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    <title>Research in Progress (RIP)</title>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>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>OpenRoad Link: A Public-Private Data Exchange for Safer, Smarter Trucking </title>
      <link>https://rip.trb.org/View/2646948</link>
      <description><![CDATA[Work zones, lane closures, and traffic incidents significantly impact roadway safety and efficiency. When lanes are blocked due to construction, crashes, or other disruptions, roadways no longer function as designed—leading unexpected congestion, increased crash risk, and reduced operational reliability. Many work zones are established to perform critical maintenance on aging infrastructure—essential to improving durability and extending the service life of roadways—but they also introduce temporary risks and delays that must be better managed.  Effects of lane blockages are particularly severe for commercial motor vehicles (CMVs), which require more time and space to slow or reroute and are subject to strict hours-of-service regulations that make delays especially costly. 

This project proposes to develop and evaluate a data exchange framework—OpenRoad Link—to integrate and share real-time lane closure, work zone, and incident data from the Oklahoma Department of Transportation (ODOT), the Oklahoma City and Tulsa Traffic Operations Centers (TOCs), and other key transportation and traffic enforcement partners. To build this framework, the project will first identify and assess the roadway data already collected and shared by these agencies, as well as the types of information currently accessible to the CMV industry through private telematics platforms. Building on national standards such as the Work Zone Data Exchange and SAE J2735 (the standard message set for vehicle-to-everything communications), the project will extend the data scope to include lane-blocking crashes, maintenance activities, and other short-term or unplanned restrictions not currently emphasized in existing feeds. Through collaboration with ODOT, city TOCs, and trucking industry partners—including a pilot with a major trucking company such as ABF—the project will demonstrate the delivery of curated, high-value information directly to in-cab devices or fleet management systems.  

Key tasks will include identifying and cataloging roadway and incident data currently collected by the Oklahoma Department of Transportation (ODOT) and the Traffic Operations Centers (TOCs) of Oklahoma City and Tulsa, as well as evaluating what information is already being shared with the commercial vehicle industry through private telematics platforms. The project will establish partnerships with ODOT, city transportation and public safety agencies, and private industry stakeholders to design and implement a unified, standards-compliant data exchange framework. Following the design phase, the team will develop and deploy the OpenRoad Link data feed, ensuring compliance with existing national standards and verifying data accuracy and reliability. A pilot deployment will be conducted in collaboration with a trucking company using a selected in-cab device to deliver actionable, real-time information directly to CMV drivers.  

Anticipated outcomes include improved safety for CMV drivers, a reduction in secondary crashes, enhanced freight reliability, and a validated proof-of-concept for scalable public-private data exchange. By producing a replicable model for collaboration between state DOTs and private-sector technology providers, the project aims to accelerate national adoption of interoperable safety data systems and promote safer, more efficient freight transportation. ]]></description>
      <pubDate>Tue, 06 Jan 2026 08:59:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2646948</guid>
    </item>
    <item>
      <title>Connected Corridors Advancement Initiative</title>
      <link>https://rip.trb.org/View/2645418</link>
      <description><![CDATA[The I-80 Corridor Coalition and I-35 Advancement Alliance are spearheading the Connected Corridors Advancement Initiative (CCAI) to address evolving challenges and leverage opportunities in corridor management and transportation technology. As critical transcontinental arteries, these corridors underpin national commerce and mobility, fostering regional connectivity and economic growth.

Building upon AASHTO NCHRP 20-24(138) recommendations and inspired by successful models such as the I-95 Corridor Coalition and the Eastern Transportation Coalition, the initiative seeks to establish a framework for open data standards, infrastructure modernization, and multi-state collaboration. The Nevada DOT SMART Grant Enhancing Corridor Communication Roadmap will serve as a foundation model, showcasing enhanced inter-agency coordination and scalable technology deployment. International efforts, including Europe’s NAPCORE and Canada’s CAV Standards, highlight best practices in data interoperability and advanced infrastructure.

To sustain economic competitiveness, ensure national security, and foster technological leadership, the United States must develop integrated, multi-state corridor frameworks focused on data sharing, operational efficiency, and resilient infrastructure. Enhanced collaboration will bolster domestic mobility, supply chain reliability, and national emergency response capacity. Corridor coalitions have demonstrated the effectiveness of public-private partnerships in addressing infrastructure needs, facilitating transportation planning, and improving operational efficiency across multiple jurisdictions.

OBJECTIVES: The CCAI aims to modernize corridor operations, enhance safety, and optimize economic efficiency by aligning efforts across state, federal, and private sectors. Objectives include developing and implementing open data standards for Work Zone Data Exchange (WZDx), Truck Parking Information Monitoring Systems (TPIMS), and national interoperability of communication data feeds to enable seamless communication across jurisdictions. Additionally, the initiative seeks to prepare the corridor for connected and automated vehicle (CAV) technologies by supporting data interoperability between states, agencies, emergency services, industry partners and the traveling public.]]></description>
      <pubDate>Wed, 24 Dec 2025 15:04:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2645418</guid>
    </item>
    <item>
      <title>Evaluating V2X Network Performance and Enhancing Safety and Security in Sensor Data Sharing for Connected and Automated Driving
</title>
      <link>https://rip.trb.org/View/2625308</link>
      <description><![CDATA[This project will investigate the sensor data sharing mechanism with C-V2X and networked vehicle-to-everything (V2X) communication technology in terms of safety, cybersecurity, and network performance with current bandwidth allocations. The research team will (1) develop a comprehensive evaluation framework of the V2X network performance (e.g., latency, throughput) under real – world complexities; (2) develop a data fusion model that fuses Sensor Data Sharing Messages (SDSMs) from multiple sources considering uncertainties in real-world V2X communication networks, errors in sensor-based object detection; and (3) develop a misbehavior detection model that can detect anomaly in SDSMs and evaluate the trustworthiness of the message within a short time.]]></description>
      <pubDate>Thu, 13 Nov 2025 15:28:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625308</guid>
    </item>
    <item>
      <title>Accelerating Deployment of MAP and SPaT Information Distribution Using Executable Designs
</title>
      <link>https://rip.trb.org/View/2625305</link>
      <description><![CDATA[The research team proposes MAP SPaT Digest and Digest Data Delivery functional objects using CubeDesigner to produce executable code that can be delivered to deployers who will run the code in edge physical objects. The evaluation criteria will be the successful operation of the functional objects in various host objects such as standalone Linux devices and cellular provider edge computing services. Also, the project will implement the Signal Control Status information flow using CubeProtocol so that the information integrity and communication efficiency claims of the protocol can be evaluated.]]></description>
      <pubDate>Thu, 13 Nov 2025 14:53:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625305</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S01-34. Leveraging Technology to Streamline Capital Improvement Program Management



</title>
      <link>https://rip.trb.org/View/2621997</link>
      <description><![CDATA[Inconsistent technology used across airports, state aviation departments, and federal agencies can create inefficiencies in Capital Improvement Program (CIP) management. Industry stakeholders are evolving their use of technological systems for CIP portfolio management and data sharing, which allow for collaboration and streamlined processes. It also allows them to track recurring projects and share information across departments.

OBJECTIVE: The objective of this synthesis is to document practices leveraging technology in ways to streamline Capital Improvement Program management through internal and external information sharing. For this synthesis, Capital Improvement Program (CIP) management encompasses the portfolio management life cycle from the idea of a project through planning, development, etc., to closeout, for all airport projects regardless of funding source. The audience for this synthesis is aviation planners, airport executives, and commissions/boards.  ]]></description>
      <pubDate>Mon, 10 Nov 2025 19:28:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2621997</guid>
    </item>
    <item>
      <title>KYTC Geotechnical Data 
Transition Support and 
Application Development</title>
      <link>https://rip.trb.org/View/2593940</link>
      <description><![CDATA[With the planned discontinuation of gINT, the Kentucky Transportation Cabinet (KYTC) must transition to a new geotechnical data management system. This project will facilitate that transition by ensuring geotechnical data can be accurately transferred, validated, and integrated across existing and proposed systems. Researchers will investigate current geotechnical data transfer protocols and data validation tools before developing Cabinet-specific tools that can maintain data quality and enable efficient data sharing within the agency and with external partners.]]></description>
      <pubDate>Thu, 28 Aug 2025 11:32:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/2593940</guid>
    </item>
    <item>
      <title>Examination of Light-Based Directed Vehicle to Everything Communications Systems for Bridge Strike Detection</title>
      <link>https://rip.trb.org/View/2562268</link>
      <description><![CDATA[With the emergence of advanced driver assistance systems (ADAS) in most modern passenger vehicles, the need for reliable
transmission of data from vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) has become apparent. However, many
commercial vehicles such as buses and semi-trucks are technologically behind when it comes to sensing potential safety hazards,
while having the potential to cause catastrophic damage due to their increased size and weight. One of the most common safety
incidents involving large commercial vehicles are bridge strikes and tunnel strikes, where the driver of a tall-load vehicle attempts to
pass under a bridge or tunnel and the top of the load collides with the bottom of the overpass. According to the National Highway
Safety Administration, there are approximately 15,000 bridge strikes in the USA annually, with potentially more going unreported.
These bridge strikes cause a serious threat to the safety of all road users, as well as a substantial financial cost in the form of
infrastructure repair, road closures, and traffic disruption.]]></description>
      <pubDate>Fri, 06 Jun 2025 14:57:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2562268</guid>
    </item>
    <item>
      <title>Guide to Link and Manage Information About Property Interests with Existing Utility Infrastructure Data</title>
      <link>https://rip.trb.org/View/2558401</link>
      <description><![CDATA[Utility facilities and the property interests that govern their placement are often not fully aligned or documented. Many utilities have been installed outside of designated easements, and municipal utilities frequently lack clearly defined boundaries. During relocations, older facilities are sometimes abandoned in place without proper records. As a result, state department of transportation (DOT) rights-of-way (ROW) contain numerous utilities with uncertain legal status.

Across the country, documentation of older easements is often vague, incomplete, or unrecorded, and state DOTs may struggle to obtain missing information without cooperation from utility providers. Data-sharing challenges—driven by proprietary concerns, security restrictions, workforce limitations, and changes in ownership—further complicate efforts to verify utility locations and associated property rights.

Research is needed to create a secure, collaborative system for state DOTs and utility providers to link, store, and manage utility infrastructure and property interest data.

OBJECTIVE: The objective of this research is to develop a compendium to help state DOTs collaborate with utility providers to integrate property interest information with existing utility infrastructure data. At a minimum, the compendium shall include a data governance framework, a technical architecture for linking existing utility facility data to its associated property interest, a spatial data framework holding the linked information, and implementation guidance.]]></description>
      <pubDate>Wed, 28 May 2025 09:56:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558401</guid>
    </item>
    <item>
      <title>Managing and Sharing Traffic Management Systems Video

</title>
      <link>https://rip.trb.org/View/2558409</link>
      <description><![CDATA[Traffic management systems (TMSs), which integrate advanced technologies, software, and data, are essential tools for enhancing the safety, efficiency, and reliability of surface transportation. These systems play a vital role in helping agencies meet the growing and evolving mobility needs of travelers, service providers, partner agencies, and the general public.

Traditionally, TMSs provided only static images of roadway conditions, but technological advancements have transformed this practice into 24/7 live-streaming video feeds of traffic conditions. Increasingly, individuals and private companies are capturing, scraping, or archiving these video feeds, and often repackaging and selling the data to public or private customers, raising legal, technical, and operational challenges for transportation agencies.

Most TMSs do not record or archive video feeds due to concerns over legal obligations and public information requests, risks of releasing sensitive or personally identifiable information (PII), potential liability from unintended uses, and technical burdens of video management. The rising expenses of data storage and telecommunications add complexity to video management.

Research is needed to help agencies evaluate the implications, benefits, and risks of sharing TMS video.

OBJECTIVE: The objective of this research is to develop a guide for transportation agencies on managing and sharing access to TMS video. The research will identify current practices, challenges, unintended consequences, and opportunities for improvement.]]></description>
      <pubDate>Tue, 27 May 2025 20:58:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558409</guid>
    </item>
    <item>
      <title>Aeromedical Information Sharing and Data Analysis Public Private Partnership – Phase 2</title>
      <link>https://rip.trb.org/View/2518972</link>
      <description><![CDATA[The Federal Aviation Administration's (FAA’s) Office of Aerospace Medicine aims to collaborate with Part 121 operators by FY26 to modernize pilot medical certification policies through a Safety Management System framework. Currently, the FAA lacks evidence linking pilot medical hazards to proactive safety outcomes (degraded performance), relying instead on historical events like accidents or incapacitations. To address this, the Office sponsored a phase 1 feasibility study for a Public-Private Partnership (PPP) between FAA and industry to advance aeromedical safety. That study confirmed the viability and industry support for a focused PPP, the Aeromedical Certification Collaborative (ACC), and proposed a collaboration framework and an initial study. Phase 2 will operationalize this framework by conducting one or two ACC-defined studies and formalizing how the collaborative works together as needed to sustain this unique and impactful research partnership. ]]></description>
      <pubDate>Tue, 04 Mar 2025 14:56:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2518972</guid>
    </item>
    <item>
      <title>Prototyping a Low-cost Roadside Device System for Cooperative Automated Driving</title>
      <link>https://rip.trb.org/View/2425404</link>
      <description><![CDATA[Although significant progress has been made in automated driving technologies, technical challenges still exist, especially for complex Operational Design Domains (ODDs). A low-cost roadside device system, the Connected Reference Marker (CRM) System, has been developed to support CAVs in those ODDs. The CRM system can facilitate CAV localization by providing real-time distance measurement and road geometry changes (i.e., work zones). Therefore, the CRM system has the potential to serve as a gateway system for infrastructure-based cooperative driving automation (CDA) due to its low cost and easy deployment. This project will evaluate the performance regarding localization and road geometry data provision in field experiments. Specifically, this project will build a prototype system and evaluate the localization accuracy in various scenarios; in addition, the prototype system will be used to detect the boundaries of work zones, as improving access to work zone data is one of the top needs identified through the USDOT Data for Automated Vehicle Integration (DAVI) effort. The detected boundaries of work zones will be later translated into a data feed following the Work Zone Data Exchange (WZDx) specification, a national work zone data standard pioneered by USDOT to meet the DAVI requirement and a critical part of the Roadway Digital Infrastructure (RDI) strategy.]]></description>
      <pubDate>Thu, 05 Sep 2024 16:58:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2425404</guid>
    </item>
    <item>
      <title>Establishment of a Public-Private Transportation Data Exchange Center</title>
      <link>https://rip.trb.org/View/2414020</link>
      <description><![CDATA[State departments of transportation (DOTs) across the country are paying third-party vendors to provide traffic data from their own roadways. The data is costly, and the source of the data is not verifiable.  An entire industry is emerging that increasingly perceives DOTs as their primary financial source.  Currently a significant number of vehicles are equipped with sensors, cameras, and in some cases lidar technology, which have the capability to provide DOTs accurate information pertaining to vehicular movements on United States roadways. This information is currently retained by the Original Equipment Manufacturers (OEMs). If this information was shared with the departments of transportation, it could lead to a safer and more efficient system for their users.  Cooperative efforts by a consortium of State entities to facilitate this data exchange could yield substantial benefits for the DOT, the OEMs, but most importantly the people driving on the roadways. Historically, there has been a reluctance within the private sector to share information with government agencies.  The premise of this TPF study is to collaboratively look at the development of a data repository that could act as an impartial arbiter of data to ensure all personal identifying details are excluded. 

The goal of the project is to develop a secure computing, data analytics, and storage infrastructure with a data repository (data warehouse or data lake) that will collect all relevant vehicle data as well as other types of data (including environment data, weather data, among other sources) and share the data with DOTs for data analyses without any identifying information attached to improve transportation decision-making.]]></description>
      <pubDate>Wed, 07 Aug 2024 15:56:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2414020</guid>
    </item>
    <item>
      <title>Guide for Digital Project Delivery: Integrating Design and Construction</title>
      <link>https://rip.trb.org/View/2381719</link>
      <description><![CDATA[In recent years, there has been an explosion of digital tools and practices to enhance how transportation agencies conduct business and deliver projects more collaboratively with partners. State departments of transportation (DOTs) are replacing paper and image-based workflows with more intelligent digital processes to tap the potential of digital information more fully for collaboration, productivity, and risk and quality management. Digital practices such as three-dimensional (3D)/four-dimensional (4D) modeling, e-Construction/e-Ticketing, and building information modeling (BIM) for infrastructure are improving project delivery by enabling more effective collaboration and seamless data exchange, reducing errors during handoffs. However, integration of these digital practices remains largely ad hoc, particularly in areas like risk evaluation and management for project delivery. Research is needed on the utilization of digital project delivery practices within the transportation sector, the benefits achieved, and how these practices can be adapted to meet state DOT needs.

The objective of this research is to develop a guide for implementing digital delivery practices from design through construction of the transportation infrastructure life cycle.]]></description>
      <pubDate>Tue, 21 May 2024 17:06:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2381719</guid>
    </item>
    <item>
      <title>Road Weather Management Using Connected Vehicle Technology</title>
      <link>https://rip.trb.org/View/2342040</link>
      <description><![CDATA[Road weather systems are used by state and local agencies to mitigate and manage the disruptive impact of weather events on roadways. Some of the fundamental aspects of road weather systems are the collection of weather-related data from environmental sensor stations and probe vehicles, the processing/distribution of data, and the determination of how/when/where to deploy road maintenance resources and/or to issue general traveler advisories and/or issue location specific warnings to drivers.

As momentum behind connected vehicle technology continues to build, practitioners are showing interest in determining how connected vehicle technology can be leveraged to support traffic management activities, including road weather systems. Specifically, the ability to communicate with connected vehicles opens up new opportunities for collecting data from many vehicles, and targeted dissemination of information to drivers. Thus, it will be important to ascertain the types of data that can be communicated in connected vehicle messages, as well as other intrinsic aspects of connected vehicle communications to understand how connected vehicles can enhance existing and open up opportunities for new road weather strategies.

Research will be undertaken as part of this project to review connected vehicle data standards, and to engage Aurora members to determine which road weather strategies are of greatest interest to practitioners. The project team will apply knowledge gained from members, as well as their background in engineering systems, to develop a Concept of Operations, which will provide a description of how connected vehicle communications and data may be employed to enhance the capabilities of road weather systems.]]></description>
      <pubDate>Mon, 19 Feb 2024 18:12:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342040</guid>
    </item>
    <item>
      <title>Enhancing Traffic Flow through Private Data Sharing and Incentivizing New Mobility Services</title>
      <link>https://rip.trb.org/View/2338819</link>
      <description><![CDATA[As urban areas experience rapid population growth and development, the pervasive issue of traffic congestion has become increasingly challenging, particularly in large cities. Various strategies aimed at mitigating congestion have been proposed, spanning from the expansion of roadways and the optimization of transportation systems to the implementation of demand management. Congestion pricing and incentive schemes, integral to demand management, have emerged as tools to reinforce traffic control measures. While extensive research has focused on congestion pricing in conventional mobility systems, there's a notable gap in understanding its implications for future mobility services. In the traditional paradigm, the driver, who is also the car owner, holds absolute decision-making authority over aspects such as origin, destination, route, and travel time. In contrast, future mobility systems involve a diverse array of organizations and companies that exert varying degrees of influence over the behavior of individual drivers, whether human or AI-based. These entities encompass car-sharing services (e.g., Zipcar), ride-hailing services (e.g., Waymo, Uber, Lyft), crowdsourced delivery systems (e.g., Amazon Flex, Instacart, DoorDash), navigation applications (e.g., Google Maps and Waze), and even companies producing autonomous vehicles with integrated navigation systems (e.g., Tesla), among others.

In future mobility systems, (real-time) incentivization of organizations can be more effective than targeting individual drivers. In addition, having insights into organizations' anticipated road network demand becomes instrumental for the central planner to implement impactful incentives, steering the entire network towards the "system optimal" point. Consider, for instance, the knowledge of impending delivery deadlines for Amazon packages or the anticipated demand for road segments by Waymo/Uber drivers in the next few minutes—such information empowers the central planner to offer targeted and effective incentives. However, the challenge lies in acquiring this knowledge, as organizations are often reluctant to share their data due to data protection regulations or concerns about divulging information to competitors.

The objective of this project is to develop "private collaborative" mechanisms facilitating data sharing among organizations and a central planner. Subsequently, the central planner utilizes this shared data to offer incentives, encouraging organizations to influence the behavior of individual drivers within their ranks or those utilizing their services. Drawing from the principles of "differential privacy" in machine learning, the research team aims to ensure a rigorous guarantee of privacy protection for the organizations' data. The proposed framework integrates real-time traffic data, alongside the anticipated future demands of organizations and their tasks, to continually forecast network traffic flow and incentivize organizations to alleviate congestion. The methodology's performance will be assessed through an evaluation utilizing data from the highly congested urban landscapes of Los Angeles and New York. These locations are chosen as ideal validation areas due to being among the most traffic-congested cities in the United States. Specifically, the assessment will rely on the Archived Data Management System (ADMS) in Los Angeles, The New York City Taxi and Limousine Commission (TLC) data in New York, and The City of New York Department of Transportation's real-time traffic data.]]></description>
      <pubDate>Tue, 13 Feb 2024 21:49:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/2338819</guid>
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