport network, especially to answer the questions of “Where to build potential roads?”, “How much budget is needed?”, “How long does it take to evacuate?”, and “How reliable is the network connectivity?”.]]></description>
      <pubDate>Wed, 17 Sep 2025 10:55:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2587278</guid>
    </item>
    <item>
      <title>A Platform for Safe Operations of Unmanned Aircraft Systems in Critical Areas</title>
      <link>https://trid.trb.org/View/2557324</link>
      <description><![CDATA[The use of unmanned aerial system (UAS) in congested airspace and/or in the proximity of critical infrastructure poses several challenges as far as safe and secure operations are concerned. The paper provides a detailed description of the architecture and workflow of a platform for UAS traffic management (UTM), designed to pave the way for increased, improved and safer UAS operations in the civil airspace. In particular, access to low-altitude airspace for UAS operations is managed, while facilitating the implementation of beyond visual line-of-sight (BVLOS) operations, and ensuring a safe and efficient integration of UAS into both controlled and uncontrolled airspace. Detection and management of unidentified or uncooperative UAS’s is also taken care of. To this end, an architecture based on three interacting layers is proposed, with the air traffic control at the highest level, the UAS operator(s) at the bottom, and a UAS service supplier acting as an interface. The platform, with its physical and digital elements, guarantees the effective and efficient interaction among these three layers, including management of contingency scenarios, which require a variation of admissible flight volumes for UAS operations and/or fast trajectory re-planning. The platform, developed within a research project which involved several partners, was tested in a relevant operational scenario at the Grottaglie–Taranto airport in Italy. The operators involved in the tests provided positive feedback on the services provided by the platform and the usability of the interfaces, while also making suggestions for adding new features in future developments.]]></description>
      <pubDate>Wed, 11 Jun 2025 10:52:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2557324</guid>
    </item>
    <item>
      <title>Risk Identification, Prioritization, and Mapping for Early Construction Cost Contingency in Transportation Infrastructure Projects</title>
      <link>https://trid.trb.org/View/2402318</link>
      <description><![CDATA[State Departments of Transportation (DOTs) require reliable early construction cost estimates for project budgeting. Typically, project budgets are established early in the development process before finalizing a project’s scope of work. Due to the inherent incompleteness of scope definition and specifications, early estimates of construction costs are hardly accurate, necessitating the estimation and usage of a contingency. However, most DOTs use a predetermined approach to estimate construction cost contingencies without considering project-specific risks and uncertainties. Furthermore, few research studies have been focused on improving construction cost contingency estimation in the early phases. This study contributes to the body of knowledge by laying the initial foundation for a project-specific and risk-driven approach for DOTs. Significant risks affecting construction cost contingencies were identified, prioritized, and then mapped with common project types by applying a hybrid research methodology of reviewing and analyzing DOT manuals, risk checklists, and risk registers and conducting and analyzing questionnaire surveys with DOT experts. The subjectivity and vagueness of survey responses affecting risk prioritization were addressed using fuzzy sets and fuzzy logic approaches.]]></description>
      <pubDate>Wed, 18 Sep 2024 09:41:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2402318</guid>
    </item>
    <item>
      <title>Streamlining Work Planning for County Maintenance Workforces
</title>
      <link>https://trid.trb.org/View/2427614</link>
      <description><![CDATA[Ohio Department of Transportation (ODOT) County Maintenance Staff face complex challenges in coordinating, scheduling, and documenting work conducted by crews. While work assignments ultimately must be formally documented, the steps taken to finalize that documentation vary greatly from garage to garage, are full of redundancies, and open to potential missteps. Methods currently utilized by County Garage personnel to track activities span from emails, post-it-notes, dry erase boards, calendars, spreadsheets, and notes on paper. County Garage Managers develop work plans on a daily/weekly/monthly/quarterly and annual basis. Activities from these plans are assigned as tasks to each crew based on specific days/weeks to accomplish projects in a timely manner. However, maintenance forces are often redirected from scheduled work to address roadway emergencies such as accidents, vehicle fires, roadway flooding, fallen trees, lost tractor-trailer loads, slips, calls from local law enforcement and/or emergency responders for maintenance of traffic or other assistance, calls from the public to report issues, and so forth. When these emergencies arise, the work originally scheduled to take place that day does not occur, and it must be rescheduled to another day. Given the ad-hoc tracking of assignments, it is difficult to ensure tasks are not lost, all work that needs to be rescheduled is addressed appropriately, and formalized documentation of the activities that took place occurs. 

The goal of this research is to streamline maintenance work planning processes for county garage staff.           ]]></description>
      <pubDate>Wed, 11 Sep 2024 14:42:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2427614</guid>
    </item>
    <item>
      <title>Supply chain disruption for crude oil due to the effect of COVID-19 pandemic: evidence from Vietnam</title>
      <link>https://trid.trb.org/View/2406590</link>
      <description><![CDATA[The operation of the crude oil supply chain under the influence of the pandemic has not been extensively examined, despite its importance as a strategic commodity. Based on a powerful simulation model using real-time data parameters, this study investigates the effects of a worldwide pandemic on the crude oil supply chain. The study indicates a downturn in performance and a disruption in the supply chain, as revealed by the outcome of key performance indicators (KPIs). Green field analysis (GFA) experiments are furtherly implemented for different scenarios to investigate the variation of KPIs. As a result, the authors propose contingency rerouting as a potentially proactive solution that can support crude oil businesses in the resilience process during the pandemic.]]></description>
      <pubDate>Thu, 22 Aug 2024 15:11:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2406590</guid>
    </item>
    <item>
      <title>Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network</title>
      <link>https://trid.trb.org/View/2382531</link>
      <description><![CDATA[Using game theory techniques, a three-layer planning model (THLPM) for the defense, attack, and operational layers has been established to address malicious damage to pipelines. A robust planning model was developed for situations with uncertain attack resources. In this model, the defense layer protects critical infrastructure within the network to minimize losses. The attack layer targets unprotected facilities based on the defensive strategy. The operational layer formulates the optimal pipeline transmission strategy based on the decisions of the defense and attack layers. By utilizing the duality theorem, the THLPM is transformed into a two-layer planning problem, which is then linearized and solved using a decomposition algorithm. Taking a specific ring-shaped pipeline network as an example, the study analyzes the significant role of backup pipelines in enhancing system resilience and evaluates the offensive and defensive strategies of THLPM. The effectiveness of THLPM in protecting the network was assessed, showing that when defense and attack resources are invested at levels 3 and 10, respectively, operational costs of the network are reduced by 54.2 % compared to a scenario without any defenses. The methods proposed in this paper are applicable to other pipeline systems.]]></description>
      <pubDate>Mon, 24 Jun 2024 09:26:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2382531</guid>
    </item>
    <item>
      <title>Improvement Project Contingency Planning</title>
      <link>https://trid.trb.org/View/1782610</link>
      <description><![CDATA[The framework for environmentally conscious manufacturing in industry is the life cycle assessment structure developed by the Society of Environmental Toxicology and Chemistry and incorporated into ISO 14000 Environmental Management Systems. Plant managers subject to this standard have the responsibility for environmental improvement projects. Often, applying these projects creates significant risks, particularly if the project is unsuccessful or requires a new technology that has not been widely applied. Plant managers are inherently risk averse. Thus plant managers need to know not only how a project will succeed but also what could happen if the project fails or results in a state different than intended. Based on that knowledge, plants managers prepare contingency plans. This paper illustrates a method by which the optimum plan and all possible contingency plans can be selected based upon minimizing project cost while maximizing project success to arrive at an improvement goal.]]></description>
      <pubDate>Tue, 18 Jun 2024 11:49:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1782610</guid>
    </item>
    <item>
      <title>Risk-aware urban air mobility network design with overflow redundancy</title>
      <link>https://trid.trb.org/View/2381146</link>
      <description><![CDATA[In urban air mobility (UAM), as envisioned by aviation professionals, novel flight vehicles will transport passengers and cargo at low altitudes within urban and suburban areas. To operate in urban environments, precise air traffic management, in particular the management of traffic overflows due to physical and operational disruptions will be critical to ensuring system safety and efficiency. To this end,  authors propose UAM network design with reserve capacity, i.e., a design where alternative landing options and flight corridors are explicitly considered as a means of improving contingency management. Similar redundancy considerations are incorporated in the design of many critical infrastructures, yet remain unexploited in the air transportation literature. In the authors' methodology, their first model how disruptions to a given UAM network might impact on the nominal traffic flow and how this flow might be re-accommodated on an extended network with reserve capacity. Then, through an optimization problem, the authors select the locations and capacities for the backup vertiports with the maximal expected throughput of the extended network over all possible disruption scenarios, while the throughput is the maximal amount of flights that the network can accommodate per unit of time. The authors show that they can obtain the solution for the corresponding bi-level and bi-linear optimization problem by solving a mixed-integer linear program. The authors demonstrate their methodology in the case study using networks from Milwaukee, Atlanta, and Dallas–Fort Worth metropolitan areas and show how the throughput and flexibility of the UAM networks with reserve capacity can outcompete those without.]]></description>
      <pubDate>Fri, 14 Jun 2024 10:26:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2381146</guid>
    </item>
  </channel>
</rss>