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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>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Traffic Simulation and Safety Assessment Requirements for Enhancing Road Safety Prediction Tools</title>
      <link>https://trid.trb.org/View/2580060</link>
      <description><![CDATA[Improving road safety prediction tools requires assessing established traffic simulation tools and safety assessment methods. Enhancing these tools with innovative data sources and methods can significantly reduce urban crashes and their impact. To achieve this, it is imperative to identify the requirements and gaps of relevant stakeholders in terms of professional road safety analysis tools. The present study aims to utilize association rule mining to determine underlying profiles of local stakeholders who are identified as hands-on practitioners. To accomplish this objective, a dedicated survey was conducted, and the data were analyzed to discover meaningful links among stakeholder characteristics through the characteristics mined using the Apriori algorithm. The results provide a quantification of the frequency and relationships between stakeholder responses, indicating connections between education levels, work regions, experience levels, and stakeholder needs related to road safety prediction tools. The study insights offer a quantitative perspective on the interconnections and dependencies among different stakeholder attributes, shedding light on potential patterns and preferences that can guide decision-making in the context of road safety improvements.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580060</guid>
    </item>
    <item>
      <title>A Data-Driven System-Theoretic Bayesian Network Framework for Probabilistic Safety Assessment of Passenger Vessels</title>
      <link>https://trid.trb.org/View/2664341</link>
      <description><![CDATA[Passenger vessel operations present a high-consequence environment where a paradox has emerged: incident frequency is decreasing, yet catastrophic severity is not. This trend exposes the inadequacy of existing risk models, which are typically localized, and reliant on subjective expert elicitation. This study develops a robust, data-driven risk assessment framework by synergizing System-Theoretic Process Analysis (STPA) with a Bayesian Network (BN), grounded in a novel database of 235 official European accident reports. STPA defines the BN’s causal topology, ensuring theoretical coherence and mitigating the epistemic uncertainty and bias of conventional expert-led modeling. Sensitivity analysis reveals the probabilistic primacy of latent systemic precursors, identifying Structural Failure and Defective Maintenance as dominant risk control points. The analysis moves beyond simplistic attributions of “human error”, revealing how operational failures like COLREGs infringements are symptoms of distinct causal pathways dependent on vessel type and operational conditions. The resulting model is a quantitative instrument that identifies the most probable pathways to catastrophe, offering an objective foundation for transitioning from reactive compliance to proactive, data-driven safety governance.]]></description>
      <pubDate>Fri, 01 May 2026 14:31:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664341</guid>
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    <item>
      <title>Human-centered Formal Safety Assessment (FSA) of Pilotage Operations at a Narrow Channel in Indonesia</title>
      <link>https://trid.trb.org/View/2606212</link>
      <description><![CDATA[A pilotage service in Surabaya West Access Channel (SWAC) is mandatory for ships of 500 GT or above, as per the Decree of the Minister of Transportation Number KP 455 of 2016. Due to the high density of traffic in SWAC, this research aimed to evaluate the risk of the pilotage process in terms of Human Reliability Assessment by utilizing Formal Safety Assessment. The probability was estimated based on the Human Error Probability using the method of HEART 4M combined with AHP-Technique for Order Preference by Similarity to Ideal Solution. In contrast, the consequences were gathered based on the historical accident data of the pilotage service. The risk was represented by the risk matrix from the Indonesian Classification Bureau. From the risk matrix, Task 1 and Sub-task 2.3 were categorized as high risks. Five Risk Control Options (RCO) were then proposed and analyzed using the Cost-Benefit Analysis. The recommended RCO for Task 1 is to review the installation and maintenance procedure of the pilot ladder (A03)—with a gross cost of $34,000—which gives a 33% risk reduction. Meanwhile, workload planning and shift rotation adjustment (A03) were recommended for Sub-task 2.3, which had a gross cost of $24,200, and a 31% risk reduction.]]></description>
      <pubDate>Mon, 27 Apr 2026 16:35:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606212</guid>
    </item>
    <item>
      <title>Evaluation of Safety Operational Thresholds for Dynamic Compaction Techniques in Saturated Clayey Sands</title>
      <link>https://trid.trb.org/View/2690965</link>
      <description><![CDATA[The safety and operational thresholds of dynamic compaction techniques in loose clayey sand layers with high groundwater tables were investigated using stress-controlled cyclic triaxial tests. Simulations of intermittent and continuous loading patterns were conducted at confinement pressures of 32 kPa and 53 kPa. Results identified a critical threshold at a cyclic stress ratio greater than 0.35, where the soil transitioned from efficient densification to unstable dilation, accompanied by a spike in the excess pore-water pressure ratio above 0.30. Analysis of the stiffness degradation index established maximum effective cycle limits of 3–5 blows for high-energy intermittent loading and 30 blows for shallow continuous loading. Continuous loading induced significant shear strains at the higher confinement pressure of 53 kPa, dictating depth-dependent operational parameters. The findings supported an operational protocol integrating cumulative and impact-control strategies, analytically linked to the applied energy factor through a site-specific constant derived from geophysical testing.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:58:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2690965</guid>
    </item>
    <item>
      <title>Comprehensive literature review of systemic safety analysis: Trends and development in the maritime sector</title>
      <link>https://trid.trb.org/View/2687085</link>
      <description><![CDATA[With the growing complexity of sociotechnical systems in maritime transportation, system-theoretic approaches such as STPA, STAMP, and CAST have emerged as effective tools through their focus on control problems. To strengthen both theoretical foundations and practical implementation in the industry, it is necessary to review the development of systems theory within this domain, addressing current limitations and outlining future research directions. This article presents a comprehensive review of system-theory applications in maritime transportation, encompassing modelling processes, application areas, and associated challenges. A bibliometric analysis of 76 papers published between 2015 and 2024 was conducted to identify thematic clusters, keywords, and research trends. The review examined how systems theory has been applied, the data sources employed to generate models, and how these methods are integrated with conventional risk assessment approaches. Findings indicate that STPA is the most widely adopted technique in the maritime sector for systems-based safety analysis. More than half of the reviewed studies applied systems theory to risk analysis for autonomous vessels, demonstrating researchers’ confidence in STPA’s capacity to address the challenges of highly complex systems such as autonomous ships. At the same time, there is a growing interest in combining STPA with other methodologies to produce quantifiable results for safety assessments. Consequently, an increasing proportion of studies are evolving towards integration with computational methods, algorithms, and Quantitative Risk Assessment (QRA). Overall, this paper provides a critical overview of system-theory applications in the maritime domain, highlighting limitations while offering recommendations to guide future research and practice.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:57:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2687085</guid>
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    <item>
      <title>Safety assessment of MASS navigational performance in coastal voyage using cognitive reliability and Bayesian best worst approach</title>
      <link>https://trid.trb.org/View/2693312</link>
      <description><![CDATA[Maritime autonomous surface ships (MASS) represent new operational perspective which transfer navigational responsibilities from ship crew/operator to complex automated systems, specifically in coastal sea voyage where marine traffic congestion and environmental conditions pose significant risks. This paper performs a conceptual safety performance assessment of MASS navigation in coastal voyage systematically under cognitive human error prediction and Bayesian best–worst method (BWM). In the paper, while cognitive human error is predicted to quantify human–machine interaction (HMI) vulnerabilities, including perception, decision-making, and supervisory control tasks; the BWM can predict probabilistic priority weights for critical safety key tasks under uncertainty and expert judgment inconsistency. The outcome of the paper is showing that operational key task MFD2 and CC2 has the highest failure probability values affecting safety performance of MASS navigation in coastal voyage. Besides improving safety performance of autonomous ship navigation, the paper will contribute by providing a conceptual framework for determining critical navigational vulnerabilities, prioritizing safety factors, and supervisory strategies for designers, safety inspectors, ship owners, remote control centre operators and safety researchers.]]></description>
      <pubDate>Wed, 22 Apr 2026 14:59:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2693312</guid>
    </item>
    <item>
      <title>Safety Evaluation of Operational Metro Shield Tunnels Using Improved Game Theory and Dynamic Variable Weight Theory</title>
      <link>https://trid.trb.org/View/2660562</link>
      <description><![CDATA[The safety assessment of operational shield tunnels involves complexity, randomness, and uncertainty. Traditional constant weight methods fail to account for the dynamic changes in structural state caused by the interaction among different defects. Therefore, this study proposes a novel safety evaluation framework for operational tunnels by integrating game theory and variable weight theory. This evaluation model is applied to four tunnel sections of Beijing Metro Line 8 and is compared with three other evaluation models (including conventional weighting methods, fuzzy comprehensive evaluation, etc.). Sensitivity analysis identified U31, U32, U33, and U52 as the key indicators affecting the tunnel’s structural safety. On-site investigation results demonstrate that the proposed model provides more accurate evaluations, thereby verifying its feasibility. Furthermore, this study has also established an evaluation framework that is applicable to the comprehensive assessment of the entire tunnel section. Evaluating an entire tunnel section as a single unit may conceal local high-risk areas, leading to inaccurate assessment results. It facilitated managers taking safeguard measures in a timely manner based on the evaluation results and ensuring the safety and reliability of the tunnel structure.]]></description>
      <pubDate>Wed, 22 Apr 2026 14:04:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2660562</guid>
    </item>
    <item>
      <title>Safety Effectiveness of Unsignalized Restricted Crossing U-Turn Intersections in Mississippi using an Empirical Bayes Before–After Study</title>
      <link>https://trid.trb.org/View/2691042</link>
      <description><![CDATA[At-grade intersections on rural high-speed highways can be hazardous, particularly where lower-speed vehicles from minor roads must cross high-speed traffic on major roads. To enhance safety at these junctions, an alternative design known as restricted crossing U-turn (RCUT) has gained considerable interest in recent years. RCUTs can help reduce both the number and severity of crashes by rerouting minor road traffic to downstream U-turns, thereby minimizing crossing conflict points between high-speed and low-speed vehicles. This research aimed to estimate the safety performance following the implementation of eight unsignalized RCUT intersections on rural high-speed highways in Mississippi. The study considered two different definitions of the intersection influence area and employed two distinct methodologies: naïve average annual number of crashes analysis, and a rigorous Empirical Bayes (EB) method. To facilitate the crash modification factor (CMF) development, new local safety performance functions (SPFs) were developed, and the results were compared with those derived from the HSM (Highway Safety Manual) SPFs and state-specific SPFs. Results showed significant crash reductions following RCUT implementation: a 63% reduction in total crashes and a 79% reduction in fatal and injury crashes. Annual angle crashes dropped by over 96%, and left-turn crashes by 40%, although sideswipe and rear-end crashes increased slightly as a result of redirected traffic. Despite methodological differences, all analyses confirmed RCUTs’ effectiveness in improving safety, making them a promising solution for high-speed rural intersections in Mississippi.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:36:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691042</guid>
    </item>
    <item>
      <title>Corridor-level and approach-level features associated with arterial wrong-way driving crashes and hotspots in South Florida</title>
      <link>https://trid.trb.org/View/2686116</link>
      <description><![CDATA[Wrong-way driving (WWD) crashes often result in fatalities. Understanding these crashes can help agencies reduce traffic fatalities and get closer to Target Zero. Arterial WWD crashes (AWWCs) are more prevalent than limited-access WWD crashes, but few studies have focused specifically on AWWCs. This paper examines AWWCs using a corridor methodology rather than analyzing segments and intersections separately. By understanding the relationships between AWWC frequency, corridor-level features (geometric design, traffic volumes, signage, medians, and lighting), and approach-level features (signage, lighting, and pavement markings on approaches entering the corridor), agencies can implement appropriate treatments. Among various regression models fitted to the data, a negative binomial model with corridor length as an offset variable was found to outperform other models. One-way corridors, more non-crash WWD computer-aided dispatch events, more through lanes, higher corridor left-turn lane densities, lower vegetation median proportions, and lower lighting overlap proportions were estimated to increase mean AWWC frequency. Ten hotspot corridors were examined in detail. These hotspots were characterized by a high through lane count, high left-turn lane density, and low lighting continuity on both sides. This study aids agencies in identifying factors which influence AWWCs and pinpointing hotspot corridors for targeted safety improvements to reach Target Zero.]]></description>
      <pubDate>Wed, 15 Apr 2026 10:29:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686116</guid>
    </item>
    <item>
      <title>Transferability of safety inspection procedures for network-wide safety assessment of two-lane rural roads - an Italian-Hungarian experiment</title>
      <link>https://trid.trb.org/View/2686639</link>
      <description><![CDATA[The new EU Directive on Road Infrastructure Safety Management requires Member States to classify the road network into at least three categories according to its safety level. This study examines the application and transferability of the procedures between EU countries. The methodology consisted of two steps. First, the authors conducted a questionnaire survey among twenty Hungarian road safety inspectors, and second, the authors applied the Italian procedure to calculate the risk index and compare it with historical crash data. Two-lane rural roads were selected and divided into 200 m sections, excluding intersections. Road safety inspectors evaluated these using a matrix of 18 criteria based on video recordings. The risk index was calculated, together with a sensitivity analysis, and its consistency with the observed crash history was investigated. Finally, three homogeneous groups were identified using k-medoids cluster analysis. The survey showed good acceptance of the process, but the authors also found differences in how inspectors rated certain criteria. The analysis of inspectors’ ratings of severity showed that there were varying degrees of agreement. However, the authors also concluded that the three-level rating may help to reduce disagreement. The risk index calculations used four years of crash data, and a moderate correlation between the crash rate and the risk index was found. By assigning a weighted average of adjacent sections and performing a k-medoids cluster analysis, the authors found that the optimal number of clusters is three, and these show a meaningful relationship with crash frequency. Regarding the application of the Italian procedure in Hungary to meet the requirements of the new EU RISM, the results are promising, and the lessons learned may also be useful for other countries.]]></description>
      <pubDate>Tue, 14 Apr 2026 16:59:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686639</guid>
    </item>
    <item>
      <title>Does Height Matter? Analysis of Contributing Factors to Tall-Vehicle/Pedestrian Crashes</title>
      <link>https://trid.trb.org/View/2691021</link>
      <description><![CDATA[With increasing urbanization, interactions between pedestrians and vehicles have become more frequent, raising safety concerns. Now comprising about 40% of the consumer fleet, tall vehicles such as trucks and sport utility vehicles pose unique risks with their elevated front profiles and large blind zones. This “car bloat” trend, combined with distracted and risky driving behaviors, has contributed to an 80% increase in pedestrian fatalities in the U.S. since its record low in 2009. In this study, an in-depth analysis of 15 years of single-vehicle/single-pedestrian crash data (2008–2022) from Wisconsin uncovers that tall vehicles, defined as 5.5 ft (66 in.) or greater in height, are disproportionately involved in crashes during left turns and backing maneuvers, with higher risks across specific pedestrian locations, pedestrian actions, and area type (urban versus rural). The results of a binary logistic model quantify that tall vehicle involvement was significantly associated with specific driver actions, such as left turns, as well as road types, and pedestrian presence in crosswalks, in addition to risk factors such as speed and driver behavior. The findings are instrumental to identify effective countermeasures to improve pedestrian visibility to tall vehicles and prioritize targeted strategies for roadway design, integrated planning, data-driven safety analysis, and targeted driver education addressing tall-vehicle risks.]]></description>
      <pubDate>Mon, 13 Apr 2026 08:41:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691021</guid>
    </item>
    <item>
      <title>NGBoost-Naïve Bayes collaborative deep learning for structural safety evaluation of bridges</title>
      <link>https://trid.trb.org/View/2653201</link>
      <description><![CDATA[In structural safety evaluation, machine learning (ML) based methods often exhibit strong data-fitting capabilities but struggle to effectively handle uncertainties in structural response data. Fortunately, Bayesian deep learning (BDL) algorithms can address this drawback by integrating the Bayesian theory with ML algorithms, thereby unifying perception and inference tasks within a single framework. For this purpose, a BDL framework has been proposed combining natural gradient boosting (NGBoost) and the Naïve Bayes theory. The NGBoost serves as the perception component, capturing correlations between deflections at various measurement locations of a healthy structure, while the Shapley Additive Explanation (SHAP) is employed to enhance interpretability. During the training process, the optimal hyperparameters of the NGBoost is objectively determined through Bayesian optimization (BO). The predicted probability distributions of these deflections are treated as hinge variables. By applying the triple standard deviation principle, a structural safety interval is defined to identify scenarios requiring further evaluation. The task-specific component, based on the Naïve Bayes theory, is then utilized to evaluate the structural condition. A bridge benchmark model was used to verify the safety assessment performance under the limited training samples. In addition, a continuous box-girder bridge was employed to further validate the effectiveness of the proposed structural condition indicator. As the structural degradation increased, the condition indicator accurately reflected the degradation variation.]]></description>
      <pubDate>Wed, 08 Apr 2026 13:57:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2653201</guid>
    </item>
    <item>
      <title>Aviation accident investigation analysis methodologies used by 12 government Safety Investigation Authorities</title>
      <link>https://trid.trb.org/View/2676204</link>
      <description><![CDATA[Leading government Safety Investigation Authorities (SIAs) that investigate major aviation accidents are members of the International Transportation Safety Association (ITSA). Investigation analysis methodology details are rarely included on SIA websites, in final accident reports, shared with peers, or specified by the International Civil Aviation Organization (ICAO). Some ‘New View’ safety researchers assume SIAs don’t use systemic methodologies and that accident investigation has little value. Because of the sensitivity of SIA work and need to prioritize safety value from available investigation funding, there has been little academic research on choice and use of investigation analysis methodologies to address these issues supported by SIAs or involving multiple SIAs.   Investigation analysis methodologies were defined broadly to include SIA-used academic models and ‘bespoke’ investigation processes. Over several years the authors gained the trust of 12 ITSA SIAs to provide written and interview data to address four research questions. NVivo12 software supported interview thematic analysis.   Ten SIAs reported using Rasmussen-based methodologies, 7 Reason-based, 6 own bespoke methodologies, 5 BowTie, 5 more recent systemic methodologies such as CAST and FRAM, and 10 SIAs used other methodologies such as SHELL, 6M, and bespoke methodologies from other ITSA SIAs.   Multiple investigation analysis methodologies were used by all SIAs, sometimes in the same investigation. In contrast with aging ICAO publications and negative New View claims, the SIA research data illustrates choice and usage of complex systemic and less complex analysis methodologies in varying investigative contexts.  The research is being used by the 12 SIAs to better understand, and draw from, each other. It has broad relevance for updating ICAO documentation that is now underway, for other SIAs and the wider aviation community, and for other high-risk industries that seek to understand professionally operationalized methodologies used for investigation, analysis, and safety action with associated learning.]]></description>
      <pubDate>Wed, 08 Apr 2026 13:40:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2676204</guid>
    </item>
    <item>
      <title>Analysis of different road network safety analysis procedures</title>
      <link>https://trid.trb.org/View/2687068</link>
      <description><![CDATA[In 2019 the European Parliament updated Directive 2008/96/EC on road safety management. In the updated Directive, they introduced the concept of network-wide road safety assessment (NWRSA), which is a network screening that must be based on both visual inspections of the road and accident analysis. The procedure should provide a classification of the different road sections analyzed into at least three different risk levels (low, medium, and high). This paper investigated eight safety analysis procedures that are eligible to be included in the NWRSA process to identify elements in common and in conflict among them. These procedures have been applied to a two-lane two-ways rural highway stretch of about 10 km. Due to the differences in the parameters, algorithms, and processes considered in each procedure, the results of each evaluation may differ, both considering the typology of the output, both considering the measure of risk for a specific segment. To provide the road authorities with effective assessment tools for all road segments inside their network as a function of data available, the results of the procedures are analyzed and discussed both qualitatively and quantitatively using statistical analysis such as Kendall W and non-parametric Kruskal–Willis, to test for concordance and significative difference between the analyzed procedure respectively. Moreover, the main characteristics of the procedures are highlighted and discussed, such as the required data and the considered segmentation. The results show that some procedures lead to results that do not differ significantly. Therefore, they can be used as alternative procedures to assess different road stretches according to specific data availability, while others not.]]></description>
      <pubDate>Mon, 06 Apr 2026 08:52:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2687068</guid>
    </item>
    <item>
      <title>NCHRP Research Report 1152: Leveraging AI and Big Data to Enhance Safety Analysis</title>
      <link>https://trid.trb.org/View/2678815</link>
      <description><![CDATA[National Cooperative Highway Research Program's (NCHRP's) Project 17-100 explored ways to harness artificial intelligence and data from traffic cameras, automated vehicles, and other systems to evaluate and enhance traffic safety. This article looks at the research design and phases, pilot demonstrations, deliverables, and agency application. Application examples include: automated streetlight inventory from street-view imagery; turning speeds and trajectories from intersection video analytics; inference of vehicle volumes and types, classified by length, from single loop detectors; turning-movement estimation from connected-vehicle telemetry; lane-marking and width extraction from lidar; traffic-sign detection and recognition from roadway video logs; multiscale pedestrian detection from mounted surveillance cameras; and road-surface condition analytics from on-site edge computing devices. The primary deliverable was a practitioner-focused user’s guide, NCHRP Research Report 1152: Leveraging Artificial Intelligence and Big Data to Enhance Safety Analysis: A Guide. Agencies can use the guide to translate safety questions into appropriate datasets and model designs, adopt a planning-first pathway for machine learning, and implement tested workflows across the full data life cycle from acquisition through deployment.]]></description>
      <pubDate>Thu, 02 Apr 2026 15:16:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2678815</guid>
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