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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>Classifying experienced male drivers’ mental workload on freeway ramps based on heart rate and speed measurements: A real-vehicle experiment</title>
      <link>https://trid.trb.org/View/2659462</link>
      <description><![CDATA[Freeway ramps are recognized as high-risk segments of the road network due to their geometric complexity and dynamic traffic demands. This study investigates drivers’ mental workload in ramp areas by integrating psycho-physiological responses, specifically heart rate growth (HRG), with vehicle kinematic data, including speed and acceleration. Data were collected through real-world driving experiments from 32 experienced male drivers (aged 30–50 years) under both daytime and nighttime conditions. The findings revealed that HRG values were significantly higher at night, indicating increased cognitive stress in low-light conditions. In addition, the study identified a strong linear relationship between HRG and speed across all scenarios, indicating that increased speed is closely associated with higher mental workload. The relationship between HRG and acceleration followed a three-phase pattern, with sharp HRG changes at both low and high acceleration levels, and more stable responses within the mid-range. Based on these relationships, a classification framework was developed to categorize experienced male drivers’ mental workload into three workload categories (Class 1, Class 2, and Class 3) using joint thresholds of HRG, speed, and acceleration. These findings provide a data-driven basis for identifying cognitively demanding ramp segments and inform the design of adaptive speed guidance systems, real-time driver monitoring technologies, and ramp infrastructure improvements.]]></description>
      <pubDate>Wed, 25 Feb 2026 13:58:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659462</guid>
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    <item>
      <title>Preventing Maritime Accidents: The Role of Human Factors and Cognitive Performance</title>
      <link>https://trid.trb.org/View/2672673</link>
      <description><![CDATA[Background: The maritime industry, despite rigorous safety measures, remains a high-risk sector due to persistent human errors. Objective: This study aims to assess mental workload, accuracy, and attention across various mental states and explore the relationships among key variables affecting cognitive performance through a Bayesian network (BN) analysis. Methods: Data were collected from 51 officers at a maritime training center using demographic surveys and the NASA Task Load Index (NASA-TLX) mental workload index. Participants were then subjected to three different simulation scenarios, during which their physiological responses and brain waves were recorded. Results: Results indicated that effort scored the highest and failure the lowest among the dimensions assessed. Notably, the average heart rate increased from 74.33 beats per minute at rest to 85.92 after the second scenario, signifying heightened physiological stress. Post-scenario analyses showed an increase in attention and alertness levels compared to the resting state, while meditation levels decreased. Physiological responses, including heart rate and blood pressure, were found to elevate after rest periods, correlating with decreased attention and increased mental workload, as evidenced by the BN findings. Conclusions: These results underscore the intricate interplay between physiological responses and cognitive performance, highlighting the critical need for targeted strategies to mitigate human errors in maritime operations.]]></description>
      <pubDate>Wed, 25 Feb 2026 08:54:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672673</guid>
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    <item>
      <title>The relationship between electroencephalographic measures and driving performance in older adults: A scoping review</title>
      <link>https://trid.trb.org/View/2663681</link>
      <description><![CDATA[With the number of older adult drivers on the road increasing, more older adults are experiencing age-related changes in cognitive functions necessary for driving. Previous research suggests electroencephalography (EEG) may be a useful methodology for assessing these changes, given its high temporal resolution. However, the relationship between specific EEG markers and components of driving performance in older adults is currently unknown. The aim of this scoping review is to examine the current state of knowledge on EEG measures and driving performance in older adults. This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Papers were eligible for inclusion if they examined a) the relationship between EEG and driving performance measures or b) EEG and driving performance measures simultaneously, in older adults aged 55 years and older. A total of 468 papers were identified, and six papers were included in the final analysis. Results indicate frequency band analyses and event-related potentials are the most commonly used EEG measures to assess changes in driving performance. However, there is considerable variability between the current studies, in terms of the sample sizes, experimental design and the variables of interest. Considerable methodological heterogeneity and the lack of experimental data using cognitive paradigms for EEG, limits the ability to draw conclusions on the relationship between neurocognitive changes and driving performance in older adults. Directions for future research are discussed.]]></description>
      <pubDate>Wed, 25 Feb 2026 08:53:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663681</guid>
    </item>
    <item>
      <title>Understanding the role of metacognitive awareness in the self-regulation of driving among older adults</title>
      <link>https://trid.trb.org/View/2667204</link>
      <description><![CDATA[Metacognitive awareness, the ability to be aware of and regulate one’s internal processes, may play a role in how effectively older drivers both manage their attention and assess their driving capabilities.  This study investigated the links between self-reported metacognitive awareness, subjective changes in driving skills, driving inattention, and driving regulation in a sample (N = 713) of Australian drivers aged 60 years and older.  The results showed that most participants reported minimal change in their driving skills over the past few years, with higher proportions reporting improvements rather than decline. Comparative analyses indicated that participants who rated their cognitive-motor skills as improved scored higher in metacognitive evaluation, metacognitive awareness of driving attention, and driving quantity, but lower in driving inattention, regulation, and age. Bivariate correlations revealed significant associations between metacognitive evaluation, metacognitive awareness whilst driving, subjective changes in driving skills, driving inattention, and the regulation of driving. However, follow-up path analysis suggested the interrelationships between these constructs were complex. Where greater metacognitive evaluation and awareness of attention were linked with improved driving attention and a decreased tendency to regulate driving, metacognitive evaluation and awareness of thoughts and feelings were tied with greater subjective safety-behavior skills and an increased tendency to regulate driving. The findings suggest that metacognitive awareness may support safer driving behaviors among older adults by encouraging appropriate regulation of driving and enhancing attention management.]]></description>
      <pubDate>Wed, 25 Feb 2026 08:53:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2667204</guid>
    </item>
    <item>
      <title>Optimisation of floor evacuation map based on drive design</title>
      <link>https://trid.trb.org/View/2625879</link>
      <description><![CDATA[To investigate the optimisation scheme for a floor evacuation map, library, and mall scenarios were considered as examples, and drive designs, including non-drive design, salient stimulus-drive design, and working memory-drive design, were introduced in the experiment. Participants’ wayfinding behaviour and responses were studied by analysing the average duration of fixation (ADF), average fixation counts (AFC), accuracy rate (AR), response time (RT), and other relevant indices. The experimental data revealed that both the salient stimulus-drive and working memory-drive designs significantly reduced the ADF and AFC compared to the non-drive design while improving the AR. The RT of the salient stimulus-driven group was significantly longer than that of the other two groups. The experimental results indicated that incorporating floor plans and relevant salient stimuli into the design of floor evacuation maps can enhance their readability, thereby facilitating better retention of evacuation routes by participants.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625879</guid>
    </item>
    <item>
      <title>The relationship between emotional intelligence, visual cognitive performance, and driving behavior across different age groups</title>
      <link>https://trid.trb.org/View/2655591</link>
      <description><![CDATA[In the process of driving, visual cognitive abilities and emotional intelligence (EI) play very important roles in the perception of, and the subsequent decision about hazards and sudden events in the surrounding environment. This study explored the differences in EI, visual cognitive performance, and driving behavior across various age groups. It examined the differences in the number of collisions and eye movements in regular and sudden traffic incidents and investigated the relationship between EI, visual cognitive performance, and driving behavior. A total of 52 participants were recruited and divided into three groups: a younger group, a middle-aged group, and an older group. All participants were required to respond to both regular and sudden events in simulated driving sessions, during which data on the number of collisions and eye movements were collected. In addition, assessments for risky driving and EI were also performed. The results indicated that young drivers exhibited considerably higher scores in the management of others’ emotions than those of middle-aged and older drivers, whereas older drivers demonstrated less frequent risky driving and distracted driving behavior. In terms of eye movement performance, young drivers rapidly noticed traffic incidents and exhibited a larger number of eye movements and longer fixation duration during regular traffic incidents compared with the other age groups. In addition, risky driving and the number of collisions in different traffic event types were strongly correlated with age, distracted driving, EI, and visual cognitive performance. This study contributes to understanding the effects of age, EI and visual cognitive performance on risky driving, as well as the relationship among risking driving and eye movements characteristics. This study can serve as a reference for developing preventive measures against risky driving behavior and traffic accidents, based on the differences in EI, visual cognitive performance, and eye movement characteristics.]]></description>
      <pubDate>Wed, 18 Feb 2026 11:59:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655591</guid>
    </item>
    <item>
      <title>Enhancing Road Safety Through Wearable Sensor Technology and Explainable Artificial Intelligence: A Novel Approach To Cognitive Load Monitoring in Driving</title>
      <link>https://trid.trb.org/View/2642280</link>
      <description><![CDATA[Innovative wearable neurotechnology offers new methods to enhance user capabilities and provide insights into cognitive processes. These brain-computer interfaces, increasingly accessible, have the potential to become commonplace, necessitating proactive consideration of their societal and sector-specific impacts—including traffic and transportation. However, their development presents two major risks: potential misuse of cognitive data and challenges in user trust and acceptance. This paper proposes a novel approach to improve road safety through the integration of wearable sensor technology and Explainable Artificial Intelligence (XAI). The primary goal is to monitor drivers’ cognitive load in real-time to mitigate the dangers of distracted driving. Wearable sensors, such as EEG headbands and heart rate monitors, continuously capture physiological signals, which are then processed using advanced machine learning algorithms, including XAI models, to yield interpretable assessments of driver cognitive states. The proposed system offers several advantages over traditional methods, including non-intrusiveness, real-time operation, and the capacity for personalized intervention. By developing explainable deep learning models, the system fosters transparency and trust among users and regulatory bodies, encouraging adoption. Ultimately, the integration of this cognitive monitoring system into smart road infrastructure aims to reduce road accidents caused by distraction and promote safer journeys for all road users.]]></description>
      <pubDate>Wed, 18 Feb 2026 08:51:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642280</guid>
    </item>
    <item>
      <title>Towards operational safety in maritime transportation: a neurophysiological workload measurement using deep learning</title>
      <link>https://trid.trb.org/View/2664986</link>
      <description><![CDATA[Human factors account for 70 %–90 % of maritime accidents, with mental workload (MWL) being a significant risk element. Current assessments of seafarer MWL lack objective neurophysiological measures, restricting accurate monitoring and proactive safety measures. This study employed electroencephalography (EEG) data from 10 crew members during simulated navigation tasks to introduce an EEG-based MWL measurement framework for simulated navigation tasks, aimed at monitoring cognitive states and supporting maritime safety management. Three innovations are proposed: (1) a maritime-specific EEG index indicating task-related cognitive demand; (2) a neurobehavioral link between EEG metrics and observed operational errors, showing how high MWL relates to operational safety; (3) a hybrid convolutional neural network and bidirectional long short-term memory (CNN-BiLSTM) model for classifying MWL states. The model provides objective assessments by identifying key EEG bands with Shapley Additive Explanations (SHAP). In a cross-subject validation, the model achieved an AUC of 0.94, demonstrating its ability to generalize across different seafarers. These findings illustrate how EEG-derived workload assessment can inform data-driven crew management and training strategies, providing a neurophysiological foundation that may support enhancing maritime safety from a human factor perspective.]]></description>
      <pubDate>Mon, 09 Feb 2026 08:42:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664986</guid>
    </item>
    <item>
      <title>Drawing errors but not drawing strategies: Discriminating safe from unsafe driving in commercial drivers and cognitively at-risk seniors</title>
      <link>https://trid.trb.org/View/2656217</link>
      <description><![CDATA[The Vitals cognitive assessment tool is a battery of tablet-based cognitive and sensorimotor tasks which are used to predict safe or unsafe driving. One of the Vitals tasks is a visuospatial working memory task, which requires people to replicate a simple shape following a short delay. Previous evidence suggests that poor performance on this task is associated with cognitive impairment and risky driving, but this poor performance could have several possible explanations, including a working memory deficit, abnormal drawing strategies, or problems with motor execution. In this study, the authors recruited medically at-risk older drivers and healthy commercial drivers to perform the Vitals, as well as an on-road driving evaluation. Drivers who failed the on-road evaluation drew fewer correct shapes compared to drivers who passed, but did not show any differences in drawing strategy. At-risk older drivers who failed showed an increase in motor errors while producing the drawings, while commercial drivers who failed were slower to complete the task. This pattern of results excludes suboptimal drawing strategies as an explanation for poor performance, and also exclude motor errors while producing the drawings as an explanation for increased completion time. The best explanation for poor performance on the Vitals’ visuospatial working memory task is therefore a working memory deficit.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:52:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2656217</guid>
    </item>
    <item>
      <title>A systematic review of gaming effects on driving related skills</title>
      <link>https://trid.trb.org/View/2654605</link>
      <description><![CDATA[Road traffic accidents (RTAs) rank as the twelfth leading cause of death globally. While several factors contribute to RTAs, diminished visual and cognitive abilities remain an often-overlooked cause, negatively affecting driving performance. The “learning to learn” hypothesis suggests that playing games enhances general learning abilities and executive control mechanisms, enabling to transfer acquired-skills across real-world tasks. Considering this potential, this review investigates existing research on the connection between playing different types of games and driving behavior. Following PRISMA guidelines, a narrative synthesis was conducted with an effect size analysis using R. Studies were categorized based on game type, intervention duration, and outcome measures related to driving skills. The review analyzed the findings from three interventional and nine observational studies. Effect size analysis of observational studies revealed a positive association between gaming experience on computerized driving tasks (g = 0.96, 95 % CI: 0.63, 1.28). Interventional studies suggested that driving racing games, when played for 8–10 h in total, can improve short-term performance in computerized and on-road driving tasks. Available evidence suggests a significant positive association between gaming and computerized driving task outcomes. Furthermore, driving-specific gaming interventions have a significant effect on simulator tasks and on-road skills. However, to establish gaming interventions, further research is needed to analyze the effect of different gaming genres on different skills that are necessary for driving. Standardizing interventional methodologies and driving variables are essential for providing reliable evidence. Developing evidence-based gaming interventions requires well-defined protocols and game selection criteria.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:52:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2654605</guid>
    </item>
    <item>
      <title>Fathoming out risk perception : an onboard ethnography of ro-pax sister ferries</title>
      <link>https://trid.trb.org/View/2666500</link>
      <description><![CDATA[This thesis examines how risk perception is shaped, communicated, and enacted by crew members on board two sister ro-pax ferries operating in European trade. It asks how safety is understood and practiced not merely as a formal requirement, but as a lived reality grounded in social norms, experience, and departmental culture. Making use of ethnographic fieldwork including interviews, observation, fieldnotes and informal conversations, the study shows how formal procedures interact with the routines of onboard life, producing a collective perception of risk. Two conceptual triads are developed to structure the analysis: the triad of the senses comprising making sense, sharing sense and common sense; and the triad of the responses which consists of clash, harmony, and routine non-conformity. These frameworks capture how risk perception is formed, shared and made collective, and show how crew members respond to top down safety initiatives, revealing safety culture as a negotiated process between institutional regulation and everyday practice. Informed by normative institutionalism, the unanticipated consequences of purposive action, and the notion of organisational deviance, the thesis explores how formal rules are received on the deck floors and, in doing so, reveals crew members' situated expertise and proactive engagement with risk. Methodologically, the study contributes to maritime ethnography through a combination of realism, confessional narrative, and impressionism, and offers an immersive account of onboard working life. Practically, it identifies barriers to reporting systems and highlights the importance of informal mentoring in guiding newcomers toward a shared perception of risk. The study proposes that improved safety outcomes may depend not only on compliance, but on a better institutional understanding of how risk is perceived and negotiated collectively, on the deck floors.]]></description>
      <pubDate>Thu, 05 Feb 2026 08:32:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666500</guid>
    </item>
    <item>
      <title>Cognitive Task Analyses of Air Traffic Management (ATM) Workforce to Inform Human Performance Modeling</title>
      <link>https://trid.trb.org/View/2658080</link>
      <description><![CDATA[This report documents a comprehensive Cognitive Task Analysis (CTA) conducted by The MITRE Corporation’s Center for Advanced Aviation Systems Development (CAASD) for the Federal Aviation Administration (FAA) Human Factors Division (ANG-C1). The primary objective was to analyze key air traffic workforce positions at Air Route Traffic Control Centers (ARTCCs)—including Radar (R) and Radar Associate (RA) controllers, Operations Supervisors (OSs), Traffic Management Coordinators (TMCs), Supervisory Traffic Management Coordinators (STMCs), and Oceanic controllers—to inform operational changes, improve procedures, training, interfaces, and decision support aids. The research adopted a holistic CTA approach, spanning systems and capturing the overall operational workflow rather than focusing on system-specific tasks. Data collection involved approximately 60 hours of facility observations and guided discussions at Seattle (ZSE), Oakland (ZOA), and Miami (ZMA) ARTCCs, enabling the team to document both observable actions and underlying cognitive processes. MITRE developed multi-level CTA models using flowcharts for task flows and Goals, Operators, Methods, and Selection Rules (GOMS)-based cognitive models to represent decision-making criteria, automation interaction, and communication. Key findings highlight the complex interplay of attention, vigilance, communication, and perceptual skills required across all ARTCC positions, with unique operational characteristics observed in oceanic areas and supervisory roles. The CTA results provide a baseline for discrete event task network modeling, supporting the FAA’s efforts to anticipate cognitive performance issues and improve individual and team performance. Recommendations include further research to expand efforts to the Terminal Radar Approach Control (TRACON) and Airport Traffic Control Tower (ATCT), further validate model applicability across additional ARTCC facilities and expanding supervisor task analysis to include both operational and administrative responsibilities to inform insights beyond the scope of this effort such as those focused on overall workload experience. Next steps involve formatting task flow diagrams for integration with the Improved Performance Research Integration Tool (IMPRINT) and extending CTA research to TRACON and ATCT facilities.]]></description>
      <pubDate>Mon, 02 Feb 2026 14:13:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658080</guid>
    </item>
    <item>
      <title>The Association Between Health Problems and Driver Status Among Older Adults</title>
      <link>https://trid.trb.org/View/2635337</link>
      <description><![CDATA[Many health problems, especially those associated with older age, can have an impact on an individual’s mobility. This paper addresses how specific functional limitations and medical conditions may be associated with driving status, while controlling for age and gender. This paper uses baseline data (N=2025) from a longitudinal survey of adults, ages 55 and older, the Study of Physical Performance and Age-Related Changes in Sonomans (SPPARCS). For the 35 selected medical conditions and functional limitations, this report presents the prevalence, the relative “risk” ratio (i.e., the risk that an individual with that condition no longer drives), and the attributable risk (i.e., the percent of ex-drivers with each condition). Compared to current drivers, ex-drivers had higher rates of physical limitations (ability to ascend one flight of stairs or walk three blocks), cognitive impairment, vision problems and stroke. The conditions with the highest relative risk included personal mobility limitations (such as the ability to transfer onto or from bed and the ability to use the lavatory) and decreased peripheral vision. The relative risks of medical conditions’ effects on driving status offer a perspective on individuals’ mobility choices, and the attributable risks offer a perspective on the most important causes of driving cessation in the elderly population.]]></description>
      <pubDate>Sat, 31 Jan 2026 16:28:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635337</guid>
    </item>
    <item>
      <title>Re-understanding accessibility through a cognitive process: a conceptual framework and quantification</title>
      <link>https://trid.trb.org/View/2617225</link>
      <description><![CDATA[Accessibility, as a manifestation of the right to the city, plays a pivotal role in assessing social equity and spatial justice. Accurate accessibility measurements are critical for guiding equitable urban planning. Conventional accessibility metrics focus on physical environmental characteristics, while recent advancements increasingly incorporate perceptions of the built environment. However, existing advancements mainly adopt an outcome-based approach, neglecting the underlying mechanism through which physical environmental characteristics translate into perceptions. Decoding this perceptual process is vital for refining accessibility measurements and achieving more comprehensive, accurate results. This study re-understands accessibility by proposing a conceptual framework incorporating perception mechanisms rooted in cognitive process theories. The framework delineates how individuals gather spatial information to identify opportunities at origins, destinations, and during travel, which are then filtered through constraints, attitudes, and habits. We empirically validate this framework using social sensing data to evaluate restaurant accessibility in Shenzhen, China. Our case study reveals that conventional accessibility metrics tend to overestimate individuals' access to potential opportunities. The proposed framework is quantifiable, interpretable, and scalable across diverse contexts. By bridging the gap between the physical environment and perceptual outcomes, it advances a new understanding of accessibility that integrates perception into measurement, offering valuable insights for equitable planning and policy-making.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617225</guid>
    </item>
    <item>
      <title>Method for Designing Operational Management Concepts for Low-Crewed Surface Vessels</title>
      <link>https://trid.trb.org/View/2647472</link>
      <description><![CDATA[In this work, we outline and appraise a method for creating and evaluating an Operational Management Concept (OMC) for Low- Crewed Surface Vessels (LSVs) in the Royal Netherlands Navy (RNLN). Utilizing Cognitive Work Analysis (CWA) and Design Thinking tools, three workshops were carried out with seven Subject Matter Experts (SMEs) focused on task allocation and the feasibility of minimal crewing. The first two workshops developed a task allocation concept, considering human responsibility, automation, and shore support. The third workshop utilized a tabletop game to evaluate the OMC’s feasibility and to enrich the OMC with more detail. The workshops led to an innovative OMC with roughly a dozen crew members, heavily dependent on automation, redundant systems, and shore support. The workshops allowed SMEs to expand their current experiences and encouraged discussions on human responsibility, collaboration, and technological support. The workshops underscored the need for deeper immersion (e.g., by using Virtual Reality) to effectively assess advanced automated systems.]]></description>
      <pubDate>Mon, 26 Jan 2026 08:41:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647472</guid>
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