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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>Autonomous Emergency Collision Avoidance and Collaborative Stability Control Technologies for Intelligent Vehicles: A Survey</title>
      <link>https://trid.trb.org/View/2659152</link>
      <description><![CDATA[This paper presents a comprehensive literature review on intelligent driving technologies, with a special emphasis on Automatic Emergency Collision Avoidance Technology (AECA) and Collaborative Stability Control (CSC). These technologies play a crucial role in the active safety of vehicles. AECA proactively detects and responds to potential collisions, and CSC enhances vehicle stability by integrating various systems across multiple driving scenarios. The synergy between AECA and CSC is essential for improving passenger safety and the overall efficiency of traffic systems. This review delves into the application of AECA and CSC, particularly under conditions that might compromise vehicle stability, emphasizing the crucial balance between safety and stability in collision avoidance scenarios. The paper discusses the challenges faced by intelligent vehicles, such as the strong coupling nonlinearity in vehicle dynamics, unpredictable environmental conditions, and the increasing complexity of control systems. It examines strategies in braking, steering, and the coordination of multiple systems to achieve effective collision avoidance and stability control. Additionally, the review provides a forward-looking perspective on potential developments and insights for ongoing research in domains of AECA and CSC within intelligent technologies. The goal is to present a structured overview of the current state of research, highlight significant findings, and identify critical areas where future research could significantly advance the field of intelligent driving systems.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659152</guid>
    </item>
    <item>
      <title>Impact of the built environment on urban mobility patterns and advanced transport dynamics: A systematic review</title>
      <link>https://trid.trb.org/View/2656335</link>
      <description><![CDATA[This systematic review explores the complex relationships between the built environment, transport systems, and travel behaviors, synthesizing findings from 62 studies screened from the Scopus database. The review highlights how factors like infrastructure quality, transportation network connectivity, and land use diversity influence travel patterns. Key findings show that high-density bicycle networks and mixed-use urban developments promote active transportation, though their effectiveness varies by socio-economic and cultural contexts. Emerging mobility innovations, such as electric bicycles and dockless bike-sharing, further complicate these dynamics. The review also underscores the importance of subjective factors like perceived safety and comfort, alongside objective built environment attributes. Public transit systems, particularly rail networks, are crucial for facilitating multimodal travel and fostering urban development, but challenges related to equity and accessibility persist. Future research should focus on adaptive strategies that integrate advanced technologies, localized planning, and inclusive policies to enhance urban mobility, sustainability, and equity.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:52:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2656335</guid>
    </item>
    <item>
      <title>A Group Decision-Making Based Spherical Fuzzy MCDM Approach for Smart Airports</title>
      <link>https://trid.trb.org/View/2648627</link>
      <description><![CDATA[Recent technological developments have changed the business landscape in the aviation industry. The widespread use of advanced digital technologies has transformed customers’ and passengers’ behaviors and expectations, as well as the future trajectory of the industry. The aviation ecosystem is characterized by its complexity, comprising numerous components, players, and systems. Within this framework, airports hold significant importance as they function as critical junctions for all components, stakeholders, and participants involved in the industry. The smart airport concept has become a buzzword with the integration of digital technologies into airports to offer innovative solutions and seamless passenger experiences. At this point, it is critical to understand the characteristics of a smart airport. However, transitioning to a smart airport is a strategic decision-making process that requires considering multiple criteria. Therefore, this study aims to identify and analyze the characteristics of smart airports to inform future strategies and roadmaps for decision-making. It emphasizes the importance of technology selection and investment planning through a group decision-making (GDM) approach. The study systematically collects characteristics through a comprehensive literature review and the insights of three decision-makers (DMs) who possess expertise in the industry. To evaluate the suitability, accuracy, and validity of these characteristics, the research utilizes the Spherical Fuzzy Analytic Hierarchy Process (SF AHP) methodology within the context of an airport in Turkey. The study findings indicate that technology infrastructure plays a crucial role in smart airports. Additionally, cybersecurity, interactivity, human-machine collaboration, connectivity, and technology strategy should be prioritized within the smart airport ecosystem.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2648627</guid>
    </item>
    <item>
      <title>Artificial Intelligence in Maritime Cybersecurity: Dual-Use Applications for Defense and Offense in the Age of Digital Seas</title>
      <link>https://trid.trb.org/View/2598397</link>
      <description><![CDATA[The maritime sector’s rapid digital transformation – including the integration of IT and operational technology (OT) systems and the rise of autonomous vessels – has significantly expanded the cyberattack surface[1] . Artificial Intelligence (AI) now plays a dual role in this landscape, acting as both a powerful enabler of cyberattacks and a critical tool for cybersecurity defense [2] . This paper explores current and emerging uses of AI in offensive and defensive cyber operations targeting maritime systems and infrastructure. On the offensive side, threat actors are leveraging AI for sophisticated attacks such as AI-generated spear phishing, polymorphic malware generation, GPS spoofing, and manipulation of industrial control systems (ICS)[3], [4]. On the defensive side, AI is employed in anomaly detection, predictive analytics, autonomous vessel and port monitoring, and other security applications[5]. The paper also examines vulnerabilities of AI itself – including adversarial attacks, data poisoning, and model manipulation – and discusses strategies to enhance maritime cyber resilience. Key strategies include the use of digital twin simulations, AI-driven deception (honeypots), adversarial training, explainable AI, and international cooperation for information sharing. By analyzing both offensive and defensive developments, this study provides a comprehensive perspective on the dual-use nature of AI in shaping the future of maritime cybersecurity.]]></description>
      <pubDate>Mon, 22 Dec 2025 17:03:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2598397</guid>
    </item>
    <item>
      <title>Traffic-IT: Enhancing traffic scene understanding for multimodal large language models</title>
      <link>https://trid.trb.org/View/2599198</link>
      <description><![CDATA[In recent years, the convergence of artificial intelligence and urban infrastructure has driven transformative advances in intelligent transportation systems (ITS). However, traditional models often lack the generalizability needed to adapt to diverse traffic scenarios. Multimodal large language models (MLLMs) offer a promising solution, yet they are typically trained on general datasets, limiting their effectiveness in specific transportation contexts. To address this, we introduce Traffic-IT, a dataset comprising 220,950 question-and-answer pairs from 30,000 images, designed to enhance MLLMs’ capabilities in traffic scene understanding. The dataset covers various traffic scenarios, including weather conditions, locations, and times of day, providing in-depth insights and driving strategies tailored to real-world needs. Created through expert consultation and rigorous validation, Traffic-IT significantly improves MLLMs’ performance in interpreting complex traffic scenes. We anticipate that Traffic-IT will be a crucial resource for future developments in smart city applications.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599198</guid>
    </item>
    <item>
      <title>Additively Manufactured Aluminum-Lithium Alloys—Advances, Challenges,
     and Future Directions</title>
      <link>https://trid.trb.org/View/2631612</link>
      <description><![CDATA[Aluminum-lithium alloys are extensively used across various industries due to                     their exceptional strength-to-weight ratio, excellent fatigue/corrosion                     resistance and good thermal stability. These attributes, combined with improved                     weldability and ease of fabrication, make them ideal for lightweight engineering                     applications in sectors such as aerospace, automotive, and defense. Additive                     manufacturing (AM) offers unique opportunities to fully leverage the potential                     of aluminum-lithium alloys by enabling the fabrication of complex geometries,                     minimizing material waste, and supporting on-demand production. This paper                     explores the significance of lightweight materials, traces the evolution of                     aluminum-lithium alloys and provides a comprehensive overview of their AM. It                     discusses the properties and real-world applications of these alloys and                     examines various AM techniques employed in their processing. Key advancements in                     the AM of aluminum-lithium alloys are reviewed, including novel alloy                     formulations, development of high-lithium-content variants, microstructural and                     mechanical property enhancements through heat treatment, defect mitigation                     strategies, and surface treatment methods for performance improvement.                     Challenges associated with the AM of aluminum-lithium alloys are also addressed.                     The paper concludes by outlining future research directions and technological                     developments aimed at advancing AM processes for next-generation lightweight                     engineering solutions.]]></description>
      <pubDate>Wed, 26 Nov 2025 10:45:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2631612</guid>
    </item>
    <item>
      <title>Integrated Environmental Assessment of Aviation Activities in the Kingdom of Bahrain</title>
      <link>https://trid.trb.org/View/2592312</link>
      <description><![CDATA[The growing air transport industry is under pressure to identify strategies for greenhouse gas (GHGs) emission reduction, specifically CO2, by incorporating sustainable and carbonneutral operations. This study follows an Integrated Environmental Assessment (IEA) methodology through the Driver-Pressure-State-Impact-Response (DPSIR) framework and policy analysis to evaluate the relationship between aviation-related activities and carbon emissions. It also suggests future policy pathways to achieve a sustainable scenario. The study area is the Kingdom of Bahrain, a Small Island Developing State (SIDS) in the Arabian Gulf region. The findings reveal that aviation activities and related ground operations have increased in recent years, resulting in a 7% annual increase in emissions since 2013 and a 4.88% projected increase for the coming years by 2030. In addition, Bahrain’s location and its economic developments have been the main factors influencing aviation emissions. The average growing population rate of 2.7% has put an additional demand on the air transport system to expand its infrastructure, increase aircraft fleets, and upgrade facilities. The study uniquely identified a lack of distinct institutional mechanisms and a requirement for legislative standardization at both national and industrial levels. Through policy analysis, Bahrain’s national policies and industry-level policies are mostly regulatory instruments, with varying degrees of effectiveness. It also recommends that research gaps in local aviation impacts be technically filled to assist Bahrain in achieving its 2060 goal of Net Zero emissions.]]></description>
      <pubDate>Thu, 30 Oct 2025 08:49:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2592312</guid>
    </item>
    <item>
      <title>Innovative Highways: A New Era Begins</title>
      <link>https://trid.trb.org/View/2608100</link>
      <description><![CDATA[Attention in this article is directed to three recent events that indicate a new era for the nation's highway system. First, the Transportation Research Board (TRB) has just released a report entitled America's Highways: Accelerating the Search for Innovation. Published as part of TRB's Strategic Transportation Research Study (STRS), this report identifies six high-priority, high-payoff targets for a large-scale, concentrated research effort. Second, on July 17, 1984, the American Association of State Highway and Transportation Officials (AASHTO) endorsed the STRS Program and decided to seek legislation that would direct 1/4 of 1 percent of federal-aid highway funds in support of the program. Third, on the basis of a recent Congressional report, Highway Transportation Infrastructure Research and Technology, early indications are that the U.S. Congress may be receptive to this proposal. This report recommends renewing the nation's commitment to highway and bridge materials and structures research, increasing the proportion of funds available for research, and concentrating research support on a small number of critical high-payoff research problems. The STRS, AASHTO, and Congressional recommendations are nearly identical in terms of how highway research should be reoriented to meet the needs of the future. In addition, Federal Highway Administrator Ray A. Barnhart has been an enthusiastic supporter of the proposals that are emerging. Together, these developments reflect a widespread sentiment that major new initiatives to stimulate innovation in the highway sector will be a reality in the very near future.]]></description>
      <pubDate>Sat, 18 Oct 2025 18:52:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608100</guid>
    </item>
    <item>
      <title>Regional-scale bridge health monitoring: survey of current methods and roadmap for future opportunities under changing climate</title>
      <link>https://trid.trb.org/View/2571979</link>
      <description><![CDATA[Climate-related extreme events are becoming increasingly frequent, posing significant threats to bridges, which are critical components of transportation infrastructure. This paper offers an overview of recent advancements in methodologies and technologies for conducting structural health monitoring (SHM) of bridges over large areas, where deploying sensors on every structure may be cost-prohibitive for local administrations. It specifically examines two approaches that have garnered interest in the past decade: indirect SHM, which involves instrumenting vehicles and analyzing their dynamic responses to infer information about bridges, and satellite interferometric radar data, which offer static displacement measurements for large regions and has recently been exploited for civil SHM purposes. Additionally, it reviews the recent developments in population-based SHM, which facilitates knowledge-sharing among structures with similar characteristics within a population. Through an analysis of the advantages and limitations of these three rapidly developing research areas, the paper outlines future opportunities and lays the roadmap for a comprehensive “regional-scale SHM” approach based on remote and/or crowdsourced data, supported by population-level analyses. Specific topics addressed include strategies for similarity assessment among monitored structures, available data sources, and feature extraction/integration approaches for different scenarios.]]></description>
      <pubDate>Thu, 25 Sep 2025 09:30:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571979</guid>
    </item>
    <item>
      <title>Sustainable Aviation: A Critical Review of Policies, Technologies, and Future Pathways</title>
      <link>https://trid.trb.org/View/2576960</link>
      <description><![CDATA[This review critically examines the evolving landscape of sustainable aviation, focusing on the interdependent roles of policies, technologies, and future strategies in decarbonizing the air transport sector. The study synthesizes developments across five key domains: international and regional regulatory frameworks, technological innovations in propulsion and fuel systems, operational and market-based measures, persistent challenges, and long-term transition pathways. Particular emphasis is placed on sustainable aviation fuels (SAFs), electric and hydrogen propulsion, air traffic management modernization, economic viability, technological maturity, regulatory uncertainty, and consumer behavior. The analysis highlights the importance of integrated policy approaches, public-private partnerships, investment in research and development (R&D), and consumer engagement as enablers of systemic change. While meaningful progress has been achieved, especially in SAF development and emissions optimization technologies, the sector faces substantial hurdles in aligning with global climate goals. The review concludes by offering a roadmap for coordinated action and identifies knowledge gaps that merit future research. This research aims to inform policymakers, industry leaders, and researchers committed to steering aviation toward a more sustainable, resilient, and equitable future.]]></description>
      <pubDate>Mon, 08 Sep 2025 14:54:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2576960</guid>
    </item>
    <item>
      <title>A Scheduling Assistant Toolkit for GDOT’s Effective Planning of Transportation Projects</title>
      <link>https://trid.trb.org/View/2569138</link>
      <description><![CDATA[The Scheduling Assistant Toolkit was developed to enhance the Georgia Department of Transportation’s (GDOT) project scheduling efficiency by providing data-driven recommendations on optimal activity overlapping strategies. Traditional scheduling methods often rely on finish-to-start dependencies, leading to unnecessarily long project durations and inefficiencies in resource utilization. This research introduces a scheduling assistant toolkit that integrates rule-based decision frameworks, risk-cost trade-off analysis, and productivity benchmarking to determine the most effective level of activity overlap while minimizing risks such as rework, inefficiencies, and delays. A key component of the study involved benchmarking location and trade productivity on a synthetic GDOT highway project to quantify productivity losses due to handoffs, work discontinuities, inefficiencies, and ineffectiveness. Results revealed that substantial productivity losses stem from crew transitions and poorly synchronized workflows, emphasizing the need for improved scheduling strategies. The toolkit utilizes Python-based algorithms to automate critical path detection, overlapping decision logic, and cost modeling, allowing project managers to evaluate various scheduling scenarios dynamically. Future developments will focus on pilot testing in GDOT projects, integration with existing scheduling systems like Primavera P6, and scalability for more complex infrastructure projects. By adopting this Scheduling Assistant Toolkit, GDOT can achieve shorter project durations, improved resource efficiency, and cost-effective construction management, setting a new standard for transportation project scheduling]]></description>
      <pubDate>Wed, 20 Aug 2025 15:28:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569138</guid>
    </item>
    <item>
      <title>How Autonomous Bus Trials Affect Passengers’ Views: Exploring the Gap Between Pre-Ride Expectations and Real Word Experience</title>
      <link>https://trid.trb.org/View/2585720</link>
      <description><![CDATA[The study investigates passengers’ perceptions of a real-world trial involving a level 4 full-sized Automated Bus (AB) operating as a commercial service on a 22 km inter-urban route along public roads in East Scotland. By focusing on a trial, where the AB navigates mixed traffic, different road types (including motorways) and operates at speeds of up to 80 km/h, this research fills a significant gap in the existing literature, which has offered limited exploration of passenger AB experiences in such complex and realistic operational environments. The contribution of this study lies in providing a comprehensive analysis of passenger expectations and satisfaction, considering both the automated driving technology and the service in all its aspects, while also taking into account their interactions. Results (n = 490) revealed generally positive views from passengers with 61.7 % indicating that the AB technology exceeded their expectations and 71.1 % expressing a high likelihood of recommending the service to others. A binary probit model with random parameters showed satisfaction with ride smoothness and vehicle noise, low pre-ride expectations, and a willingness to use unstaffed ABs were key determinants of post-trial evaluation. In addition, frequency of bus use and gender were found to have mixed effects. A second binary probit model found that high pre-trial expectations, infrequent car use, and frequent bus use influenced the net promoter score, with satisfaction with AB driving style and with service characteristics having heterogeneous effects. These findings offer valuable insights for the transport industry, guiding their future developments and strategies for the successful implementation of AB technology.]]></description>
      <pubDate>Wed, 20 Aug 2025 11:57:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2585720</guid>
    </item>
    <item>
      <title>Research on drivers’ hazard perception and visual characteristics before vehicle-to-powered two-wheeler collisions</title>
      <link>https://trid.trb.org/View/2569161</link>
      <description><![CDATA[Understanding drivers’ hazard perception levels and visual behavior in conflict scenarios is crucial for improving traffic safety and advancing intelligent driving systems, especially given the growing complexity of traffic conditions and the rapid evolution of intelligent driving technologies. This study examines typical near-collision scenarios involving vehicles and powered two-wheelers, focusing on the effects of collision scenarios, driving states, and risk conditions on drivers’ hazard perception and visual characteristics. Using quantile regression and generalized linear mixed models, the study quantitatively assesses how these factors influence hazard perception and visual behavior, uncovering the visual response mechanisms underlying hazard perception. The results reveal that different vehicle-to-powered two-wheeler collision scenarios significantly affect drivers’ hazard perception and visual behavior. Drivers exhibited higher hazard perception levels and collision avoidance success rates in “Crossing from Right” and “Cut-in from Right” scenarios, whereas lower hazard perception abilities were observed in “Crossing from Left” and “Oncoming” scenarios. Fatigue was shown to severely impair drivers’ alertness and visual search abilities, resulting in diminished hazard perception levels. Under high-risk conditions, while drivers exhibited reduced collision avoidance success rates, their heightened attention and vigilance toward powered two-wheeler enhanced hazard perception. Besides, the study also highlights a strong correlation between visual characteristics and drivers’ hazard perception. These findings are significant for understanding the mechanisms underlying drivers’ hazard perception in intersection scenarios and may provide a scientific basis for future developments in human–machine collaborative monitoring and intelligent traffic safety strategies.]]></description>
      <pubDate>Tue, 22 Jul 2025 14:39:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569161</guid>
    </item>
    <item>
      <title>Advances and perspectives in fire safety of lithium-ion battery energy storage systems</title>
      <link>https://trid.trb.org/View/2495156</link>
      <description><![CDATA[With the advantages of high energy density, short response time and low economic cost, utility-scale lithium-ion battery energy storage systems are built and installed around the world. However, due to the thermal runaway characteristics of lithium-ion batteries, much more attention is attracted to the fire safety of battery energy storage systems. In this review, the authors comprehensively summarize recent advances in lithium iron phosphate (LFP) battery fire behavior and safety protection to solve the critical issues and develop safer LFP battery energy storage systems. Firstly, the authors overview the recent developments in thermal runaway mechanisms, gas venting behavior and fire behavior evolution at the battery, module, pack, and energy storage container levels. Afterward, the advanced thermal runaway warning and battery fire detection technologies are reviewed. Next, the multi-dimensional detection technologies that have applied in battery energy storage systems are discussed. Moreover, the general battery fire extinguishing agents and fire extinguishing methods are introduced. Finally, the recent development of fire protection strategies of LFP battery energy storage systems is summarized, and the future directions of firefighting technology are prospected.]]></description>
      <pubDate>Fri, 20 Jun 2025 17:03:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2495156</guid>
    </item>
    <item>
      <title>Systematic review railway infrastructure monitoring: From classic techniques to predictive maintenance</title>
      <link>https://trid.trb.org/View/2499469</link>
      <description><![CDATA[The efficiency and availability of modern railway infrastructure plays an increasingly strategic role in the sustainability, development and prosperity of communities and nations. Recent Artificial Intelligence (AI) algorithms, which enable the use of digital tools such as Data-Driven models that can automatically adapt system operation, make decisions and suggest strategies based on collected data, form the basis of modern Predictive Maintenance (PdM). PdM is considered a key opportunity for accurate Structural Health Monitoring (SHM), especially for railway infrastructure, where the transition from traditional preventive or periodic maintenance to PdM will reduce intervention times and costs. Furthermore, by directly correlating actual infrastructure conditions with measured information, SHM can utilise a limited number of sensors installed on critical components such as insulated rail joints. This review starts by clearly describing the different components that make up the railway infrastructure, the monitoring systems currently in use and the technical performance parameters that indicate their health status and goes on to examine the issues related to the SHM and related modern digital tools. All these topics are summarised to provide an effective theoretical and practical knowledge of SHM for railway infrastructure, to better understand the current transformation of the sector and to predict future developments.]]></description>
      <pubDate>Tue, 18 Feb 2025 10:45:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2499469</guid>
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