<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>Infrastructure and supply pathways for liquid hydrogen at airports: A technical framework for feasibility and airport master planning</title>
      <link>https://trid.trb.org/View/2681227</link>
      <description><![CDATA[Hydrogen-powered aviation is increasingly considered a promising option for reducing aviation emissions, particularly on regional and short-haul routes. The use of liquid hydrogen (LH2) as an aviation fuel offers significant environmental benefits, but its adoption and integration require the development of new infrastructure at airports, including hydrogen liquefaction facilities. This paper lays the groundwork for assessing the feasibility of onsite hydrogen liquefaction by examining the technical principles, supply chain configurations and spatial requirements of such facilities. The study starts with a comprehensive overview of hydrogen as an aviation fuel, outlines current aircraft developments and compares three LH2 supply pathways: centralised offsite liquefaction, onsite liquefaction from offsite hydrogen, and full onsite production and liquefaction. Drawing on real-world examples from operational liquefaction facilities in South Korea, the US and Canada, this paper presents a generalised layout for airport-based liquefaction facilities, detailing core liquefaction process zones and supporting systems. These zones serve as a planning tool for early-stage spatial assessments, safety zoning and integration of hydrogen liquefaction facilities with existing airport infrastructure. The layout presented in this paper is modular and scalable, allowing airports to adapt infrastructure to varying hydrogen demand and spatial constraints. While current liquefaction plants demonstrate technical feasibility and viability at scales up to 90 tons per day (TPD), this paper explores the practical challenges of implementing such infrastructure at airports. These include gaining access to gaseous hydrogen via backbone networks, energy demands, constrained land availability, safety zoning requirements and regulatory complexity. Rather than resolving these issues, the paper provides a descriptive framework to understand and assess them, supporting airport master planning and future airport feasibility studies. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.]]></description>
      <pubDate>Wed, 25 Mar 2026 16:40:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681227</guid>
    </item>
    <item>
      <title>A data-driven framework for railway risk assessment and safety management: evidence from Thailand’s national network</title>
      <link>https://trid.trb.org/View/2643208</link>
      <description><![CDATA[This study presents a data-driven framework to assess risk and enhance safety within Thailand’s railway network, particularly during Thailand’s transition to high-speed rail. Using more than 70,000 accident records (2009–2024), the research applies temporal, spatial, and statistical analyses to identify high-risk patterns. Findings indicate that accidents peak during the evening hours and the rainy season, with derailments and level-crossing collisions significantly associated with higher fatality rates (r = 0.68, 𝘱 < 0.01). At the provincial level, Bangkok recorded the highest number of incidents (𝘯 = 31) but comparatively few casualties, while Phetchaburi and Chachoengsao reported fewer incidents yet disproportionately high numbers of injuries and fatalities. To address these risks, the study employs Decision Tree, Random Forest, and Bayesian Network models. The Random Forest achieved the highest predictive accuracy (95.6%), while the Bayesian Network offered interpretable causal reasoning. These models underpin the Rail-Risk Management Platform, a web-based tool providing real-time visualisation, alerts, and scenario analysis. Pilot testing reduced assessment time from 45 to 8 minutes and achieved a user satisfaction score of 4.52 out of 5. The study recommends targeted investments, intelligent safety systems, workforce development, and a unified risk management framework for sustainable railway-safety governance in Thailand.]]></description>
      <pubDate>Wed, 25 Mar 2026 15:50:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643208</guid>
    </item>
    <item>
      <title>Road safety management and interventions in Africa: Is there a correlation between management performance and traffic fatalities?</title>
      <link>https://trid.trb.org/View/2653231</link>
      <description><![CDATA[The primary aim of this article is to deepen understanding of road safety management in Africa and its relationship with traffic fatalities on the continent. Drawing from a performance review of the African Road Safety Action Plan 2011–2020, the article examines the extent to which interventions to strengthen road safety management capacity on the continent are implemented. The analysis shows that many countries struggle to mobilize finance, facilitate research, strengthen data management systems, monitor, evaluate and report on road safety. As a result, road safety management capacity on the continent remains weak, hampering the implementation of interventions in other road safety pillars, namely safer roads and mobility, safer vehicles, safer road users and post-crash response. The authors also use different regression models to analyze the relationship between performance in road safety management and traffic fatality rates. Mixed results are obtained. Analysis using linear and beta regression models suggests that road safety management is not a statistically significant predictor of fatality rate. However, a significant correlation between road safety management performance and variation in road fatality rate is obtained when the robust regression method, which handles outliers in data, is used. These results are useful as they suggest that strengthening road safety management may not be sufficient to significantly reduce road deaths in Africa. It is therefore imperative to investigate the relative importance of other factors that contribute to traffic fatalities on the continent.]]></description>
      <pubDate>Wed, 25 Mar 2026 11:43:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2653231</guid>
    </item>
    <item>
      <title>Applicability of Anomalous Driving Detection Methods to Driving Safety Management</title>
      <link>https://trid.trb.org/View/2674225</link>
      <description><![CDATA[Recently in Japan, traffic accidents caused by driver error or dangerous driving have become a serious social problem. Along with the development of automated driving and advanced driver assistance systems, driver education and awareness should also be improved to encourage safer driving practices. In this study, we evaluate the effectiveness of anomalous driving detection methods for driving safety management. These methods identify potentially dangerous driving behaviors that are often difficult for drivers to recognize. In conclusion, it was evident that providing feedback on driving performance reduced the occurrence of anomalous driving behaviors.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:21:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2674225</guid>
    </item>
    <item>
      <title>STPA and SFHA Combined: Airbus A320 Family ATA 27B High-Lift System Case Study</title>
      <link>https://trid.trb.org/View/2666090</link>
      <description><![CDATA[This paper explores the integration of System-Theoretic Process Analysis (STPA) and System Functional Hazard Analysis (SFHA) as a combined approach for safety assessment, using the Airbus A320 family ATA 27B High-Lift system as a case study. The proposed approach utilizes the complementarity of STPA and SFHA: STPA focuses on interactions and control flaws among system or components, identifies scenarios that traditional methods may not consider, while SFHA provides a structured assessment of functional hazards and their severity. By beginning with STPA analysis to identify potential loss scenarios, the following SFHA can be performed in a more comprehensive manner, extending its scope beyond hardware failures to include software issues and human related factors. Output of merging STPA and SFHA shows improvement in hazard identification and assessments.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666090</guid>
    </item>
    <item>
      <title>The Landscape of Integration and Automation for STPA in Aerospace: A Systematic Review</title>
      <link>https://trid.trb.org/View/2666086</link>
      <description><![CDATA[As aerospace systems grow in complexity, traditional safety analysis methods are proving insufficient, leading to the adoption of systemic approaches like System-Theoretic Process Analysis (STPA). However, its practical application is often diminished by its cognitively demanding nature, with a significant portion of published analyses being incomplete and lacking independent validation. While prior reviews have mapped STPA’s applications, a dedicated analysis of its integration and automation within the aerospace safety engineering lifecycle has been absent. This paper fills that gap, presenting a systematic literature review of 126 studies to assess the state of the art. This analysis reveals a clear bifurcation in the literature: model-based approaches are well positioned to integrate STPA into the entire engineering workflow, using its outputs to inform subsequent design and verification stages. In contrast, non-model-based applications tend to treat STPA as an isolated, standalone analysis, limiting its impact. Despite the strong trend towards Model-Based Systems Engineering (MBSE), our review identifies several critical research gaps that persist. There is a widespread absence of substantive validation for analytical outputs, limited attention given to methods for filtering and managing the “scenario overload” problem, and a preference for MBSE over the more specialized Model-Based Safety Analysis (MBSA) frameworks. These findings suggest that while the automation of STPA is advancing, its full potential will only be unlocked by addressing these challenges of integration, validation, and scalability.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666086</guid>
    </item>
    <item>
      <title>Basic safety and security requirements for the transport of CBRN agents with special emphasis on R and N components</title>
      <link>https://trid.trb.org/View/2665854</link>
      <description><![CDATA[The paper summarizes some recent approaches to ensuring the safe and secure transport of dangerous materials of the CBRN (Chemical, Biological, Radiological, and Nuclear) category, with more details given in addressing their Radiological (R) and Nuclear (N) components. These substances are usually produced in one place but used in another, where they must be transported. During the movement of CBRN material, strict protection measures should be applied to protect the persons involved in the transport and the security of the transported cargo so that unauthorized persons do not have access to these dangerous substances. Special attention should be paid to ensure adequate protection of people and the environment in case of any accident or terrorist attack. Relevant emergency standards should be applied to minimize the consequences of such situations. Although most of the essential protection measures are similar for each of the CBRN components, there are some specific requirements to ensure necessary safety and security for R and N agents.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665854</guid>
    </item>
    <item>
      <title>Safety risks and train drivers’ perceptions: Measurement of latent difficulties from the Taiwan railway</title>
      <link>https://trid.trb.org/View/2672755</link>
      <description><![CDATA[This research utilizes data from the Taiwan railway to investigate the applicability of the SHELL (software, hardware, environment, liveware) model and psychometric multidimensional Rasch methods in evaluating train drivers’ risk perceptions across various hazardous scenarios. The study establishes a systematic approach to identify which risks are challenging to perceive and to characterize the traits associated with risky train drivers. The findings indicate that certain drivers may be more prone to incurring higher risks. Safety supervisors can leverage this information to identify these high-risk individuals and implement tailored training programs aimed at mitigating potential risks proactively. Furthermore, the proposed methodology for assessing train drivers’ risk perception can be adapted for application in other railway systems. The results derived from Rasch analysis provide railway safety managers with valuable insights, enabling them to minimize the likelihood of railway accidents.]]></description>
      <pubDate>Wed, 18 Mar 2026 09:00:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672755</guid>
    </item>
    <item>
      <title>Hazards in the port system and their impact on safety performance: An empirical study of the hazard management system of the Tianjin Port Group</title>
      <link>https://trid.trb.org/View/2672754</link>
      <description><![CDATA[This study investigates how sustained governance of hidden hazards influences safety performance in port systems, using data from 54 production and key non-production enterprises within the Tianjin Port Group. Employing correlation analysis, regression modeling and mediation–moderation analysis, the study finds that both systematic hazard governance and standardized safety management significantly improve safety outcomes. Basic management-level governance directly reduces the frequency of incidents, while site-level governance enhances safety performance indirectly by promoting standardization. Moreover, the overall risk level of hidden hazards moderates the effectiveness of these governance strategies. The study confirms the alignment between hazard inspection frameworks and safety management systems, and proposes a closed-loop model to support continuous improvement and long-term risk control in high-risk port environments.]]></description>
      <pubDate>Wed, 18 Mar 2026 09:00:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672754</guid>
    </item>
    <item>
      <title>Tourist Safety on the Polish Baltic Coast: Analysis of Risks and Preventive Strategies</title>
      <link>https://trid.trb.org/View/2624157</link>
      <description><![CDATA[The Polish Baltic Sea coast is a popular destination for tourists seeking picturesque landscapes, sandy beaches, and a rich cultural heritage. Each year, millions of visitors flock to the region to enjoy its natural beauty and recreational opportunities. However, the increasing number of tourists also brings unique challenges related to safety and risk management. Ensuring the safety of visitors is a multifaceted task that requires collaboration between local authorities, businesses, and emergency services. The paper explores the primary risks faced by tourists on the Polish Baltic coast, including natural hazards, infrastructure challenges, and human-related factors such as crime or accidents. Furthermore, it examines the strategies and measures implemented to mitigate these risks, highlighting the importance of education, preparedness, and effective communication. By analyzing both threats and preventive actions, this study aims to provide valuable insights for policymakers, local stakeholders, and tourists themselves to enhance safety and promote a secure environment for all.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:57:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2624157</guid>
    </item>
    <item>
      <title>Edge AI-Enhanced Traffic Monitoring and Anomaly Detection Using Multimodal Large Language Models</title>
      <link>https://trid.trb.org/View/2562213</link>
      <description><![CDATA[This paper addresses the challenge of traffic monitoring and incident detection in remote areas, utilizing multimodal large language models (LLMs) deployed on edge AI devices. The key novelty of the LLM is to convert real-time video streams into descriptive texts, enabling low-bandwidth transmissions and reliable detection of anomalies and incidents in environments of intermittent connectivity. The model is developed based on fine-tuning open-source LLMs and extending it with multi-modal capabilities to analyze video frames. Our work also involves deploying this model on edge devices such as Nvidia IGX Orin and is planned to be tested in realistic environments in future work. The methodology includes data set curation, iterative model fine-tuning and compression, and hardware-based optimization. This approach aims to enhance traffic safety and response speed in remote areas, marking a significant advancement in the application of AI for traffic monitoring and safety management.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2562213</guid>
    </item>
    <item>
      <title>Pre- and post-COVID-19 spatiotemporal dynamics of pedestrian safety: Evidence from Chicago</title>
      <link>https://trid.trb.org/View/2647781</link>
      <description><![CDATA[The COVID-19 pandemic transformed daily travel patterns. Prior studies have examined pandemic-induced changes in travel behavior, but the long-term spatiotemporal consequences for pedestrian safety remain underexamined. This study assesses shifts in the severity-weighted spatial distribution of pedestrian crashes in the City of Chicago across two windows: pre-COVID-19 (2017–2020) and post-COVID-19 (2021–2024) at the Traffic Analysis Zone (TAZ) level. We employ Moran’s I for both crash frequency and a severity index that weights crashes by injury outcome, and we use Getis-Ord Gi hotspot analysis to identify clusters in each period. Results indicate statistically significant positive spatial autocorrelation for both frequency and severity. Citywide crash counts rose steadily from 2017 to 2020, dropped sharply during the lockdown, and then resumed their prior upward trajectory from 2021 to 2024; however, pedestrian fatalities increased despite the temporary decline in total crashes. Spatially, in the three years prior to the lockdown, the downtown area and the West and South Sides of Chicago (predominantly lower-income neighborhoods) are identified as hotspots. However, in the one-year window following the start of the lockdown, downtown hotspots disappeared, likely due to reduced activity and work-from-home patterns, while persistent and intensifying hotspots were observed on the West and South Sides, especially the South Side. In the three-year window after the lockdown, downtown re-emerged as a hotspot as travel patterns approached a new normal. Although high pedestrian activity in downtown increases the probability of hotspot designation, the consistently identified hotspots on the South Side (predominantly lower-income areas with limited or poor-quality pedestrian infrastructure) indicate a higher priority for safety improvements. These findings underscore the need for place-based safety investments in persistent hotspots to advance long-term Vision Zero Chicago goals.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647781</guid>
    </item>
    <item>
      <title>Exploring the Impact of the Built Environment on Traffic Accidents Using a Multi-Scale Geographically Weighted Random Forest Model</title>
      <link>https://trid.trb.org/View/2613358</link>
      <description><![CDATA[Exploring the potential impacts of built environment factors on traffic accidents is crucial for rational and coordinated urban planning, as well as for enhancing traffic safety. Previous studies have typically analyzed the spatial variability and non-linearity of the built environment’s impact on traffic accidents separately, often overlooking the benefits of integrating these two aspects. To address this gap, this paper develops an innovative Multi-Scale Geographically Weighted Random Forest model. Initially, this study refined the built environment indicators, applied the MGWR model to calculate regression coefficients for traffic accident rate, and visually analyzed the spatial variability of these impacts. Subsequently, these coefficients were incorporated into the RF model to train and predict the non-linear impacts on the traffic accident rate. Finally, the importance of each built environment explanatory variable was ranked to guide traffic planning and safety management.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613358</guid>
    </item>
    <item>
      <title>Evaluation Methods for Urban Expressway Weaving Sections Based on a Risk Index Model: A Driving Simulation Study</title>
      <link>https://trid.trb.org/View/2613356</link>
      <description><![CDATA[Urban expressway weaving sections, characterized by complex vehicle interactions such as merging, diverging, and lane changing, are critical areas in traffic safety research. This study employs a driving simulation experiment to design scenarios with varying weaving section lengths, traffic flow densities, and driving paths. A risk index model is developed to quantitatively assess the operational risks in these sections. The results indicate that weaving section length, traffic flow density, and driving paths significantly influence risk levels. The proposed risk classification method provides a scientific basis for the safety management of weaving sections.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613356</guid>
    </item>
    <item>
      <title>Research on the Risk Identification Mechanism of Driving Behavior Based on Multi-Source Data Fusion</title>
      <link>https://trid.trb.org/View/2613098</link>
      <description><![CDATA[Considering the safety risks associated with highway driving, such as damage to highway infrastructure, sudden traffic accidents, and extreme weather conditions, this study analyzes a substantial amount of historical traffic accident data along with the corresponding driving behavior characteristics at the time of these incidents. Employing a multi-source data fusion approach, the research aims to uncover insights that cannot be derived from a single data set. It comprehensively examines various traffic factors, including the state of vehicle movement, driver behavior within the vehicle, and the dynamic external environment at the moment of the accident. By constructing a behavior chain framework to decompose driver actions, this paper explores the intricate relationship between driving behavior characteristics and traffic accidents, ultimately offering new theoretical perspectives for driver training and traffic safety management.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613098</guid>
    </item>
  </channel>
</rss>