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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>
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      <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>A Framework for Integrated Quality of Service Evaluation using Operational and Safety Considerations</title>
      <link>https://rip.trb.org/View/2703926</link>
      <description><![CDATA[This project addresses a critical gap in transportation decision-making by examining the relationships among safety and operational performance measures that State DOTs typically use for planning, design, and operations. While agencies rely on different metrics depending on application, such as crash-based measures for safety projects and travel time reliability or delay for congestion management, there is limited guidance on how these measures interact or how they should be jointly considered when evaluating alternatives. Using multi-source data from State DOTs and third-party providers along major corridors in Region VII, the project will quantify correlations, trade-offs, and synergies among key performance measures and develop a practical, multi-objective evaluation framework tailored to common DOT applications. The resulting framework and guidance will enable agencies to conduct more consistent, transparent, and context-sensitive evaluations that better balance safety and operational objectives.
]]></description>
      <pubDate>Thu, 21 May 2026 22:41:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703926</guid>
    </item>
    <item>
      <title>Developing Simplified and Unified Planning-Level Metrics for Operational Benefits </title>
      <link>https://rip.trb.org/View/2663585</link>
      <description><![CDATA[Transportation agencies increasingly rely on Performance-Based Planning and Programming (PBPP) to make transparent, data-driven investment decisions and to evaluate and prioritize projects. In Virginia, Virginia Department of Transportation (VDOT) and the Office of Intermodal Planning and Investment have advanced PBPP through VTrans, Project Pipeline, and SMART SCALE, a recognized program for ranking investments across safety, congestion, accessibility, environmental quality, and economic development. In addition, VDOT’s Project Planning function establishes a long-term vision for the transportation system. Despite progress in Virginia’s planning framework, no rapid and transferable methodology exists to quantify operational benefits of roadway and ITS improvements. Current approaches, such as the Interstate Operations and Enhancement Program and SMART SCALE , provide valuable insights but lack standardized lightweight measures of operational benefit metrics. When VDOT needs to compare alternatives or screen early-stage concepts, analysts must rely on microsimulation, HCM procedures, or project-specific before–after studies. These methods are accurate but slow, data-intensive, and not scalable to dozens or hundreds of candidate projects. The absence of standardized, easy-to-apply operational metrics constrains Virginia’s ability to efficiently screen projects, communicate benefits, and ensure consistent decision-making within PBPP. This research will define Operational Modification Factors, a proportional before/after change derived from operational benefit metrics, and develop a reusable and transferable planning-level methodology that enables VDOT to estimate operational benefits rapidly using limited inputs (e.g., v/c ratio, facility type, AADT, geometry, improvement type). 
]]></description>
      <pubDate>Tue, 03 Feb 2026 10:42:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663585</guid>
    </item>
    <item>
      <title>Framework for Transportation Systems Management and Operations Curricula
</title>
      <link>https://rip.trb.org/View/2558371</link>
      <description><![CDATA[Transportation systems management and operations (TSMO) is a set of strategies focused on operational improvements that maintain and restore the performance of existing transportation systems before additional capacity is required. A wide range of careers falls under TSMO, including intelligent transportation system (ITS) engineers, traffic management control operators, and data scientists. Growing and developing the TSMO workforce requires multiple approaches and strategies, from educating students about TSMO careers to preparing existing professionals from other fields to transition into TSMO roles.

Several resources exist to advance the knowledge, skills, and abilities of TSMO practitioners. For example, the American Association of State Highway and Transportation Officials (AASHTO) Transportation Operations Manual serves as a resource for transportation agencies to develop and sustain the operational capabilities and strategies needed to preserve and optimize system performance. The Operations Academy is a training program designed for mid- to high-level managers whose current or future responsibilities include TSMO. The National Operations Center of Excellence (NOCoE) TSMO Workforce Development website provides a variety of additional resources. However, few initiatives focus on individuals who have not yet entered, or are new to, the TSMO workforce.

Research is needed to help educational organizations develop and align curricula that introduce TSMO concepts, build relevant skills, and connect students with career opportunities in the field.

The objective of this research is to develop a framework for educators to establish recruitment pipelines that expand the talent pool and enhance the competencies of candidates entering the TSMO workforce.]]></description>
      <pubDate>Thu, 29 May 2025 13:03:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558371</guid>
    </item>
    <item>
      <title>Advancing Cyber Resilience of Transportation System Management and Operation Programs </title>
      <link>https://rip.trb.org/View/2558388</link>
      <description><![CDATA[Transportation systems and technology across the United States are becoming increasingly interconnected, spanning local, state, and national borders. This integration supports safe and efficient transportation networks but introduces cybersecurity challenges. Many transportation system management and operation (TSMO) strategies rely on real-time data sharing, integrated traffic management centers (TMC), and interoperable technologies, all of which create new threat vectors for cyber incidents. The potential for severe injuries and fatalities, data loss, service disruptions, and other failures necessitate a more resilient approach to cybersecurity, shifting the focus from merely preventing attacks to ensuring the ability to recover and maintain essential functions during an incident. Research is needed to develop coordinated, cross-jurisdictional frameworks and methodologies to assess, manage, and enhance cyber resilience within integrated transportation systems. 

OBJECTIVE: The objective of this research is to develop a guide for incorporating cyber resiliency into state and local TSMO programs. At a minimum, the guide will address: 
(1) Build the foundation for future TSMO projects involving system integrations; (2) Evaluate and enhance cyber resilience in TSMO programs; (3) Identify cross-jurisdictional TSMO program stakeholders; (4) Improve intra-agency and interagency coordination;
(5) Reduce impacts in the event of cyber incidents; (6) Establish clear responsibilities and recovery processes; and (7) Support risk management through strategic planning. 

Accomplishment of the objective will require at least the following tasks.
TASKS: Task descriptions are intended to provide a framework for conducting the research. The National Cooperative Highway Research Program (NCHRP) is seeking the insights of proposers 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.

PHASE I: (Task 1) Perform a literature review on relevant resources, frameworks, generally accepted industry standards and practices, and reports published by U.S. Department of Transportation (USDOT), National Institute of Standards and Technology (NIST), NCHRP, American Association of State Highway and Transportation Officials (AASHTO), Institute of Transportation Engineers (ITE), National Transportation Communications for Intelligent Transportation System Protocol (NTCIP), National Electrical Manufacturers Association (NEMA), etc. Conduct a national cross-jurisdictional scan (surveys and interviews with the majority of state DOTs and at least one representative municipality from each covered state with TSMO system integration needs) to cover the following topics: (1) Multimodal cybersecurity risks for TSMO projects and programs, including those related to data sharing, interoperability, connected infrastructure, cyber-physical systems (CPS) and multimodal operations. This assessment shall include the potential for failures and data loss across jurisdictional boundaries and transportation modes; (2) Reference materials to integrate cyber resilience and cyber security checkpoints into the systems engineering analysis process and support security by design for pre-procurement, procurement, deployment, implementation, system integration, maintenance and operation, intra-agency and interagency collaboration, and workforce development; (3) Possible threat vectors and mechanisms that would impact TSMO system availability; (4) Methods to map the flow of data, whether it is from a roadside device, such as an automatic traffic recorder, dynamic message sign, or traffic signal controller box, referencing the intelligent transportation system (ITS) system architecture, to detect anomalies in the data, and to devote immediate attention. (5) Near-term risks evolved by emerging technologies, including but not limited to vehicle-to-everything (V2X), digital twins, and artificial intelligence (AI); (6) Tools and noteworthy practices for coordinating cyber resiliency efforts and modes that focus on incident response incorporating identify, protect, detect, respond and recover; (7) Example narratives about how cyber resiliency/security must be embedded into the culture of infrastructure owner operators (IOOs) and across partner agencies; (8) Methods to incorporate ITS cybersecurity training into workforce development for TSMO staff and embedded information technology (IT) supporting staff; and (9) Defined roles and responsibilities for ITS network communications development and support between TSMO staff and IT supporting staff. Conduct gap analysis to identify synergy and conflicts of these topics, and areas for improvement.

(Task 2) Prepare an annotated outline that will serve as the basis for guide development in Task 4. This annotated outline is intended to provide the context for the subject matter in the guide, which will include key technical topics and associated issues, major concepts, current trends, state of the practice, illustrative case studies, and recommendations. The annotated outline shall clearly describe: (a) intended structure of the guide; (b) key topics and supporting issues to be presented in each chapter, using the topics in Task 1 as starting point; and (c) any other items to be included in the guide (e.g., appendix, figures, tables). (Task 3) Prepare Interim Report No. 1 documenting the findings of Tasks 1 and 2 and provide an updated work plan for the remainder of the research no later than 8 months after the subaward is awarded. The updated work plan must describe the methodology and rationale for the work proposed for Phase II. Note: Following a 1-month review of Interim Report No. 1 by the NCHRP panel, the research team will be required to meet with the NCHRP project panel via a virtual meeting to discuss the interim report. Work on Phase II of the project will not begin until authorized by the NCHRP. 

PHASE II: (Task 4) Execute the work plan according to the approved Interim Report No. 1. (Task 5) Prepare Interim Report No. 2 that includes a draft guide based on the final annotated outline and an updated work plan for the remainder of the research no later than 6 months before the subaward end date. The updated plan must describe the process and rationale for the work proposed for Phase III. Note: Following a 1-month review of Interim Report No. 2 by the NCHRP, the research team will be required to meet in person in Washington, DC with the NCHRP project panel to discuss the interim report. Work on Phase III of the project will not begin until authorized by the NCHRP. 

PHASE III: (Task 6) Present the research findings to appropriate technical committees of AASHTO for comments and any proposed revisions. Note: The research team should anticipate making two virtual presentations during the period of performance to appropriate technical committees at AASHTO meetings. Revise the draft guide after consideration of review comments. (Task 7) Prepare the final deliverables, including: (1) Guide. (2) Conduct of research report that documents the entire research effort. (3) Two-pager flyer of outreach materials to increase practitioner awareness and understanding of the guide. (4) Presentation with speaker notes summarizing the research results. The presentation shall specify the research purpose, objective, issues addressed, research product developed, and benefits identified in the guide. (5) Stand-alone technical memorandum titled “Implementation of Research Findings and Products.” 

Note: Following receipt of the draft final deliverables, the remaining 3 months shall be for NCHRP review and comment and for research agency preparation of the final deliverables. 
]]></description>
      <pubDate>Wed, 28 May 2025 13:35:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558388</guid>
    </item>
    <item>
      <title>Utilizing Digital Twining Technologies for Addressing FDOT Priorities</title>
      <link>https://rip.trb.org/View/2550951</link>
      <description><![CDATA[This project has the following objectives: • The primary objective of this project is to establish a comprehensive understanding of digital twin (DT) technology in the context of transportation. This involves providing an overview, conducting a thorough literature review, and exploring practical use cases that create a foundation for further applications. • Proposing a prototype DT framework tailored to the specific needs of the Florida Department of Transportation (FDOT). This involves addressing technical considerations such as data integration, interoperability, and scalability to lay the groundwork for practical implementation. • Developing comprehensive and practical DT frameworks for selective sub-domain in transportation and transportation systems management and operations (TSMO) applications, such as utilizing the SunTrax testing facility as a real-world testing ground. This involves simulating scenarios, integrating diverse data sources, and showcasing the potential of DT technology in enhancing decision-making, infrastructure planning, and testing various intelligent transportation systems (ITS) applications.]]></description>
      <pubDate>Thu, 08 May 2025 12:29:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2550951</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Highway Practices. Topic 56-09. Staffing Models for Transportation Systems Management and Operations (TSMO)



</title>
      <link>https://rip.trb.org/View/2384697</link>
      <description><![CDATA[State DOTs have an increasing need for TSMO staff with a unique combination of information technology (IT) and operation technology (OT) expertise. Staffing for TSMO in this context supports the planning, design, maintenance, and operations for TSMO strategies, such as: network infrastructure and communications, intelligent transportation systems, and traffic management center operations.

The TSMO roles and responsibilities have historically blended IT and OT staff in multiple ways. Increasingly, IT and OT spheres are expanding and converging due to several developments including: (1) Increased utilization of shared communication networks;
(2) Use of more cloud-based software and services; (3) Expanded cybersecurity needs requirements; (4) Requirements for connected and automated vehicles and digital infrastructure; (5) Increased need for remote access and control of TSMO software and field devices; and (6) Greater inter-agency operations-related data sharing and data governance.

State DOTs have addressed the convergence of IT and OT staff support in various ways. For example, some agencies dedicate IT staff for TSMO and may embed them within traffic operations or TSMO units. At the other end of the spectrum, TSMO programs may be required to work through a separate IT agency which may have responsibility over multiple state business areas, with transportation being only one of many.

The objective of this synthesis is to document state DOT staffing models for TSMOs, including organizational structure, classification, funding sources, and skill sets.
Information to be gathered includes (but is not limited to): (1) Required staff knowledge, skills, and abilities; (2) Staffing models, including 24/7 staffing needs; (3) Program funding source for staff; (4) Authority for system operation between IT and OT responsibilities;
(5) Staff to evaluate emerging innovation; (6) Staffing use of consultants/vendors; and
(7) Staffing for TSMO project phases (e.g., technology procurement, implementation, management, maintenance, and sunsetting).

Information will be gathered through a literature review, a survey of state DOTs, and follow-up interviews with selected DOTs for the development of case examples. Information gaps and suggestions for research to address those gaps will be identified.

Information Sources (Partial): (1) FHWA IT-TSMO resources https://ops.fhwa.dot.gov/plan4ops/focus_areas/integrating/it.htm (2) National Operations Center of Excellence Peer Exchange Summary (December 2023); (3) 2024 TRB Annual Meeting IT-OT Workshop co-sponsored by several TRB Committees; (4) Upcoming NOCoE Peer exchange on IT and TSMO; (5) FHWA Traffic Management Pooled Fund Study underway on Staffing for Traffic Management Systems (report not yet available).

TRB Staff (consultant): Sandra Q. Larson, Phone: 515-971-6329, Email: slarson@nas.edu.

Meeting Dates: First Panel Meeting: February 25, 2025; Teleconference with Consultant: June 12, 2025, 3-4 pm eastern; Second Panel Meeting: January 29, 2026; Washington D.C. Keck Center.

Topic Panel: Xiaoyu Skye Guo, District Department of Transportation, Susan Klasen, New Hampshire Department of Transportation, Zhongren Wang, California Department of Transportation, Stephen Wardle, North Carolina Department of Transportation, Justin Aaron Yoh, Ohio Department of Transportation, Scott Zeller, Washington State Department of Transportation, Richard Denney, Federal Highway Administration (FHWA).
 ]]></description>
      <pubDate>Fri, 31 May 2024 20:51:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2384697</guid>
    </item>
    <item>
      <title>Developing a Data Repository to Help with TSMO Strategies Evaluations



</title>
      <link>https://rip.trb.org/View/2381698</link>
      <description><![CDATA[As agencies seek to improve transportation safety and mobility, effectively operating transportation facilities and networks is critically important. There are dozens of Transportation Systems Management and Operations (TSMO) strategies that a facility or network could use. Knowing which TSMO strategies are more likely to be effective at addressing safety and operations issues enables agencies and practitioners to make data-driven decisions to effectively use limited funding. 

The evaluation of TSMO strategies is often complicated by unique characteristics of TSMO strategies, such as deployment of two or more strategies at once, intermittent or flexible use based on prevailing conditions, and widespread effects across a network. Access to better evaluation methods will support agencies in assessing their own use of TSMO strategies. A lack of a central repository that enables sharing of strategy effectiveness data and information impedes the efficiency of agencies and their decision-making for more effective and efficient investments in TSMO strategies. 

Research is needed to help state departments of transportation (DOTs) develop tools to evaluate TSMO strategies, compile results, and make them available to practitioners.

OBJECTIVES: The objectives of this project are (1) to develop evaluation methods to assess the effectiveness of TSMO strategies and (2) to create a web-based central repository to share information, data, and evaluation methods and results for DOTs and other agencies.  ]]></description>
      <pubDate>Mon, 20 May 2024 21:18:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2381698</guid>
    </item>
    <item>
      <title>Advancing TSMO Knowledge Management with Generative AI



</title>
      <link>https://rip.trb.org/View/2381707</link>
      <description><![CDATA[The innovation of generative artificial intelligence (gen AI) tools offers new opportunities in curating, synthesizing, managing, and transferring knowledge. Gen AI tools have potential for leveraging state departments of transportation’s (DOTs) resources to assist with tasks such as producing an initial draft of a literature review, generating executive summaries, and responding to user prompts and questions with detailed insightful feedback from the library of existing resources. Gen AI tools are poised to revolutionize accessing knowledge by reducing the time and effort for retrieving relevant information, using and synthesizing information, enhancing decision-making, facilitating best practice exchange, and providing engaging personalized user experiences. 

As DOTs' interest in adopting gen AI tools for knowledge management grows, research is needed to create suitable knowledge management gen AI tools for transportation agencies.  

OBJECTIVE: The objective of this research is to explore gen AI's potential for enhancing knowledge management at transportation agencies by (1) developing a scalable framework to use gen AI tools for improved knowledge management, (2) designing a trustworthy human-AI collaboration prototype that leverages DOTs' resources to address common transportation systems management and operations (TSMO) scenarios within the established framework, and (3) implementing a pilot deploying the identified prototype to demonstrate its efficiency and effectiveness. ]]></description>
      <pubDate>Mon, 20 May 2024 20:03:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2381707</guid>
    </item>
    <item>
      <title>Innovative Transportation Projects at TxDOT</title>
      <link>https://rip.trb.org/View/2370940</link>
      <description><![CDATA[From time to time, Texas Department of Transportation (TxDOT) districts produce Intelligent Transportation System (ITS) and other technology and process innovations that improve roadway/worker safety, improve roadway efficiency, and/or produce cost savings. This contract leverages the capabilities of Texas Transportation Institute (TTI) to identify, develop, and scale district innovations that are ready to deploy across the state, so that TxDOT can capture the full benefit of 25 different districts with particular insights, creativity and innovative thinking. TTI will investigate innovative district practices and develop plans at a district and statewide level to share and scale innovation across the state. By harvesting the real-world knowledge already contained within TxDOT, new avenues will open to improve roadway safety, efficiency and produce cost savings impacting the millions of travelers across the state. Additionally, by cataloging and bringing together these innovations, divisions and districts can work together to make sure that solutions are developed in such a way that unified systems and interoperability occur throughout the state.]]></description>
      <pubDate>Tue, 23 Apr 2024 16:20:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2370940</guid>
    </item>
    <item>
      <title>Weather Responsive Management Strategies Implementation</title>
      <link>https://rip.trb.org/View/2342164</link>
      <description><![CDATA[Texas Department of Transportation (TxDOT) personnel who work in responding to extreme weather can greatly benefit from the ability to monitor live activities and analyze recent treatment progress. Handwritten brine logs can be supplemented with automated recordkeeping.  Sensing of winter operations (WinterOps) such as plowing, brine spraying, and gravel spreading is accomplished through the use of the GPS fleet tracking system already equipped in all TxDOT vehicles, along with the installation of a few low-cost items. WinterOps activities are then tracked without any special interaction required from the driver or operations personnel. Integration of visualizations with GIS systems provide powerful ways to use the collected data for improving safety, operations, and public communications.]]></description>
      <pubDate>Tue, 20 Feb 2024 15:41:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342164</guid>
    </item>
    <item>
      <title>Data Subsystems and Data Management Plans for Traffic Management Systems</title>
      <link>https://rip.trb.org/View/2286626</link>
      <description><![CDATA[Traffic management systems (TMSs) are deployed in the United States to improve the efficiency, safety, and reliability of travel on designated portions of the surface transportation network. TMSs are typically large, complex systems, that consist of a number of subsystems (e.g., ramp metering, traffic signal control, dynamic message sign, data, traveler information, communication, software, hardware), as well as a range of components (e.g., dynamic message signs, detection devices/sensors, closed-circuit television cameras, signal heads, controllers, communication switches, servers, video wall, phones).

TMSs capabilities could support different services, functions, tasks, or actions. For example, some TMSs manage only the vehicular traffic on freeways in each region, while others may manage the entire road network, which may include surface streets and freeways. TMSs may also have different roles and responsibilities (e.g., sharing roadway and traveler information) that involve sharing, coordinating, or making information available to other agencies, systems, or service providers (e.g., emergency services, transit).

TMSs range in size (i.e., coverage area), functionality (e.g., incident management, ramp management), services (e.g., traveler information, managing traffic across institutional boundaries), and capabilities (e.g., whether or not the system includes a traffic management center, which can be used for sharing information).

Significant changes have occurred with cloud options available to agencies to store data. TMSs have traditionally been designed with local servers and limited ability to modify or make changes. Technical options are available to support agencies making changes in the design, configuration, and technologies used to support a data subsystem (see Special Note A). 

Limited technical information and resources exist to help agencies assess the capabilities and evolving needs for TMSs data subsystems. There are limited resources to support agencies integrating the needs and requirements of data subsystems into the decisions made in planning and programming processes throughout the life cycle of a TMS (e.g., how to plan, design, or procure needed data storage and management capabilities). Agencies face challenges with systematically managing data as part of their TMSs operation. There are limited resources for agencies to use or to assist with data management (e.g., archiving, use, configuration, monitoring use), and issues with receiving, sharing or using data with third-party sources or within an agency (e.g., licenses, proprietary, sensitive information). Research is needed to help agencies better manage data in TMSs.  

The objective of this research is to develop two technical reports to support agencies’ decision-making processes and frame the opportunities for agencies to consider when contemplating improvements to data subsystems and data management plans of their TMSs: (1) Report No.1, Data Subsystems for TMSs, and (2) Report No.2, DMP for TMSs.]]></description>
      <pubDate>Tue, 07 Nov 2023 12:01:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2286626</guid>
    </item>
    <item>
      <title>Understanding Travel Behavior Impacts of Transportation Systems Management and Operations Strategies



</title>
      <link>https://rip.trb.org/View/2286617</link>
      <description><![CDATA[Transportation systems management and operations (TSMO) strategies (e.g., 511, work zone speed management, smart work zones, ramp metering, managed lanes, real-time travel information, etc.) are playing an increasing role in supporting transportation agencies’ strategic goals of improved equity, mobility, reliability, safety, and sustainability. Many evaluations of the effectiveness of TSMO deployments have been performed over the last few decades, but most have focused on the system performance outcomes, namely the impacts on performance metrics such as travel speed, travel time, delay reduction, and crash rates. The impacts of TSMO strategies on traveler behavior, such as mode choice, departure time, and route choice, are not well known. In addition, the impact of traveler behavior (due to TSMO deployments) on the overall transportation network performance is not well established. By better understanding how deployed TSMO strategies affect both the tactical and strategic behavior of travelers, more effective combinations of TSMO approaches can be designed to help agencies meet their goals.

Research is needed to evaluate the impacts of TSMO deployment on traveler behavior and corresponding network performance using data from active TSMO deployments. There are typically five stages in an immediate trip chain where travelers make choices. These include destination choice, time of day choice, mode choice, route choice, and lane/facility choice. When comprehensively applied, TSMO strategies can influence many stages of the trip chain and thus influence both the supply and demand sides of transportation management. Different TSMO strategies can influence different parts of the trip chain, and the focus is more on the influence of TSMO in making short-term, real-time changes to traveler behavior based on prevailing conditions than on long-term, habitual, and static changes to traveler behavior. Understanding how deployed TSMO strategies affect the dynamic decisions travelers make and how network performance changes because of these choices is key. 

The objective of this research is to develop a guide to help public agencies evaluate how various TSMO strategies affect traveler behaviors (pretrip, en route, or holistically) and how these behavior changes affect transportation system performance. ]]></description>
      <pubDate>Mon, 06 Nov 2023 16:29:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2286617</guid>
    </item>
    <item>
      <title>Optimal and Safe Route for Freight Transportation in Rural Areas </title>
      <link>https://rip.trb.org/View/2239027</link>
      <description><![CDATA[The project aims to develop an optimal and safe route for freight transportation in rural areas. Transportation of goods in remote regions often faces challenges such as inadequate road infrastructure, limited access to real-time information, and potential safety hazards. This project seeks to address these issues by utilizing advanced technologies and data-driven approaches. The primary objective is to design an intelligent routing system that takes into account various factors, including road conditions, weather conditions, traffic congestion, and the nature of the cargo being transported. By leveraging historical and real-time data, the system will analyze and identify the most efficient and secure routes for freight transportation.
To achieve this, the project will employ a combination of geographic information systems (GIS), machine learning algorithms, and sensor technologies. The GIS will provide a spatial framework for mapping rural areas and identifying potential routes. Machine learning algorithms will be trained using historical data to predict road conditions and traffic patterns. Sensors placed on vehicles will collect real-time data, enabling the system to dynamically adjust routes based on current conditions.
The outcome of this project will be a robust and reliable routing system that enhances freight transportation efficiency and safety in rural areas. This will benefit businesses by reducing transportation costs, minimizing delivery delays, and ensuring the integrity of the cargo. Additionally, it will have a positive impact on rural communities by improving connectivity and fostering economic development.
]]></description>
      <pubDate>Thu, 07 Sep 2023 09:40:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2239027</guid>
    </item>
    <item>
      <title>Division of Operations Researcher on Call (ROC)  FY2024-2026
</title>
      <link>https://rip.trb.org/View/2227516</link>
      <description><![CDATA[The Ohio Department of Transportation (ODOT) is charged with the management and maintenance of Ohio's vast transportation system.  ODOT strives to execute this charge in the most effective and efficient manner possible.  At times, ODOT encounters situations where low-cost, short-term, focused research tasks are needed to address an urgent issue.  While important and potentially impactful, these research tasks do not warrant the level of a full-scale research project.  Due to the time-sensitive nature of these tasks, it is possible that some of these tasks go unmet because the standard contracting process requires more time than available.  To address this issue, ODOT developed the Research-On-Call (ROC) program.  The ROC is designed to provide direct, quick access to researchers in specific areas of expertise to conduct short-term, focused, urgent research tasks.  This ROC will focus on tasks from the Division of Operations.               ]]></description>
      <pubDate>Thu, 10 Aug 2023 10:56:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2227516</guid>
    </item>
    <item>
      <title>Playbook for Communicating Benefits of Transportation Systems Management and Operations Strategies Using System Performance Data</title>
      <link>https://rip.trb.org/View/2219026</link>
      <description><![CDATA[The widespread adoption of Transportation Systems Management and Operations (TSMO) strategies by agencies marks a notable advancement in transportation operations. Despite the multi-perspective benefits identified from various TSMO strategies, agencies face challenges in effectively communicating these advantages to diverse stakeholders. The surge in data from various sources and emerging technologies further complicates the communication of these benefits. 

Research efforts have improved data handling and developed new performance metrics, such as freeway and arterial reliability measures. However, linking system performance to TSMO strategies and consistently conveying their broader benefits remains a significant challenge. This indicates a gap between understanding the comprehensive impact of TSMO strategies and effectively communicating their benefits.

Research is critically needed to identify system performance measures to quantify TSMO benefits, utilize data to illustrate these benefits clearly, and provide recommendations to bridge any communication gaps to intended audiences. 

The research shall encompass defining what and how to effectively communicate TSMO benefits to whom and when in a timely, relevant, and accessible manner. The research shall also provide methods to assess the efficacy of the communications.

The objective of this research is to develop a playbook with practices for leveraging data and system performance measures to effectively communicate the benefits of TSMO to inter- and intra-agency practitioners/stakeholders, policymakers, and the public.]]></description>
      <pubDate>Tue, 25 Jul 2023 08:56:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2219026</guid>
    </item>
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