<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnM+PGZpbHRlciBmaWVsZD0iaW5kZXh0ZXJtcyIgdmFsdWU9IiZxdW90O1Rlc3QgYmVkcyZxdW90OyIgb3JpZ2luYWxfdmFsdWU9IiZxdW90O1Rlc3QgYmVkcyZxdW90OyIgLz48L2ZpbHRlcnM+PHJhbmdlcyAvPjxzb3J0cz48c29ydCBmaWVsZD0icHVibGlzaGVkIiBvcmRlcj0iZGVzYyIgLz48L3NvcnRzPjxwZXJzaXN0cz48cGVyc2lzdCBuYW1lPSJyYW5nZXR5cGUiIHZhbHVlPSJwdWJsaXNoZWRkYXRlIiAvPjwvcGVyc2lzdHM+PC9zZWFyY2g+" rel="self" type="application/rss+xml" />
    <description></description>
    <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>
    </image>
    <item>
      <title>TraCR Foundational Project: TraCR Collective Transportation Cybersecurity Testbeds</title>
      <link>https://rip.trb.org/View/2697454</link>
      <description><![CDATA[The National Center for Transportation Cybersecurity and Resiliency's (TraCR's)
foundational project aims to develop technological tools, prototypes, testing platforms, and facilities to ensure the cybersecurity and cyber-resilience of multimodal transportation systems and related infrastructure. The project is led by Clemson University (Clemson) under the strategic direction of Dr. Ronnie Chowdhury (Lead PI), with coordination support from Dr. Sabbir Salek (Co-PI), and involves all eight other TraCR partner institutions organized into four subgroups. A structured project governance framework, including biweekly subgroup meetings, monthly full-team coordination meetings, quarterly progress reporting and advisory board engagement, ensures alignment with project milestones, integration across teams, and effective monitoring of technical progress and deliverables. 

Clemson collaborates with Benedict College (Benedict), South Carolina State University (SCSU), and the University of Texas at Dallas (UTD) to advance a comprehensive, automated threat modeling capability for multimodal transportation systems. Building on the Transportation Cybersecurity and Resiliency Threat Modeling Framework (TraCR-TMF), the team conducts testbed-in-the-loop evaluations within Clemson’s real-world cybersecurity testbed, implementing digital-twin-based cybersecurity analysis of in-vehicle networks, and engaging state transportation agencies to assess operational transferability. Additionally, the team will work to integrate graph-based reasoning models into threat modeling, deploy supervised ModernBERT classifiers, and align with the MITRE Embedded Systems Threat Matrix to strengthen structured system-to-vulnerability mapping and improve threat coverage across transportation cyber-physical systems.

The other partner institutions will develop additional real-world and virtual testing platforms to support cybersecurity experimentation for multimodal transportation. Florida International University (FIU) and the University of Alabama at Tuscaloosa (UA) are jointly advancing the Open-Source Connected and Automated Mobility Co-Simulation (OpenCAMS) environment and related simulation platforms, integrating SUMO, CARLA, and network simulation tools, to evaluate privacy-aware multimodal large language models and post-quantum-secure C-V2X communications. Their efforts further include the development and validation of spoofing attack models targeting Basic Safety Message transmissions and multi-frequency GPS receivers, as well as investigations into backdoor-resilient perception systems and the security of vision-language models for intelligent transportation applications.

Purdue University (Purdue) and the University of California, Santa Cruz (UCSC) are advancing adversarial testing methodologies through integrated physical-virtual experimentation frameworks that combine miniature autonomous vehicle testbeds, CARLA/METS-R simulation coupling, and scenario-based vulnerability discovery. These activities include simulation-to-real validation of perception and traffic signal spoofing attacks, evaluation of V2X safety message vulnerabilities, cybersecurity analysis of shared micromobility Bluetooth pairing protocols, implementation of lightweight post-quantum cryptographic protections for vulnerable road user beacons, and closed-loop security assessments of traffic signal controller infrastructures, along with investigations of secure multimodal AI agents and memory-augmented reasoning architectures for autonomous robotic transportation systems.

In addition, Morgan State University (MSU) is enhancing its connected vehicle cybersecurity experimentation capabilities by developing replay-attack models targeting C-V2X onboard units and evaluating mitigation strategies in its real-world testbed environment, in collaboration with Clemson. These efforts quantify communication-level impacts on safety-critical applications and support the development of deployable countermeasures to strengthen resilience against wireless attack vectors affecting connected transportation infrastructure.
]]></description>
      <pubDate>Thu, 30 Apr 2026 12:19:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697454</guid>
    </item>
    <item>
      <title>SentinelLab: A Plug-in Online Defender Testbed for Connected and Autonomous Vehicle (CAV) </title>
      <link>https://rip.trb.org/View/2696945</link>
      <description><![CDATA[This project develops SentinelLab, a closed-loop defender testbed designed to transform how Connected and Automated Vehicle (CAV) cybersecurity is validated. Currently, most research stops at detecting anomalies; this project bridges the gap to active defense by integrating the METS-R traffic simulator with the CARLA photo-realistic sensor simulator. The testbed utilizes a “Recognize, Decide, Act” framework. The project employs a multimodal Large Language Model (LLM) to recognize specific attack families (e.g., message replay, breaking provocation) from noisy streaming signals. It then uses an online Defender Workbench to decide on mitigation strategies via plug-in policies and automatically executes these actions in the simulation. This system enables researchers and public agencies to prepare defenses against realistic threats and quantify their impacts on safety and mobility.]]></description>
      <pubDate>Wed, 29 Apr 2026 11:32:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2696945</guid>
    </item>
    <item>
      <title>SMARTER Center CAV Testbed Digital Twin</title>
      <link>https://rip.trb.org/View/2676080</link>
      <description><![CDATA[This project advances transportation safety and mobility by developing a high-fidelity digital twin of the SMARTER Center’s Connected and Automated Vehicle (CAV) testbed at Morgan State University. The proposed platform synchronizes key infrastructure states, sensor observations, and traffic dynamics with a virtual environment in near real time, enabling safety and mobility interventions to be evaluated in a controlled, repeatable setting without exposing road users to risk. Currently, CAV safety validation faces a well-documented gap: physical testing is costly, slow, and may introduce safety concerns, while purely virtual simulations often lack real-world calibration. This project addresses that gap by integrating live testbed data—including LiDAR, CCTV cameras, roadside units, and V2X messages—with simulation-based scenario testing using CARLA, sensor fusion methods, and validated data pipelines. The system targets low latency and high spatial accuracy suitable for behavioral and safety analysis under representative traffic conditions. The platform demonstrates multi-modal capability through two application scenarios: (1) pedestrian crossing conflict analysis at signalized intersections under varying speeds, visibility, and occlusion conditions, and (2) transit signal priority evaluation using U.S. DOT bus trajectory data to assess potential operational impacts, including delay reduction. Validation is conducted using RTK-GPS probe vehicles and annotated video data, with trajectory similarity and time-to-collision metrics quantitatively assessed. Key outcomes include a functional digital twin system, evaluation of safety-critical scenarios with agreement between digital and physical testbed behavior on key performance indicators, a 5-hour annotated dataset with DCAT-US metadata, and three software modules released via GitHub. The extensible platform architecture supports future applications such as emergency vehicle preemption, freight operations, and micromobility, with documented APIs enabling replication across diverse testbeds and agencies.]]></description>
      <pubDate>Wed, 11 Mar 2026 15:33:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2676080</guid>
    </item>
    <item>
      <title>SPR-4856:  Receiver, Vehicle, and Roadway Systems for a Dynamic Wireless Power Transfer Roadway Testbed</title>
      <link>https://rip.trb.org/View/2253923</link>
      <description><![CDATA[This project will support the installation of a one-quarter mile long dynamic wireless power transfer (DWPT) testbed on northbound US-231 in West Lafayette. At the end of this project, INDOT will have a fully functional pilot DWPT constructed and key testing of the performance of the system will be performed.]]></description>
      <pubDate>Fri, 22 Sep 2023 14:51:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2253923</guid>
    </item>
    <item>
      <title>One-to-Many Simulator Interface with Virtual Test Bed for Equitable Tech Transfer</title>
      <link>https://rip.trb.org/View/1942832</link>
      <description><![CDATA[After five years of R&D, researchers have developed a number of independent simulation tools to evaluate different algorithms. A broad API will be developed to handle interfacing any simulation with a multi-agent demand simulator. This will be tested on the existing MATSim-NYC (which will be enhanced to include freight and parcel delivery activities) and a BEAM implementation, BEAM-NYC, for three use cases in electric transit, freight, and traffic, considering equity impacts on different population segments (by income level, ability, and age). The team will jointly conduct case studies in NYC and Seattle, enabling deeper insights of evaluated cases and promote tech transfer and collaboration to broader communities (including agencies, the industry, and the public).]]></description>
      <pubDate>Fri, 22 Apr 2022 11:11:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/1942832</guid>
    </item>
    <item>
      <title>Evaluation of Integrated Overweight Enforcement System using High Accuracy WIM System and Non-Proprietary ALPR System</title>
      <link>https://rip.trb.org/View/1942837</link>
      <description><![CDATA[The main objective is to establish the second testbed for overweight enforcement along the BQE corridor in New York City. The team will develop the drawing for the site-specific sensor layout, install the Quartz sensors and automated-license-plate-recognition (ALPR) cameras to measure truck weight data and identify license plate and/or USDOT number, and evaluate the performance of the overweight enforcement system. The team will also estimate the impact of an extreme event using data collected for infrastructure resilience.]]></description>
      <pubDate>Fri, 22 Apr 2022 10:42:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/1942837</guid>
    </item>
    <item>
      <title>SPR-4442: Highway Lighting Test Bed on INDOT Facility (Off-Roadway)</title>
      <link>https://rip.trb.org/View/1632669</link>
      <description><![CDATA[To eliminate traffic control and potential safety concerns with conducting field Luminaire testing, it is essential to establish necessary test beds so that new models can be evaluated in a controlled and standard setting. By the end of this study, two test beds will be designed, constructed, and implemented. The test beds will improve INDOTs testing procedure and support the on-going development of INDOTs Approved Materials List for Solid State Ballasted Luminaires.]]></description>
      <pubDate>Tue, 25 Jun 2019 11:14:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/1632669</guid>
    </item>
    <item>
      <title>STOL Transportation Operations Data Resources Testbed</title>
      <link>https://rip.trb.org/View/1509903</link>
      <description><![CDATA[No abstract provided. ]]></description>
      <pubDate>Thu, 26 Apr 2018 14:52:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/1509903</guid>
    </item>
    <item>
      <title>Maintenance, Operations and Enhancement of DSRC Communications Infrastructure</title>
      <link>https://rip.trb.org/View/1441799</link>
      <description><![CDATA[The United States Department of Transportation (U.S. DOT) provided financial and technical support to California Department of Transportation (Caltrans) and PATH for updating the Dedicated Short Range Communication (DSRC) communication infrastructure of its test-bed site along El Camino Real in Palo Alto. That infrastructure needs to be maintained and supported so that it will be useful for other Caltrans and PATH projects, as well as for projects to be conducted by a variety of other public and private sector organizations in the region.  Caltrans and the University of California PATH Program have been collaborating on the development, testing and evaluation of DSRC for a decade, beginning with the VII California project. DSRC at 5.9 GHz provides a unique capability to deliver time-critical, safety-critical messages between the roadside infrastructure and vehicles with high reliability and low latency.  Work under this project will maintain the test-bed, provide support to the new users, provide liaison to National network of test-beds, upgrade and enhance test-bed capabilities and perform a radio coverage study of the 11 intersections.  This radio coverage study will investigate areas where the radio coverage is insufficient and areas where there is an overlap of the two adjacent radios.  This study will present solutions to the problems of insufficient radio coverage and overlap areas.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:52:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441799</guid>
    </item>
    <item>
      <title>Vehicle Trajectory Tool: Application Pilot for AMS Test bed</title>
      <link>https://rip.trb.org/View/1404175</link>
      <description><![CDATA[This research tests an in-vehicle device (i2d) developed by ITDS that senses and disseminates micro-scale vehicle activity to a server in the cloud. Data will be collected at 1 hertz resolution, and experiments will investigate the feasibility of using the i2d data for both system monitoring and VIV applications, using several connected vehicles]]></description>
      <pubDate>Wed, 20 Apr 2016 01:00:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1404175</guid>
    </item>
    <item>
      <title>Cooperating Camera Platforms for Ultra High-Resolution Tracking of Traffic
</title>
      <link>https://rip.trb.org/View/1369995</link>
      <description><![CDATA[This project is designed to provide high-definition cooperative camera traffic surveillance. This system will have enhanced capabilities to recognize "events" in the highway infrastructure and relay this information to command centers in real time. In addition, the technology will enable any feature extraction algorithm to interoperate with ultra high-resolution surveillance hardware. This research will explore the use of cooperating camera platforms, high accuracy gimbals, high-definition vision cameras, and servo-stabilized platforms. These technologies provide unique cross-cutting opportunities. This cross-cutting system might enable significant improvements in the power of computer vision algorithms and will allow a test bed for developers of the algorithms because the system design for utilization of the cameras provides an agnostic interface with analysis algorithms. This project will expand understanding of the advantages and disadvantages of ultra high-resolution traffic surveillance and real-time analysis and dissemination of detected "events" or anomalies.

]]></description>
      <pubDate>Tue, 22 Sep 2015 15:39:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1369995</guid>
    </item>
  </channel>
</rss>