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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>Risk analysis of domino effect of leakage accident of petrochemical pipeline based on analytic hierarchy process and fuzzy fault tree analysis</title>
      <link>https://trid.trb.org/View/2648945</link>
      <description><![CDATA[Pipeline transportation is a prevalent method for the conveyance of petrochemical fluids. Pipeline leakage can lead to severe consequences, such as fire or explosion accidents. Unlike traditional methods, which take pipeline leakage/failure as the top event of fault tree analysis (FTA), this paper studies the domino effect of pipeline leakage with the top event of the fire or explosion accident caused by petrochemical pipeline leakage. The risk assessment is based on the hybrid method combining the Analysis Hierarchy Process (AHP) and fuzzy theory. AHP is established to evaluate the ability of experts and fuzzy theory is used to convert the experts’ opinions into occurrence probabilities of basic events. The effectiveness of the approach is demonstrated by performing a risk assessment in a long-distance oil pipeline. Qualitative analysis results based on the structural importance indicated that the formation condition of the combustible mixture has the largest structural importance. Quantitative analysis results showed that the proposed method, based on AHP and fuzzy theory, can evaluate the risk of the pipeline domino effect, which can be used to support risk management and decision-making for petrochemical pipelines.]]></description>
      <pubDate>Fri, 27 Mar 2026 10:20:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2648945</guid>
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    <item>
      <title>Hazardous Freight Crash Causal Factors Identification Using Fault Tree-Based Bayesian Network</title>
      <link>https://trid.trb.org/View/2613340</link>
      <description><![CDATA[The demand for hazardous freight transportation grows alongside global economic development and industrial modernization, increasing roadway safety risks. Existing studies analyze the causes of crashes but often overlook the distinctions between traffic crashes and non-traffic incidents, introducing causal bias. This study examines crashes of varying severities and causes to propose targeted countermeasures. A fault tree model identified crashes/incidents as top events, with driver, vehicle, road, environment, and management factors as intermediates, further divided into 30 basic events. The model was then converted into a Bayesian network, with parameter learning via the Expectation Maximization algorithm and posterior probabilistic reasoning using the joint tree inference algorithm. Results highlight that non-traffic incidents arise from poor risk identification, vehicle fires, and tire issues. Severe traffic crashes stem from speed control issues, inadequate training, inappropriate loading, and illegal transportation. Findings offer a quantitative, scientific basis to inform policy-making and operational management for improved hazardous freight transportation safety.]]></description>
      <pubDate>Fri, 20 Mar 2026 14:10:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613340</guid>
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    <item>
      <title>Impact analysis of dangerous goods-related aviation accidents on safety regulations and operational procedures</title>
      <link>https://trid.trb.org/View/2627802</link>
      <description><![CDATA[Dangerous goods represent substances that pose risks due to their toxic, flammable, explosive, or corrosive properties. They require strict international measures to ensure safe handling and transportation. Although accidents and incidents involving dangerous goods in aviation are relatively rare, their consequences can be severe, often resulting from improper packaging, misdeclaration, or mishandling. Analysis of dangerous goods-related accidents, including fires caused by lithium batteries, chemical reactions, and fuel vapor explosions, emphasizes its continuing threats to aviation safety. Dangerous goods-related events have driven global regulators to enhance technical instructions, packaging and labelling standards, and require comprehensive staff training. Operational practices have also evolved, with obligatory installation of fire detection and suppression systems, improved cargo ventilation, and adoption of advances tracking technologies to prevent and manage such incidents effectively. Detailed protocols for crews to address dangerous goods emergencies, is also provided and regularly updated. The continuous improvement of regulations and operational practices shows the commitment of the aviation industry to mitigate dangerous goods-related risks, in order to protect passengers, crew, property, and the environment. This paper examines the significant impact of dangerous goods-related aviation accidents on the evolution of safety regulations and operational procedures.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2627802</guid>
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    <item>
      <title>Investigating patterns and causes of struck-by accidents in roadway construction projects</title>
      <link>https://trid.trb.org/View/2630553</link>
      <description><![CDATA[Struck-by accidents involving vehicle intrusions and heavy equipment in construction work zones, particularly utility systems, highways, streets and bridge projects, pose significant safety risks. These incidents often resulting from interactions between workers, machinery and vehicles, frequently lead to serious or fatal injuries. This study utilized a comprehensive dataset of 3,268 OSHA accident reports from 2000 to 2022 to examine patterns, contributing factors, and the severity of struck-by accidents. Through a multi-method approach combining descriptive statistics, chi-square analysis, and predictive modeling (logistic regression, Random Forest, and Gradient Boosting), the study addressed four core research questions focused on frequency, risk factor association, and injury severity prediction. The results revealed that struck-by incidents comprised over 50% of all reported construction work zone accidents and accounted for nearly 70% of related fatalities. Risk factors significantly associated with fatality included injury nature (e.g., amputation, asphyxia), worker occupation (e.g., construction laborers, highway maintenance workers), project type, cost, time of day, and specific activities such as excavation and trenching. While logistic regression offered interpretability (AUC-ROC = 0.74487), ensemble models provided greater predictive accuracy (AUC-ROC = 0.78–0.79). It also underscores the need for standardized data reporting to enhance future modeling efforts.]]></description>
      <pubDate>Fri, 09 Jan 2026 16:58:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630553</guid>
    </item>
    <item>
      <title>Team Diversity in European Air Traffic Management Teams: A New Factor Relevant to Safety?</title>
      <link>https://trid.trb.org/View/2572697</link>
      <description><![CDATA[Team diversity refers to all visible and invisible traits which make people unique, leading individuals to the perception that another person is different from themselves (Ely & Thomas, 1996; Van Knippenberg et al., 2004). In a team various diversity category may create hypothetical dividing lines, called faultlines, that split the team into subgroups affecting its cohesion and efficiency (Spoelma & Ellis, 2017; van Knippenberg et al., 2011a; Wegge et al., 2020). Even though team diversity and faultlines influence team’s performance (Martins & Sohn, 2021; van Knippenberg et al., 2011b) they have not yet been well studied in aviation teams even though human factors are found to be a leading cause in aviation accidents (Kelly & Efthymiou, 2019; Kharoufah et al., 2018). This paper aims to investigate the diversity changes in European Air Traffic Management (ATM) teams, identify the most saliant faultlines in ATM teams, and consider diversity relevance to safety climate. To answer the research questions, 28 semi-structured interviews were conducted with participants from 11 European Air Traffic Control (ATC) Centers. Thematic analysis was applied to the transcribed and pseudonymized interviews. The study found that the most saliant faultlines in ATM teams are gender, age, experience, and management. Furthermore, the results showed that while most of the people perceived diversity as relevant to the safety climate of the team, the phenomenon is not reflected yet in ATC work practices neither in team resource management, nor in supervisory training. This paper proposes that further studying of the influence of team diversity on aviation work could contribute to improving safety culture. The qualitative findings should be further tested by quantitative controlled experiments to understand the mechanisms through which diversity may interplay with safety, decision-making and organizational climate in the ATM industry. In addition, given the importance of emotional intelligence on safety (Bates, 2023), this paper calls for further research on ATM teams’ diversity faultlines, identifying new training needs, and decision-making practices that include diversity as a factor in human factor studies. Findings from these studies could be also beneficial for other high-risk organizations.]]></description>
      <pubDate>Mon, 08 Dec 2025 15:19:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572697</guid>
    </item>
    <item>
      <title>A STAMP-Informed framework for classifying interorganizational risk management challenges in ports</title>
      <link>https://trid.trb.org/View/2602773</link>
      <description><![CDATA[Interorganizational Risk Management (IRM) is critical in port operations, where actors such as port authorities, shipping companies, and terminal operators must coordinate safety and risk governance across organizational boundaries. Traditional risk management approaches often neglect how failures emerge from systemic misalignments in control structures, feedback mechanisms, and interorganizational coordination. This study systematically classifies IRM challenges in port settings using the Systems-Theoretic Accident Model and Processes (STAMP) as an analytical lens to explore how such challenges are conceptualized in existing literature. Rather than modeling specific control systems, the authors map IRM challenges to STAMP components to identify commonly disrupted control functions. Based on a structured analysis of 50 peer-reviewed studies published between 2014 and 2024, the authors extract 233 quotes describing IRM challenges. Using a hybrid methodology that combines inductive coding, semantic clustering supported by natural language processing (NLP), and deductive mapping to STAMP, the authors identify 14 IRM challenge categories. These are grouped into three control layers: Strategic, Operative, and Adaptive. Each category is linked to specific STAMP control structure components to illustrate patterns in how interorganizational coordination is affected. Findings show that IRM challenges are concentrated in areas involving feedback loops, control logic, and constraints. This approach offers a novel system-theoretic classification of IRM challenges and contributes a transparent, replicable method for analyzing challenges in complex organizational networks. The paper also identifies future research opportunities, including expert validation, cross-regional comparison, and the use of organizational mechanisms to support IRM in ports.]]></description>
      <pubDate>Mon, 27 Oct 2025 09:34:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2602773</guid>
    </item>
    <item>
      <title>Residual ultimate strength of a container ship under dropped object impact: numerical simulations and empirical formulations</title>
      <link>https://trid.trb.org/View/2599120</link>
      <description><![CDATA[Accidentally dropped objects during the cargo handling represent a significant threat to container vessels' structural integrity and operational safety. Such incidents can occur for several reasons, including equipment failure, human error, bad weather, or accidents during lifting operations, and moving cargo from supply vessels to container vessels or discharging containers at port facilities. A collision with a heavy object can cause localized structural damage, reducing the vessel's residual strength. This study aims to present a series of numerical investigations concerning the residual longitudinal strength of container ships when subjected to collisions with dropped containers via advanced numerical analyses and empirical modeling. Based on the analysis conducted on ABAQUS, finite element analysis (FEA) is employed to study the structural response resulting from the application of sagging and hogging moments, with validation against experimental data. Extensive parametric studies are carried out to investigate different impacts based on drop height, impact location, boundary condition, and container mass. Based on numerical results, new empirical formulations are derived to predict the container ships' ultimate bending strength reduction. The proposed models provide important information for ship designers and operators to reduce the risk of dropped object incidents on ships. These findings enhance maritime safety by improving structural assessment methodologies and guiding design.]]></description>
      <pubDate>Wed, 24 Sep 2025 15:31:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599120</guid>
    </item>
    <item>
      <title>Improving warehouse operations efficiency in a retailer: a case study employing a systemic approach</title>
      <link>https://trid.trb.org/View/2550913</link>
      <description><![CDATA[Researchers continuously develop effective approaches to improve warehouse management systems. This study presents an efficient warehouse management framework that aims to improve the warehouse layout planning, smooth the flow of warehouse operations and facilitate the efficiency in accessing and deploying of materials, while at the same time establishing additional safety procedures in retail warehouses. With the help of empirical data collected from a case study company that manufactures perfumes and aromatic products based in Jeddah, Saudi Arabia, a framework for developing and refining an optimal warehouse management system is outlined. The suggested framework was then implemented at the case study company which resulted in a revised warehouse layout plan, a reorganised inventory, and improved material handling operations. The study observed for three months the performance of operations under the revised warehouse layout. The evaluation concluded with a risk assessment to ensure a safe and secure warehouse working environment.]]></description>
      <pubDate>Thu, 26 Jun 2025 11:42:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2550913</guid>
    </item>
    <item>
      <title>How to Reduce Work-Related Road Deaths? Driver Fatigue Monitoring – Case Study</title>
      <link>https://trid.trb.org/View/2535009</link>
      <description><![CDATA[Work-related road deaths are the leading cause of occupational death. These traffic accidents contribute to at least one quarter all work-related deaths. Key risk factors associated with driving for work are driver fatigue and speeding. Driver fatigue is the growing problem of the new era. Due to traffic exposure, commercial vehicles are identified as a particularly risky category. According to traffic accident data, depending on the country, the percentage of traffic accidents caused by driver fatigue ranges up to 40%. In this paper, the authors used a unique procedure for identifying fatigue based on eleven factors, using expert knowledge, budget allocation and the composite rank method. The case study was realised in the Republic of Serbia, which is a country with a huge professional drivers deficiency problem. The main objective of this paper is to present an approach to reducing work-related road deaths to reach vision zero, based on a model for identifying commercial vehicle driver fatigue before the drivers start their shift. The advantage of this model is that it does not distract the driver in any way while driving and is based on objective data. It does not require recording the driver with a camera or hooking up to an electrode to record heart or brain activity.]]></description>
      <pubDate>Wed, 07 May 2025 15:54:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2535009</guid>
    </item>
    <item>
      <title>Developing a deep reinforcement learning model for safety risk prediction at subway construction sites</title>
      <link>https://trid.trb.org/View/2506624</link>
      <description><![CDATA[Underground construction work is heavily affected by surrounding hydrogeology, adjacent pipelines, and existing subway lines, which can lead to a high degree of uncertainty and generate safety risk on site. In order to overcome rigid thinking of causal factors within a structured framework and incorporate features of different accidents, this study adopted grounded theory for the investigation on factors contributing to workplace accidents in subway construction. The deep reinforcement learning model of double deep Q-network (DDQN) was developed for predicting subway construction safety risk, which integrated the advantage of reinforcement learning in decision making with the advantage of deep learning in objection perception. The findings denoted that DDQN performed better than other machine learning models inclusive of random forest, extreme gradient boosting, k-nearest neighbor, and support vector machine. Contributing factors relevant to subway construction accidents were quantitatively analyzed using permutation importance of attributes. It was beneficial for determining how the 37 contributing factors had negative effects on subway construction safety risk. Safety measures for risk reduction and controlling could be optimized according to permutation importance of individual contributing factor, which paved a new way for the promotion of safety management performance at subway construction sites.]]></description>
      <pubDate>Tue, 25 Mar 2025 16:57:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2506624</guid>
    </item>
    <item>
      <title>Predictive Assessment of the Technical and Economic Effect of the Implementation of Automated Production Risk Management Systems at the Shipyard</title>
      <link>https://trid.trb.org/View/2407698</link>
      <description><![CDATA[The article briefly describes the structure of the managing industrial risks process at a shipyard, a block diagram of the automated risk management system algorithm developed by the authors, and a general description of the operation process in this system. It is noted that in addition to the direct economic effect, the introduction of automated risk management systems makes it possible to meet modern quality and management standards for the shipyard, thereby increasing its attractiveness for investment and competitiveness in the face of tough competition. To determine the predicted economic effect from the production risk management system automation, the authors took into account the approximate cost figures. Such a predictive assessment of the technical and economic effect makes it possible to assess the attractiveness of automation of the risk management system quickly and with a sufficient degree of accuracy from the point of view of: increasing the efficiency of working with risks; accelerating the process of their quantitative assessment; formation of corrective actions and management decisions. It is noted that the design and implementation of automated risk management systems at shipyards not only simplifies the process of managing industrial risks greatly, makes it possible to quickly check the validity of the decisions made earlier or currently taken in terms of the occurrence of industrial risks, significantly saving labor and time resources at the same time, but it is also an extremely profitable solution from the economy point of view.]]></description>
      <pubDate>Wed, 19 Mar 2025 10:12:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407698</guid>
    </item>
    <item>
      <title>Safety barrier performance assessment based on multi-phase Markov model and EPN: Application to FPSO gas leakage</title>
      <link>https://trid.trb.org/View/2510559</link>
      <description><![CDATA[The FPSO topside module has a risk of gas leakage during oil and gas treatment, and safety barriers are required to prevent accidents from escalating and avoid catastrophic consequences. To ensure the high reliability of safety barriers in responding to accidents, it is necessary to conduct performance assessment to quantify the performance of safety barriers during operation. This study proposes a safety barrier performance assessment framework based on multi-phase Markov model and event Petri net (EPN) for dynamic performance analysis of safety barriers and assessment of the probability of gas leakage accident escalation. First, identify the safety barriers involved in FPSO gas leakage, and establish the alarm interlocking logic of the safety barriers. Then, the multi-phase Markov model is used to evaluate the availability of safety barriers, which can deal with the dynamic effects of continuous testing and maintenance on barrier performance. Finally, the EPN model of FPSO gas leakage accident evolution is established based on the interlocking logic of safety barriers, and the probability of accident escalation is quantitatively evaluated by combining the availability and effectiveness of safety barriers. The implementation process of the proposed method is illustrated by a case study, and the impact of different test strategies and characteristic parameters on the safety barrier performance is explored through relevant analysis. The assessment results can provide useful references for improving the performance of safety barriers, and have important practical significance for reducing the accident escalation probability and ensuring the safety production of FPSO.]]></description>
      <pubDate>Wed, 19 Feb 2025 17:11:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2510559</guid>
    </item>
    <item>
      <title>Transport, mobility, and workplace location : models and applications</title>
      <link>https://trid.trb.org/View/2491160</link>
      <description><![CDATA[Travel demand analysis is one of the core constituents of transportation studies. The required insight to maintain and develop a sustainable transportation system, in addition to learning from previous research globally and locally, is generated from studying the effects of previous policies, investigating future possibilities and potential outcomes, and describing the current situation. The objective of the thesis is to use urban modeling and decision support methods to contribute to the knowledge that improves decision making for a sustainable society. In this thesis, three of the papers focus on implementation and application of a dynamic model of movement for prediction and forecast of workplace demand and accessibility, and for a trip chaining problem. This framework formulates movement through a Markov chain and solves it by using the Bellman equation which by the assumption of IID Gumbel error terms turns into a recursive logit, which reflects dynamic and directional nature of time in modeling movement. This approach is used for modeling a workplace choice model and accessibility to work (Paper 1., that is applied for workplace allocation in a scenario planning framework for urban development growth with a 2040 forecasted synthetic population (Paper 3., and a dynamic trip chaining model with flexible number of trips in the chain (Paper 4.. The workplace location choice model is unique as it connects the land use and transport models in a framework that is consistent with random utility maximization approach while respecting forward-looking behavior of individuals and the dynamic and directional nature of time.]]></description>
      <pubDate>Fri, 17 Jan 2025 15:15:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2491160</guid>
    </item>
    <item>
      <title>Manufacturing Algorithm for Machine Grouping Based on Machine Utilization Factors</title>
      <link>https://trid.trb.org/View/1787475</link>
      <description><![CDATA[The absence of a design and manufacturing template that can be used to develop a product is the basis for this paper. A machine grouping algorithm based on machine utilization factors is discussed. The algorithm was developed based on traditional machine grouping models, but has been modified to use the machine utilization factors to group machines into cells. Different floor layouts for a factory are considered and an optimal floor layout is determined. The WPI World Formula SAE manufacturing facility is used as a model to demonstrate the algorithm. The FSAE competition required the design of an optimal factory layout manufacturing 1000 cars/year. Total costs and times of manufacture for each sub-component of the WPI FSAE racecar are determined. These total times and costs are used to develop the machine and labor requirements for a fictitious company producing 1000 racecars/year. The proposed algorithm is used to group machines into cells on the factory floor. The algorithm is capable of handling small machine groupings. A machine utilization factor is used to determine machine placements rather than a binary mode of machine selection that can be found in standard literature.]]></description>
      <pubDate>Thu, 16 Jan 2025 09:09:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/1787475</guid>
    </item>
    <item>
      <title>Occupational Health and Safety Practices and Supplier Selection in the South African Mining and Construction Industry</title>
      <link>https://trid.trb.org/View/2407518</link>
      <description><![CDATA[The South African Mining and Construction industries are critical in driving the country’s economy. However, both industries are notorious for the high rate of fatal incidents and other workplace accidents. As a result, the Occupational Health and Safety (OHS) performance of these industries has attracted the attention of the government, investors and other stakeholders. A vital consideration typically considered in appointing suppliers in the mining and construction industries is their adherence to OHS. However, no single universally accepted standard for selecting suppliers exists. Some of the most popular criteria in supplier selection include price, quality and the capacity to deliver on time. This study explored the role of the implementation of OHS on supplier selection and competitive advantage in the mining and construction industries in South Africa. A qualitative method was followed in which semi-structured interviews were conducted with professionals representing South African mining and construction firms. Content analysis was used to develop answers to the research questions.The study’s findings show that the implementation level of OHS practices varies between firms, even for businesses operating in the same industry. The performance of OHS does not always shape supplier selection processes but influences competitive advantage. Moreover, supplier selection processes are not always effective in ensuring that OHS-compliant suppliers are selected. The research concludes that OHS is not considered a mandatory criterion when appointing suppliers. Hence, there are inconsistencies in supplier selection processes characterised by a lack of enforcement of OHS legal obligations for suppliers.]]></description>
      <pubDate>Mon, 16 Dec 2024 11:59:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407518</guid>
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