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    <title>Research in Progress (RIP)</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>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Integrated Acoustic and Human-Centered Development and Digital Twin Testing for Rail Noise Abatement Strategies in Ohio
</title>
      <link>https://rip.trb.org/View/2712240</link>
      <description><![CDATA[Rail and highway projects tend to run in tandem. Typically, residential areas along rail lines are located at grade separations. As a result, residents can be adversely impacted by rail noise and track vibration. Ohio Department of Transportation (ODOT) consistently receives complaints from residents related to rail noise. Currently, ODOT does not have any defined noise abatement strategies for rail projects. Research is needed to determine if there are feasible, reasonable, cost-effective ways to dampen rail noise for residential and other noise sensitive areas along rail lines.

Research Goal: Identify innovative techniques and/or designs that can aid in the mitigation of rail noise. For this study, rail noise is referring to sounds coming from the tracks and subsequent vibrations, not the train horn. Of particular interest is railroad crossing elimination projects, which are subject to National Environmental Policy Act (NEPA)  assignment and typically include an at grade crossing and the potential for road relocation above existing rail lines. Additional items that should be taken into consideration include ownership, requirements, and costs for installation and ongoing maintenance of all proposed solutions.

Potential Benefits: Effective noise abatement strategies for rail noise could extend benefits currently experienced from highway noise abatement strategies to residential and commercial areas located along rail lines. This includes but is not limited to increased quality of life.        ]]></description>
      <pubDate>Tue, 09 Jun 2026 10:55:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712240</guid>
    </item>
    <item>
      <title>Railway Noise Abatement Strategies: State of the Art and Applicability for Ohio Corridors</title>
      <link>https://rip.trb.org/View/2712239</link>
      <description><![CDATA[Rail and highway projects tend to run in tandem. Typically, residential areas along rail lines are located at grade separations. As a result, residents can be adversely impacted by rail noise and track vibration. Ohio Department of Transportation (ODOT) consistently receives complaints from residents related to rail noise. Currently, ODOT does not have any defined noise abatement strategies for rail projects. Research is needed to determine if there are feasible, reasonable, cost-effective ways to dampen rail noise for residential and other noise sensitive areas along rail lines.

Research Goal: Identify innovative techniques and/or designs that can aid in the mitigation of rail noise. For this study, rail noise is referring to sounds coming from the tracks and subsequent vibrations, not the train horn. Of particular interest is railroad crossing elimination projects, which are subject to National Environmental Policy Act (NEPA) assignment and typically include an at grade crossing and the potential for road relocation above existing rail lines. Additional items that should be taken into consideration include ownership, requirements, and costs for installation and ongoing maintenance of all proposed solutions.

Potential Benefits: Effective noise abatement strategies for rail noise could extend benefits currently experienced from highway noise abatement strategies to residential and commercial areas located along rail lines. This includes but is not limited to increased quality of life. 

The goal of this research is to systematically research and evaluate emerging noise abatement strategies for potential implementation in Ohio's railroad projects. The research team will directly address the effectiveness (cost per dB reduced), cost (including construction and maintenance costs, such as cost per mile), reliability, and implementation hurdles for each strategy, as well as ownership considerations. They will also consider combining measures (e.g., dampers, a short barrier, and a track pad) to achieve additive benefits beyond those reported in existing studies. The proposed project advances the state of practice for railroad noise abatement strategies from scattered information worldwide to a more defined, deployable set. It provides an in-depth evaluation of innovative rail noise abatement solutions, moving beyond the conventional highway noise wall paradigm to more adaptable, rail-specific approaches.            ]]></description>
      <pubDate>Tue, 09 Jun 2026 10:26:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712239</guid>
    </item>
    <item>
      <title>Putting a Price on Regional Rail Quality: Evaluating the Value Potential Riders Place on Regional Rail Service Attributes</title>
      <link>https://rip.trb.org/View/2702083</link>
      <description><![CDATA[Public transit has suffered from chronic disinvestment despite its community-wide benefits. Post-pandemic, drastic changes in travel demand have left agencies grappling with financial stress. California’s transit ridership has generally tracked alongside national ridership trends with a substantial dip in ridership and then slow recovery, but commuter rail mode share has remained substantially lower than pre-pandemic shares. Most rail services are geared towards serving commuters; higher frequency is offered during weekdays and peak hours, ticket pricing is tailored to favor people making the same kind of trip on a regular basis, and service hours align with commuter needs. The five days-a-week commuting to work lifestyle is no more, and rail agencies serving commuters are experiencing decimated ridership that is showing no signs of bouncing back. This project uses survey research targeted towards understanding how to tailor rail services to gain new markets for regional rail services. The research team developed a stated preference (SP) experiment to understand evolving needs of commuters and non-commuters, as well as riders and potential riders. The service attributes under study include train schedule, ticket cost, station access, reliability, station amenities, and how the potential user base views rail services. Although the study will focus on the area defined by its research partner, Capitol Corridor, it is widely applicable across the country in locations with intercity, suburban, and small urban regional rail services.]]></description>
      <pubDate>Wed, 13 May 2026 16:58:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702083</guid>
    </item>
    <item>
      <title>Advancing Rail Infrastructure Asset Management and Hazard Mitigation: Educational Tools and Practitioner Decision Support Systems</title>
      <link>https://rip.trb.org/View/2691664</link>
      <description><![CDATA[As rail infrastructure ages and faces intensifying system stressors (e.g., flooding, icing, and extreme heat), agencies need to identify pathways to enhance the durability and operational reliability of their physical assets. However, there is a significant gap in available training material regarding Rail Infrastructure Asset Management (IAM) for both university students and current practitioners. Building upon the researcher’s ongoing research into adaptive capacity and international rail best practices, this project will translate rigorous research findings into accessible educational and research tools and practical decision-support systems. The project focuses on three primary technology transfer and workforce development initiatives:


(1) Interactive Rail Asset Management Platform: The team will develop a web-based, interactive learning module (utilizing platforms such as Tigyog) targeting students and practitioners. This resource will cover the principles of IAM, condition assessment, and decision-making under uncertainty. It will feature "gamified" scenarios and narrative case studies drawn from the team's research, contrasting infrastructure failures (e.g., the East Palestine, Ohio derailment) with successful engineering adaptations (e.g., the Shinkansen automatic braking systems in Japan). Users will engage with a "build-your-own" asset management framework to apply these concepts in real-time.
(2) University Teaching Packets: To address the lack of specialized rail engineering curricula, the team will create comprehensive teaching modules for instructors. These packets will draw from the team's six-country comparative analysis (U.S., Australia, Spain, Japan, Ghana, Argentina), providing lecture slides, assignment materials, and case-study evaluations. Topics will focus on identifying key asset vulnerabilities, institutional barriers to maintenance, and successful infrastructure hardening strategies.
(3) Practitioner Decision Matrix: The team will develop a "Rail Hazard Mitigation Decision Matrix" for state agencies and rail operators.

This tool will synthesize data on geographic hazards, system ownership models, and cost-benefit ratios to help managers prioritize physical infrastructure improvements.]]></description>
      <pubDate>Sun, 12 Apr 2026 23:25:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2691664</guid>
    </item>
    <item>
      <title>A Probabilistic Intelligence-Driven Framework for Predictive Cyber Defense in Railway Systems</title>
      <link>https://rip.trb.org/View/2655703</link>
      <description><![CDATA[The rapid digital transformation of railway systems through automation, system integration, and enhanced connectivity has significantly improved operational efficiency, safety, and reliability. However, this digitalization has simultaneously expanded the cyber-attack surface, introducing new vulnerabilities in signalling, communication, and control systems. As critical national infrastructure, railways require robust protection against cyber threats to maintain operational resilience and public safety.

Railway cyber-physical environments present unique challenges distinct from traditional IT systems, characterized by strong interdependencies between digital and physical components where a single breach can cascade across subsystems, causing widespread disruption, safety hazards, and financial loss. Existing cybersecurity frameworks, often static and rule-based, are inadequate for representing the dynamic, probabilistic nature of modern cyber threats, necessitating data-informed, adaptive approaches capable of modeling complex dependencies and supporting timely decision-making.

This research develops a probabilistic modeling framework for assessing and mitigating cybersecurity risks in railway systems. The core methodology employs Bayesian Networks (BNs) to capture conditional dependencies among key threat variables, integrating both empirical data and expert knowledge to infer system vulnerabilities and potential attack outcomes. To address evolving threats, the framework extends to Dynamic Bayesian Networks (DBNs), incorporating temporal relationships that model cyberattack progression over time, enabling early threat detection and proactive defense strategies.

A central innovation is the integration of MITRE ATT&CK cyber threat intelligence, encoding real-world adversarial tactics, techniques, and procedures (TTPs) into the BN/DBN structures to enhance model realism and predictive accuracy. This research addresses three key questions: how Bayesian and Dynamic Bayesian Networks can model probabilistic relationships and temporal progression of railway cyber threats; how MITRE ATT&CK intelligence can be integrated to capture realistic adversarial behaviors; and how the proposed framework can support proactive cybersecurity risk assessment and decision-making. The resulting framework provides a systematic, interpretable foundation for probabilistic railway cybersecurity analysis, helping operators and policymakers anticipate and respond to emerging threats.]]></description>
      <pubDate>Tue, 20 Jan 2026 14:16:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655703</guid>
    </item>
    <item>
      <title>Adaptive Cyber Threat Detection for Rail SCADA Systems: A Hybrid Machine Learning and Statistical Approach</title>
      <link>https://rip.trb.org/View/2655702</link>
      <description><![CDATA[Supervisory Control and Data Acquisition (SCADA) systems form the digital backbone of modern railway operations, enabling real-time monitoring of critical track geometry parameters including gage, cross-level, alignment, and warp that are essential for preventing derailments and ensuring passenger safety. While SCADA-driven sensing has advanced continuous condition monitoring, it has also introduced new cyber-physical vulnerabilities, particularly stealthy False Data Injection Attacks (FDIAs) capable of masking real defects or fabricating false positives without detection.

Existing rule-based and signature-based detection systems fail to identify subtle or novel attacks in high-dimensional, noisy rail geometry data, and most current models require labeled attack datasets that are rarely available. Although unsupervised methods such as autoencoders and Variational Autoencoders (VAEs) can detect deviations from learned normal behavior, they remain limited by non-stationary data characteristics and static detection thresholds.

This research proposes a Hybrid VAE with Median Absolute Deviation (MAD) scoring to enable robust, adaptive anomaly detection based on the statistical significance of reconstruction errors. The study investigates whether this approach enhances detection of both subtle and overt FDIAs compared to Isolation Forest and static-threshold VAE baselines, evaluates the effectiveness of MAD-based adaptive thresholding against fixed percentile methods, and examines trade-offs in interpretability, computational load, and reliability across attack intensities.

Using an operational track geometry dataset (18,290 samples, 87 features) from Colorado rail testing, the methodology simulates FDIAs through additive spikes, multiplicative distortion, and high-variance noise injection on safety-critical features. Model performance is evaluated using precision, recall, F1-score, and accuracy, with PCA and t-SNE visualization for validation. Findings will provide actionable deployment guidelines for enhancing cyber-physical resilience in railway SCADA systems.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:16:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655702</guid>
    </item>
    <item>
      <title>Improving Traveler Experience Via Alternatives to Roadway/Railway Grade Crossings  </title>
      <link>https://rip.trb.org/View/2646961</link>
      <description><![CDATA[There are more than 240,000 at-grade crossings between railroads and roadways in the U.S. and as the number of freight trains increases, the times of interface and blocked crossings also increases. USDOT reports numerous driver complaints about delays and frequent disruptions, and in some cases, there are delays to emergency vehicles due to excessive numbers of blocked trains. Work is underway to continue documentation and to consider strategies and address the frequent and repeated delays caused by long trains. The most requested remedy is grade separation. Grade separations are extremely expensive, and planning and construction lead times are long, so there is a need to identify other more short-term strategies that will offer travelers and emergency responders options to waiting on the long trains.  

The focus of this research will be Fort Bend County and Harris County, Texas, which include major freight corridors from Port Houston, the 3rd largest container port in the country. Between the two counties, there are at least 11,000 at grade crossings. Specifically, this work will assemble delay time data showing frequency and duration for the identified railroad crossings. The team will conduct literature review and on-line and in-person conversations to determine options and strategies underway by entities (e.g., railroad operators), municipalities, and others to address better traveler information and options to reduce and avoid delay time. Potential options include cameras noting delays and following with notifications to emergency services proximate to locations with frequent delays. The study team will examine whether this information distribution could be expanded to additional users. An additional option to be examined is message signs alerting travelers to blocked crossings in time to adjust their travel route. The expected research outcome is to provide an option to grade separations that will reduce delay time for travelers caused by blocked train crossings. ]]></description>
      <pubDate>Tue, 06 Jan 2026 17:10:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2646961</guid>
    </item>
    <item>
      <title>Multi-Sensory System for Railway Track Defect Detection </title>
      <link>https://rip.trb.org/View/2646942</link>
      <description><![CDATA[Railway transportation is essential for moving passengers and freight across the U.S., but accidents continue to pose serious safety and economic risks. In 2022 alone, there were about 950 rail-related fatalities and 6,400 injuries nationwide. While human error and reckless behavior are major contributors, defective track infrastructure is a significant and preventable cause of accidents. Railway tracks are complex systems consisting of steel rails, crossties, fasteners, and ballast, all subject to heavy loads, temperature fluctuations, and environmental impacts. These stresses lead to issues such as broken rails, cracked or spalled crossties, loose or missing fasteners, geometry defects, and cross-level variations. Extreme weather conditions can further cause rail buckling or fracture. Failures in these components can trigger derailments, collisions, hazardous material spills, and major service disruptions. Although manual inspections and specialized vehicles are used, many defects go undetected between inspection cycles. Traditional manual inspections, although reliable for identifying visible rail defects, are labor-intensive and limited in scalability. To improve efficiency, various nondestructive testing (NDT) technologies, such as infrared imaging, acoustic emission, ultrasonic, and electromagnetic techniques, have been used primarily for internal defects. As surface defects become more prevalent, various methods have also been developed for detecting surface-level flaws, which can be broadly categorized into three approaches: static monitoring where sensors at fixed locations provide localized coverage; inspection trolleys which integrate sensors generally in the laboratory setting; and onboard sensing systems which enable real-time detection ahead of moving trains but suffer from high cost with varying imaging quality under different weather and lighting conditions. The primary objective of this project is to develop a comprehensive but low-cost multi-sensory system for railway track defect detection. The system will integrate binocular stereovision cameras, Global Navigation Satellite System / Global Positioning System (GNSS/GPS), and IMU sensors. The scope of this project includes development of a multi-sensory system including controller and field data acquisition, development of real-time data fusion and detection algorithms, and recommendations for system deployment on railway tracks. ]]></description>
      <pubDate>Mon, 05 Jan 2026 23:04:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2646942</guid>
    </item>
    <item>
      <title>Quick-Response Research on Long-Term Strategic Issues. Task 55. Impact of Positive Train Control</title>
      <link>https://rip.trb.org/View/2636147</link>
      <description><![CDATA[Positive train control (PTC) is an advanced rail safety technology designed to mitigate human error and improve operational safety. It reduces the risk of accidents by preventing or reducing train-to-train collisions, overspeed derailments, improperly lined switches, and unauthorized incursion into work zones. Public transportation agencies that operate commuter and intercity passenger rail services have been required to have PTC installed since 2020. To meet this deadline, agencies had to invest immense resources into new infrastructure and specially trained staff to develop and test the system. 

While PTC implementation has been extensively documented, less is known about its long-term operational impacts, realized safety benefits, and opportunities for leveraging PTC investments beyond regulatory compliance. Now that agencies have been operating with PTC for several years, research is needed to examine and document how PTC has affected passenger rail safety and how PTC-related infrastructure, data, and workforce capabilities can be leveraged to further enhance safety, security, and operational performance.

OBJECTIVE: The objective of this research is to document and quantify the safety, operational, and organizational impacts of PTC on passenger rail operations subject to the Rail Safety Improvement Act of 2008, and to identify lessons learned, current practices, and benefits realized beyond statutory and regulatory minimum requirements.

RESEARCH PLAN: The TCRP is seeking proposals on how best to achieve the research objective. Proposers are expected to describe research plans that can realistically be accomplished within the constraints of available funds and subaward time. Proposals must present the proposers' current thinking in sufficient detail to demonstrate their understanding of the issues and the soundness of their approach to meeting the research objective.

The research, at a minimum, shall: (1) Identify and summarize existing literature, industry practices, and other relevant resources on the operational safety of PTC. (2) Document the current state of PTC implementation, use, and maintenance across passenger rail agencies. (3) Assess the realized benefits of PTC implementation on passenger rail safety, including operations involving shared-use corridors, passenger operators hosting freight tenants, and passenger operators operating on freight-owned infrastructure.
(4) Quantify, to the extent practical, the safety benefits attributable to PTC systems using available industry data and performance measures. (5) Identify innovative applications of PTC-related infrastructure, data, technologies, and workforce capabilities that extend beyond statutory and regulatory minimum requirements and improve safety, security, and operational efficiency. (6) Examine PTC operating, maintenance, and lifecycle costs to determine eligibility for capitalization or federal funding assistance and identify any relevant statutory, regulatory, or policy considerations.
Proposers are encouraged to identify innovative approaches for collecting information (e.g., stakeholder interviews, focus groups, workshops, surveys, peer exchanges) and for presenting research findings (e.g., case studies, implementation guidance, checklists, fact sheets, other practitioner-oriented tools).

The research plan shall be divided into tasks that detail the work proposed. The research plan shall describe appropriate deliverables (which also represent key project milestones), including, at a minimum: (1) An amplified research plan that responds to comments provided by the project panel at the subawardee selection meeting. (2) An interim report and panel meeting. The interim report should include the analyses and results of completed tasks, an update of the remaining tasks, and a detailed outline of the final research product(s). The panel meeting will occur after the panel review of the interim report. The interim report and panel meeting should occur after the expenditure of no more than 40 percent of the project budget. (3) Final deliverables. The final deliverables should include a conduct of research report documenting the entire research effort. (4) A technical memorandum titled “Implementation of Research Findings and Products” (see Important item IV). (5) A slide deck to be used in webinars that presents the research findings and conclusions.
The research team may include additional deliverables and additional panel meetings via teleconference in the research plan. The research plan shall have a schedule for the project that includes 1 month for panel review of the interim report and 3 months for panel review of the draft final report and for the research team's revision of the draft final report.

IMPORTANT: (1) The brochure Information and Instructions for Preparing Proposals for the Transportation Research Board’s Cooperative Research Programs includes extensive guidance on the preparation of acceptable proposals for submission to CRP. Revisions to these instructions are highlighted in yellow within that document. (2) Proposals will be rejected if any of the proposed research team members work for organizations represented on the project panel. The panel roster for this project can be found here. Proposers may not contact panel members directly; this roster is provided solely for the purpose of avoiding potential conflicts of interest. (3) The text of the final deliverable is expected to be publication ready when it is submitted. It is strongly recommended that the research team include the expertise of a technical editor as early in the project timeline as possible. See Appendix F of the Procedural Manual for Subawardees Conducting Research in the Transportation Research Board’s Cooperative Research Program for technical editing standards expected in final deliverables. (4) The required technical memorandum titled “Implementation of Research Findings and Products” should (a) provide recommendations on how to best put the research findings/products into practice; (b) identify possible institutions that might take leadership in applying the research findings/products; (c) identify issues affecting potential implementation of the findings/products and recommend possible actions to address these issues; and (d) recommend methods of identifying and measuring the impacts associated with implementation of the findings/products. Implementation of these recommendations is not part of the research project and, if warranted, details of these actions will be developed and implemented in future efforts. (5) The National Academies have an ethical and legal obligation to provide proper attribution whenever material from other sources is included in its reports, online postings, and other publications and products. TRB will review all Cooperative Research Programs draft final deliverables using the software iThenticate for potential plagiarism. If plagiarized text appears in the draft final deliverable, the research team will be required to make revisions and the opportunity to submit future proposals may be affected. 

Proposals must be uploaded via this link: https://www.dropbox.com/request/v0aoa3vrj1pnawlnz17t 
Proposals are due not later than 5:00 p.m. Eastern Time on 8/18/2026.
This is a firm deadline, and extensions are not granted. In order to be considered for award, the agency's proposal must be in our offices not later than the deadline shown, or the proposal will be rejected.

General Notes: (1) Regarding non-discrimination practices and policies, proposers are required to comply with applicable federal and state laws and regulations (including without limitation, federal civil rights laws, regulations, and requirements) and follow applicable federal guidance, except as the Federal Government determines otherwise in writing. Without limitation of the foregoing, proposers agree to prohibit discrimination as prescribed by Title VII of the Civil Rights Act of 1964. (2) The essential features required in a proposal for research are detailed in the current brochure entitled "Information and Instructions for Preparing Proposals". Proposals must be prepared according to this document, and attention is directed specifically to Section IV for mandatory requirements. Proposals that do not conform with these requirements will be rejected. (3) The total funds available are made known in the project statement, and line items of the budget are examined to determine the reasonableness of the allocation of funds to the various tasks. If the proposed total cost exceeds the funds available, the proposal is rejected. (4) All proposals become the property of the Transportation Research Board. Final disposition will be made according to the policies thereof, including the right to reject all proposals.
(5) Potential proposers should understand that follow-on activities for this project may be carried out through either a contract amendment modifying the scope of work with additional time and funds, or through a new contract (via sole source, full, or restrictive competition).]]></description>
      <pubDate>Mon, 08 Dec 2025 20:06:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2636147</guid>
    </item>
    <item>
      <title>Automation of Light Rail Transit Services</title>
      <link>https://rip.trb.org/View/2636140</link>
      <description><![CDATA[Public transit agencies are beginning to explore how emerging technologies could reshape light rail transit (LRT) systems. Automation has already transformed metro rail systems in some cities and is being considered in bus rapid transit and fixed-route bus operations. Compared to other modes, light rail, especially when operating in exclusive right-of-way, offers a relatively controlled environment that may make it a strong candidate for early adoption of automation. Light rail automation has the potential to improve safety for all users of the transportation network. However, automated LRT systems deployment remains rare, and many questions persist regarding feasibility, safety, labor impacts, regulatory requirements, and operational complexity.

Light rail operates over fixed guideways and may be augmented by docking systems, warning signage, and signal priority, but conditions vary significantly across lines. Differences in track sharing, mixed traffic conditions, platform design, and operating procedures introduce additional variables that must be accounted for. The labor involved, compliance with the Americans with Disabilities Act (ADA), and security implications of removing onboard staff also raise policy and public acceptance questions that agencies must anticipate. Research is needed to investigate how agencies are approaching this issue, what pilot projects or international examples can teach us, and what technical, regulatory, and institutional barriers remain. In addition, research is needed to examine the governance, workforce, and capital planning implications of automation. A clearer understanding of these factors will help agencies assess the feasibility, risks, and potential benefits of implementation, and develop strategies for integrating automation into their long-term planning and operations.

OBJECTIVE

The objective of this research is to develop a guide that supports agencies and stakeholders in making informed decisions regarding the implementation of automated LRT systems. The guide should provide actionable guidance applicable to a range of system configurations, operating environments, and grades of automation, whether agencies are considering the transition of existing services or the design of new automated LRT systems.  ]]></description>
      <pubDate>Mon, 08 Dec 2025 19:50:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/2636140</guid>
    </item>
    <item>
      <title>Applying a Safe System Framework to Rail-Related Trespassing Deaths and Injuries in North Carolina</title>
      <link>https://rip.trb.org/View/2604727</link>
      <description><![CDATA[According to the Federal Railroad Administration, in 2023, there were 27 trespassing deaths and injuries on rail corridors in North Carolina, a 23% increase from the number of casualties in 2022. Although various research studies, both outside and within North Carolina, have examined the causes of rail trespassing casualties, preventing these deaths and injuries remains challenging due to the complexities of human behavior and the social and environmental conditions that bring pedestrians into contact with rail lines. Therefore, this research project proposes a new, Safe System-based approach to analyzing and addressing pedestrian rail trespassing incidents. 


The Safe System Approach is a public health paradigm of transportation safety management that holds human vulnerability and human fallibility as critical considerations for how to proactively prevent transportation deaths and injuries. The Safe System Approach has been formally adopted by the United States Department of Transportation and is central to the North Carolina Department of Transportation’s (NCDOT's) Strategic Highway Safety Plan. Applications of the Safe System Approach often entail an assessment of three parameters: road users’ exposure to conflicts, the likelihood for those conflicts to become crashes, and the severity of crashes when they occur. In the context of rail trespassing incidents, implementing the Safe System Approach involves understanding pedestrian exposure to rail crossings and the likelihood of trespassing because rail strikes tend to be severe. If the mechanisms behind exposure and likelihood can  be better understood, then countermeasures can be applied.

To accomplish this Safe System assessment, the research team proposes combining multiple data streams to build a  knowledge base of a model rail trespassing incident so that a systems science-based evaluation method, the AcciMap, can be applied to identify the critical risks that lead to fatal and severe trespassing incidents. The team proposes supplementing data collected for previous NCDOT projects with survey data, literature-derived risk factors, desk reviews, and field visits to establish a foundation upon which the team can apply the AcciMap method. Using the causal links identified through AcciMapping, the team can then identify countermeasures to the risks. The team will translate these methods into reproducible, locally relevant guidance for transportation agencies and local governments. 

The team of researchers from the UNC Highway Safety Research Center and North Carolina A&T University are uniquely poised to conduct this research project. They are national leaders in Safe System research and have completed rail safety research upon which this project will build. The team understands the need for novel thinking to address safety risks while also recognizing the hyper-local focus this analysis requires. They are well-equipped to produce useful resources for practitioners, such as a Safe System-based rail safety checklist and guidance for risk identification and countermeasure selection. A final report documenting the project’s findings will be accompanied by presentation materials for sharing results and a more detailed implementation plan to facilitate uptake by State and local transportation agencies.]]></description>
      <pubDate>Tue, 30 Sep 2025 15:38:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2604727</guid>
    </item>
    <item>
      <title>Evaluation of Signs at Highway-Rail Crossings</title>
      <link>https://rip.trb.org/View/2601423</link>
      <description><![CDATA[This project evaluates the safety impacts of replacing STOP signs with YIELD signs at highway–rail grade crossings. The study examines whether this transition has resulted in measurable reductions in crashes and near misses, while also analyzing key crossing characteristics—including traffic volume, train frequency, visibility, and roadway type—that may influence safety outcomes. Findings will be used to provide data-driven recommendations on whether to retain, modify, or reverse the signage change at specific locations, supporting evidence-based decisions for improving transportation safety.]]></description>
      <pubDate>Wed, 17 Sep 2025 16:18:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2601423</guid>
    </item>
    <item>
      <title>Evaluating Ballast Performance with Freeze/Thaw Cycles</title>
      <link>https://rip.trb.org/View/2573189</link>
      <description><![CDATA[In seasonally cold regions, railroad tracks are subjected to ice formation under sub-freezing conditions and ice thawing under above-freezing conditions due to significant seasonal temperature fluctuations, posing challenges for the maintenance of ballasted railway tracks and operation safety. Currently, little attention has been given to the impact of ice formation and thawing on the permanent deformation of railroad ballast and incidents due to track stiffness variation have not been reported. This proposed research project will investigate the effect of ice formation and thawing on the permanent deformation of ballast through large-scale triaxial cyclic testing, utilizing a newly developed freezing system to simulate frozen conditions. The results will demonstrate the potential track support variation when ballast is subject to freeze-thaw cycles, under the same loading cycles. The rate of permanent deformation will be related to track settlement and help predict track geometry degradation and optimize track maintenance for enhanced track safety.]]></description>
      <pubDate>Mon, 14 Jul 2025 20:12:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573189</guid>
    </item>
    <item>
      <title>Rapid Detection of Track Changes from In-Motion Data Acquisition Records: Lab Setup and Field Implementation – Year 3
</title>
      <link>https://rip.trb.org/View/2573191</link>
      <description><![CDATA[Track stiffness is a critical parameter influencing infrastructure integrity, safety, and maintenance efficiency. Track stiffness variations over time and space lead to uneven load distribution, track degradation, and increased risk of failure, necessitating continuous monitoring and timely intervention. Current technologies determine stiffness under loaded or unloaded conditions at discrete locations, or through continuous measurements. They are either costly, labor-intensive, or limited in spatial and temporal resolution. The proposed work is a four-year effort to develop an in-motion system that detects track stiffness and stiffness changes in real-time that is free of the shortcomings of existing techniques. The proposed system is an acceleration-based system that uses hybrid signal processing techniques and machine learning for classification. The system consists of three modules: (1) Data acquisition using onboard vibration sensors; (2) Hybrid signal processing on the edge for feature identification and data compression; and (3) Classification and decision support, utilizing machine learning algorithms for characterization of track conditions in predictive maintenance. This proposal is for Year 3 of the research team's current University Transportation Center for Railway Safety (UTCRS) sponsored effort. Year 1 focused on the development of a track stiffness monitoring concept and produced a feasibility study that led to Year 2 work on method development, and validation through simulations and laboratory small-scale testing. Spurred by the findings of Years 1&2, this proposal focuses on the development of an experimental prototype system and its validation through high-fidelity laboratory testing. In addition, the team proposes to develop a digital twin of the experimental prototype to facilitate extensive validation, calibration, and sensitivity studies to enhance accuracy and scalability. The project will enhance track safety, reduce maintenance costs, and improve railway infrastructure reliability by enabling continuous, cost-effective, and scalable monitoring. The research directly aligns with UTCRS’s strategic goals by advancing infrastructure monitoring technologies and contributes to the United States Department of Transportation (USDOT)’s objectives in safety and economic competitiveness.]]></description>
      <pubDate>Mon, 14 Jul 2025 20:04:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573191</guid>
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    <item>
      <title>Modeling Special Cases of Longitudinal Resistance in Continuously Welded Rail (CWR)</title>
      <link>https://rip.trb.org/View/2573194</link>
      <description><![CDATA[Continuously welded rail (CWR) is the standard for North American freight railroads due to its advantages in ride quality, fatigue life, and reduced maintenance costs, despite concerns about rail buckling and breaks. Longitudinal rail resistance is a critical parameter for re-establishing rail neutral temperature (RNT) after rail breaks and for mitigating potential rail failures caused by vehicle loading, temperature changes, and maintenance activities. This proposed research builds upon a previous year project and continues the effort to refine and enhance the Finite Element (FE) modeling of rail longitudinal resistance. Specifically, it aims to improve the representation of realistic rail and anchor conditions by integrating new experimental data into the FE models. The research will develop efficient 2D and 3D FE models in ABAQUS that incorporate rail-to-tie friction, anchor slip forces, and tie-to-ballast restraint, using both experimental results (e.g., anchor slip behavior under varying load conditions) and historical data (e.g., rail-sleeper friction and sleeper-ballast resistance). The models will accommodate various rail profiles, tie materials, and geometric configurations, and will be applicable to a wide range of track conditions including frozen ballast, frozen structures, turnouts, crossings, and loading scenarios from vehicles and maintenance activities. The proposed project will be executed through four key interconnected areas of research: (1) Effects of sleeper-ballast on models larger than 4-ft in length using FE modeling in ABAQUS, (2) experimental testing in the laboratory for anchor slippage with various anchor types, (3) sensitivity analysis, and (4) model analysis with various track conditions. ]]></description>
      <pubDate>Mon, 14 Jul 2025 19:49:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573194</guid>
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