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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>The TANGENT Project Architecture: Towards New Traffic Management Approaches</title>
      <link>https://trid.trb.org/View/2671799</link>
      <description><![CDATA[The TANGENT project (www.tangent-h2020.eu/) aims to address the challenges of urban transportation, including traffic accidents, greenhouse gas emissions, and congestion. The project focuses on optimizing traffic management and enhancing mobility through a distributed, modular, and scalable architecture. TANGENT collects and harmonizes data from various sources, including sensors, users, vehicles, schedules, pricing, and traffic flows. It uses this data to create enriched information for different transport stakeholders. The project combines technologies such as data gathering, travel behavior modeling, traffic prediction and simulation, and transport network optimization to provide advanced transport management services. This paper is focused on presenting the project architecture developed to implement four services: data collection and harmonization, enhanced information service, real-time traffic management, and transport network optimization. The project involves a consortium of organizations from nine European countries and aims to pilot its integrated tool in multiple cities in 2024.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:05:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671799</guid>
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    <item>
      <title>Digital Transformation in the Transportation Sector: Unleashing the Power of Data</title>
      <link>https://trid.trb.org/View/2671012</link>
      <description><![CDATA[The transportation sector is undergoing a profound transformation, utilizing digital technologies to move people and goods more efficiently. Data and analytics play a pivotal role as the core of digital transformation and insights-based decision making, as organizations are realizing the necessity of effectively leveraging their data assets. This paper discusses how advanced data analytics techniques, such as artificial intelligence, and solutions can be harnessed to embrace digital innovation and improve operations and services while respecting the transportation industry’s unique requirements regarding stakeholder engagement, user needs, supply chain, legacy systems, stringent safety and security regulations, and system interoperability. This discussion is built around project examples: a Digital Engineering Information Management solution for managing large and complex road construction programs; natural language processing on traffic incident data; a telematic assessment of fuel consumption and emissions from road traffic; and the predictive maintenance of transportation infrastructure. This paper concludes with the proposal of a systematic framework that encourages best practices, clarity, efficiency, and successful outcomes and value extraction from data analytics projects for the transportation sector.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671012</guid>
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      <title>Railway System Digital Twin: A Tool for Extended Enterprises to Perform Multimodal Transportation in a Decarbonization Context</title>
      <link>https://trid.trb.org/View/2671009</link>
      <description><![CDATA[To achieve our long-term goal of doubling the modal share of freight transport by rail and develop multi-modality in transports in France, a fine control over the railway network management is required to better synchronize rail transport with other modes of transport e.g., cars, trucks, trams. The Digital Twin (DT) of the railway system and the extended enterprise are central concepts in our approach to answer this problem. Our method aims at giving access to our railway system's Digital Twin through a Service Oriented Architecture (SOA). This architectural choice facilitates seamless communication and interaction with our partners, fostering a dynamic exchange of information critical for effective multimodal transportation planning. This article describes our approach with a successful implementation of an initial version of our infrastructure Digital Twin, complemented by services designed to meet the diverse expectations of users. This milestone underscores our commitment to leveraging cutting-edge technology and collaborative frameworks to enhance railway management, promote sustainable transportation practices, and contribute significantly to the reduction of GHG (Greenhouse Gas) emissions. As we continue to refine and expand our Digital Twin capabilities, we remain dedicated to advancing the future of intelligent and eco-friendly transportation systems.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671009</guid>
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    <item>
      <title>Processing Digital Railway Planning Documents for Early-Stage Simulations of Railway Networks</title>
      <link>https://trid.trb.org/View/2671006</link>
      <description><![CDATA[The digitalization of the railway domain is a key enabler for more efficient railway operations matching the future needs of society. One part of this process is the digitalization of planning processes, replacing the use of paper-based plans with digital formats. Digital planning documents also open new possibilities, e.g., deriving representative simulation in early project stages. A commonly used simulator for such purposes is the Simulation of Urban Mobility (SUMO). To use the capabilities of SUMO, we are presenting a tool chain for unifying planning documents and generating simulation configurations from them. The core of this tool chain is the yaramo model, covering mainly the topology, geography, and the control command and signaling (CCS) infrastructure of the railway network. The tool chain consists of three major layers: Importers to support multiple data sources (such as PlanPro or OpenRailwayMap), processors to enrich the model, and exporters to support various consumers of the model. This leads to several applications, such as rail network performance evaluations and test automation for CSS infrastructure. Ultimately, our work aims to support the digitalization process of the railway domain, especially the digital planning and development of railway networks.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671006</guid>
    </item>
    <item>
      <title>Assessing the Operational Safety of New Energy Truck Platoons under Information Uncertainty and Longitudinal Slope</title>
      <link>https://trid.trb.org/View/2707945</link>
      <description><![CDATA[Autonomous truck platooning represents a transformative advancement in modern highway logistics, offering substantial benefits in fuel efficiency and traffic throughput. However, the practical deployment of such systems is frequently compromised by sensing limitations and environmental factors, particularly localization uncertainty and varying longitudinal road slopes. In this study, the desired safety margin (DSM) model is employed to systematically investigate how these variables jointly affect platoon-level string stability and the safety performance of car-following maneuvers. Through rigorous linear stability analysis, we derived a novel stability criterion that explicitly accounts for stochastic localization errors and road geometry parameters. The findings reveal a critical trade-off: a negative uncertainty value, indicating a conservative distance estimation, significantly expands the stable region, thereby reinforcing platoon stability and mitigating the likelihood of rear-end collisions. Conversely, with positive uncertainty, the stability region is reduced, while dynamic performance is improved by shortening the system’s response time to lead-vehicle maneuvers. Furthermore, although the longitudinal slope has a negligible impact on fundamental stability characteristics, it exerts a decisive influence on operational safety due to the gravity-induced longitudinal acceleration component. Consequently, the results indicate that constraining randomly varying uncertainty within a calibrated range, together with slope-aware control, can optimize the balance between stability and responsiveness, offering valuable theoretical guidance for robust control design in next-generation autonomous heavy-duty vehicles.]]></description>
      <pubDate>Fri, 29 May 2026 09:00:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2707945</guid>
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    <item>
      <title>Ontology for Automated Road Construction Progress Monitoring</title>
      <link>https://trid.trb.org/View/2640342</link>
      <description><![CDATA[Recently, road construction progress monitoring (RCPM) has witnessed advancement through the integration of digital technology to automate road construction progress monitoring (ARCPM). The abundant data and information are generated and shared between various elements of CPM and technology to enable automatic and real-time progress monitoring. However, information heterogeneity is the most common challenge of ARCPM to achieving the leverage of automation through various technologies integrated with the physical construction site. Data distribution and data fusion become complex and expensive processes due to the lack of explicit representation of technology-integrated RCPM. Therefore, the holistic representation of knowledge modelling is required to systematically integrate multiple sources of heterogeneous information to support system interoperability and information management. To achieve this, this research article demonstrates the ontological solution to formalizing the ARCPM domain knowledge. It shares the knowledge representation of a physical site, an information module, and digital technology. METHONTOLOGY, a widely adopted approach, has been used to prepare ontology. The proposed ontology enables shared and formal vocabulary to successfully represent the domain knowledge ARCPM.]]></description>
      <pubDate>Tue, 28 Apr 2026 12:18:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640342</guid>
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    <item>
      <title>Construction and Application of Knowledge Graph for Urban Rail Fire Accident</title>
      <link>https://trid.trb.org/View/2113883</link>
      <description><![CDATA[Urban rail is closely related to every aspect of people's life, but in some aspects of safety prevention and control lack of scientific and reasonable technical means. These defects lead to problems such as lack of initiative in urban rail safety prevention and control, and pertinence in daily hidden trouble investigation and unclear risk identification. To solve the above problems, this paper proposes a method to construct the knowledge graph for urban rail fire accidents. First, the schema layer of the knowledge graph of urban rail accidents is constructed with the help of ontological thinking. Second, the risk identification method and the entity extraction method based on rules and character rules are used to identify named entities. Finally, the named entities are stored in the graph database Neo4j according to the triple relationship. On this basis, the application analysis based on the knowledge graph of urban rail fire accident is proposed in order to realize the active prevention and control, the risk level management, prediction and reasoning. Application example analysis shows that urban rail accident knowledge graph constructing method is scientific and reasonable, and it can be used to provide security of urban rail operation related semantic search, intelligent question-and-answer support, accurate expression and graphical results show. It is proved that the knowledge graph is helpful to provide decision support for urban rail safety management.]]></description>
      <pubDate>Tue, 21 Apr 2026 08:28:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2113883</guid>
    </item>
    <item>
      <title>Prioritizing Safety-Critical Information in the National Airspace System: A Four-Phased Human Factors Methodology and Its Future Applications</title>
      <link>https://trid.trb.org/View/2689428</link>
      <description><![CDATA[This report describes a methodology for sorting and prioritizing safety-critical aeronautical information, developed in response to a National Transportation Safety Board recommendation. The methodology integrates human factors and risk assessment principles to identify systemic vulnerabilities in information management and to align information delivery with operational, cognitive, and contextual demands. The approach applies the bow-tie risk model to represent human factors constructs as threats that weaken preventive barriers. Information characteristics, including volume, relevance, timeliness, and modality, are modeled as drivers of these threats and are explicitly linked to preventive and mitigative controls. The resulting framework supports operationally realistic filtering, sequencing, and delivery strategies. The methodology is executed in phased activities, including expert knowledge elicitation, scenario-based simulation, and development and validation of a decision support tool. Certified professional controllers and other operational roles complete realistic scenarios varying in complexity, traffic load, and environmental conditions. Data include event-linked performance metrics, post-scenario interviews, and standardized measures of workload, Situation Awareness, and trust. Integrated quantitative and qualitative analyses identify patterns in information use, decision making, and operational outcomes. Outputs include evidence-based recommendations for training, interface design, and policy and procedural improvements to reduce operational risk and support resilient operations. The scope is limited to the contiguous United States, with future research recommended for non-contiguous regions.]]></description>
      <pubDate>Thu, 16 Apr 2026 16:54:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2689428</guid>
    </item>
    <item>
      <title>The Digital-First Federal Depository Library Program [video]</title>
      <link>https://trid.trb.org/View/2685499</link>
      <description><![CDATA[The United States Government Publishing Office (GPO) produces and distributes information products and services for all three branches of the Federal Government. For this Transportation Librarians Roundtable, Megan Minta, Collection Development Librarian, speaks about GPO’s history and the scope of its public information programs.]]></description>
      <pubDate>Thu, 09 Apr 2026 13:41:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685499</guid>
    </item>
    <item>
      <title>The impacts of structured and unstructured information sharing on supply chain performance: the roles of information system connectivity, relationship commitment, and demand uncertainty</title>
      <link>https://trid.trb.org/View/2633375</link>
      <description><![CDATA[This research investigates the information sharing (IS) activities between firms and their customers and inquiries into their impacts on supply chain performance (SCP). Following the information processing theory, this study illuminates a less-explored yet crucial classification of IS activities, structured IS and unstructured IS, and investigates their impacts on SCP under different levels of demand uncertainty. We also probe into the influence of relationship commitment (a relational antecedent) and information system connectivity (an information system antecedent) on structured IS and unstructured IS. Using data of 410 Chinese manufacturers, our research finds that information system connectivity enables both structured and unstructured IS, whereas relationship commitment merely supports unstructured IS, which positively affects structured IS. Furthermore, structured IS improves SCP, while this impact can’t hold for unstructured IS. Finally, demand uncertainty negatively moderates the relationship between structured IS and SCP, while positively moderating the relationship between unstructured IS and SCP.]]></description>
      <pubDate>Wed, 25 Feb 2026 17:00:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633375</guid>
    </item>
    <item>
      <title>Supply chain digitization and enterprise ESG performance: a quasi-natural experiment in China</title>
      <link>https://trid.trb.org/View/2633373</link>
      <description><![CDATA[Supply chain digitization has promoted information availability and optimized the logistics among enterprises. The relationship between supply chain digitization and enterprise ESG is becoming a new hotspot in the context of sustainable development. This study used data from non-financial enterprises listed on China’s A-share market, and investigated the impact of supply chain digitization on enterprise ESG through the differences-in-differences model. Our findings reveal that supply chain digitization can significantly improve enterprise ESG. The mechanisms by which supply chain digitization affects enterprise ESG include easing financing constraints and improving corporate governance. Additionally, a heterogeneity analysis revealed that supply chain digitization in state-owned enterprises, low-digitization enterprises, enterprises with high institutional shareholding, and enterprises with high media attention can further improve ESG.]]></description>
      <pubDate>Wed, 25 Feb 2026 17:00:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633373</guid>
    </item>
    <item>
      <title>Cooperative partners’ heterogeneity and supplier empowerment: impact on the performance of digital technology collaborative innovation in supply chain</title>
      <link>https://trid.trb.org/View/2633363</link>
      <description><![CDATA[The rapid advancement of digital technology has stimulated collaboration between core companies and suppliers to pursue innovation activities. However, a theoretical framework is necessary to explain the impact of cooperative partners’ heterogeneity on the digital technology collaborative innovation performance in the supply chain. This study employed a multi-case analysis to investigate the collaborative innovation process of four Chinese case companies with their suppliers. Based on interviews and analyses, this study found that cooperative partners’ heterogeneity influences the digital technology collaborative innovation performance through supplier empowerment. Aligned strategic objectives, similar digital technology maturity, and complementary digital resources help achieve supplier empowerment and thus promote the performance improvement of digital technology collaborative innovation, such as digital technology R&D, resource access, and process improvement.]]></description>
      <pubDate>Tue, 24 Feb 2026 08:30:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633363</guid>
    </item>
    <item>
      <title>Suppliers 4.0 digital capabilities development in support of digital supply chains: a scoping review</title>
      <link>https://trid.trb.org/View/2633361</link>
      <description><![CDATA[Digital transformation of Supply Chains (SCs) is imperative to remain competitive. Suppliers must adapt and digitally integrate into the emerging Digital Supply Chains (DSCs). This review examines how to develop the next-generation Supplier Development Programs (SDPs) in the context of DSCs in terms of the requirements to digitally transform a SC, and the emerging Digital Capabilities (DCs) needed by their members. A PRISMA scoping review was conducted to analyse existing research on DSC transformation frameworks and relevant DCs for the next-generation suppliers to digitally transform into “Suppliers 4.0” and support their emerging DSCs. Findings point out that there is no conclusive evidence in the scientific literature of a well-established Digital Transformation Framework (DTF) supporting the development of DCs in the current supplier base. An outlook is presented on the fundamental enablers for developing DSC capabilities and their alignment with the DCs required by suppliers.]]></description>
      <pubDate>Tue, 24 Feb 2026 08:30:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633361</guid>
    </item>
    <item>
      <title>Exploring the adoption of e-commerce platform for container shipping bookings</title>
      <link>https://trid.trb.org/View/2633355</link>
      <description><![CDATA[Digitalisation has become one of the strategies for enterprises to stay competitive today, the maritime shipping servicing industry is no exception. The electronic-commerce (e-commerce) platform is one of the digitalisation attempts. Leading shipping lines provide e-commerce platforms for customers to book containers. However, it is unclear about whether these platforms disrupt the current container-booking process, the exact benefits such platforms would bring and the preferences towards the platform from users. This study aims to understand the traditional container-booking process and compare the process with and without an e-commerce platform in order to address above issues. Focus on the container-booking process and the inter-organisational communication during the process, this study unveiled the complexity of maritime shipping service and how e-commerce platforms contribute to efficiency, information sharing and transparency. This study provides managerial insights to freight forwarder managers to adopt and diffuse the e-commerce platform for digitalising the container-booking process.]]></description>
      <pubDate>Tue, 24 Feb 2026 08:30:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633355</guid>
    </item>
    <item>
      <title>Promoting or inhibiting? Digital supply chain impacts on firm performance in Industry 4.0: implication to circular supply chain strategy</title>
      <link>https://trid.trb.org/View/2633354</link>
      <description><![CDATA[Digital supply chain (DSC) is regarded as a sustainable supply chain that manages resources and reduces waste, attracting widespread attention in circular supply chains (CSC). However, it's not clear whether DSC predominantly facilitates or inhibits firm performance in Industry 4.0 amidst disruption and ambidexterity. This study is based on data from A-share listed companies in the past 10 years, exploring the impact mechanism of DSC development in Industry 4.0 on the growth of firm performance from the CSC strategy to examine firm governance boundary conditions. The study concludes that this influence mechanism is dependent on government support. Data-driven CSC strategies in Industry 4.0 help identify inefficiency challenges and risks, providing empirical evidence for the DSC sustainable development in Industry 4.0 amidst disruption and ambidexterity. The results indicate that DSC in Industry 4.0 has a significant promoting effect on firm performance, and DSC towards Industry 4.0 drives firms’ performance.]]></description>
      <pubDate>Tue, 24 Feb 2026 08:30:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633354</guid>
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