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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>Smart Drop-Shipping and Stocking Decision Support System</title>
      <link>https://rip.trb.org/View/2703794</link>
      <description><![CDATA[Drop-shipping is an increasingly important order fulfillment strategy in modern supply chains, allowing firms to reduce inventory holding costs by shipping products directly from suppliers to customers. However, because inventory is not directly controlled by the firm, drop-shipping can introduce uncertainty in product availability, delivery lead times, and service reliability. To compensate, firms often rely on expedited transportation, which increases costs and may negatively affect safety and efficiency in freight operations. These trade-offs create a challenging decision problem: determining which products should be stocked internally, fulfilled through drop-shipping, or managed under a mixed fulfillment strategy.
Industry interviews with a major U.S. wholesaler indicate that firms tend to rely on drop-shipping for slow-moving products due to limited warehouse space and capital constraints, yet lack systematic, data-driven methods to guide these decisions Existing research largely focuses on single-product settings or coordination issues between retailers and suppliers and does not address multi-product decisions under warehouse capacity constraints.
This project aims to fill this gap by developing an optimization-based decision support framework for drop-shipping and inventory planning across multiple stock-keeping units (SKUs). The proposed approach integrates mixed-integer programming with meta-heuristic methods to support large-scale, real-world applications. The model incorporates demand patterns, inventory holding costs, transportation costs, service level requirements, and cash flow constraints. A complementary simulation framework will be developed to evaluate system performance under uncertainty in demand, supplier inventory availability, and delivery times.
The project supports Mid-America Transportation Center (MATC) themes of Safety and Transportation Systems of the Future by enabling more predictable and efficient freight movements, reducing reliance on expedited shipping, and promoting data-driven planning in distributed fulfillment networks. Expected outcomes include an implementable decision support tool, analytical insights for industry stakeholders, and dissemination through publications and conference presentations.]]></description>
      <pubDate>Sat, 16 May 2026 11:49:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703794</guid>
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    <item>
      <title>Guiding Electronic Control Unit (ECU) Firmware Fuzzing with Hardware-Level Side-Channel </title>
      <link>https://rip.trb.org/View/2697290</link>
      <description><![CDATA[This project develops a novel electromagnetic (EM) side-channel-guided fuzzing framework for automotive Electronic Control Unit (ECU) firmware security testing. The approach addresses key challenges in ECU security research, namely that firmware is often encrypted, proprietary, and tightly coupled to hardware, making traditional instrumentation-based fuzzing impractical. By capturing and analyzing EM emanations from ECUs during execution, the framework estimates code coverage without requiring firmware modification, instrumentation, or rehosting. The system integrates this EM-based coverage feedback into a fuzzer to guide test case generation via Controller Area Network (CAN) bus communication. The project will conduct extensive fuzzing campaigns on real automotive ECUs from various manufacturers to discover zero-day vulnerabilities and enhance vehicle cybersecurity. ]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2697290</guid>
    </item>
    <item>
      <title>Safe and Personalized Control of Autonomous Vehicles with On-Board Vision Language
Models: System Design and Real-World Validation
</title>
      <link>https://rip.trb.org/View/2625313</link>
      <description><![CDATA[This project focuses on enhancing autonomous vehicle control systems by integrating on-board Vision-Language Models (VLMs) for safe and personalized driving experiences. Building on the previously awarded Center for Connected and Automated Transportation
(CCAT) project on “CAV Pilot Development and Deployment in Midwest Winter,” this research addresses critical challenges in autonomous vehicle development regarding limited on-board computational resources by implementing lightweight VLM frameworks and Retrieval-Augmented Generation (RAG)-based memory modules. The project will validate the system’s ability to handle challenging urban scenarios, reduce human takeover rates, and adapt to diverse environmental conditions.
]]></description>
      <pubDate>Thu, 13 Nov 2025 15:43:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625313</guid>
    </item>
    <item>
      <title>Design of Dynamic Train Crossing Estimation and Real-Time Traffic Control Systems for 
Grade Crossing Safety
</title>
      <link>https://rip.trb.org/View/2573792</link>
      <description><![CDATA[This research project aims to enhance safety and traffic flow efficiency at rail grade  crossings by developing a real-time traffic operation control system that dynamically coordinates traffic signals with train movements. A key innovation is the design of dynamically updated train crossing windows for all at-grade crossings within a region. By leveraging available real-time train tracking data, including location, speed, and projected arrival times at crossings, the system will continuously predict and update crossing windows. These predictions will be integrated into adaptive traffic signal control algorithms, ensuring efficient vehicle movement while reducing delays and potential conflicts at crossings. The proposed system will consist of three core components: (1) a real-time train movement prediction model using the Global Positioning System (GPS), trackside sensors, and historical train operation data; (2) a dynamic train crossing window estimation module that calculates and updates available crossing opportunities for all grade crossings in the region based on evolving train movement data; and (3) an intelligent traffic signal coordination system that adjusts traffic lights in real time to optimize vehicle throughput while ensuring safety at rail crossings. This approach will minimize unnecessary traffic stops, reduce congestion, and improve safety by providing a network-wide, adaptive traffic management solution. The findings of this research will contribute to the advancement of intelligent transportation systems, offering practical applications for traffic agencies and rail operators in improving grade crossing safety and efficiency.]]></description>
      <pubDate>Mon, 14 Jul 2025 19:15:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2573792</guid>
    </item>
    <item>
      <title>Guide for the Development of an Airport Asset Registry</title>
      <link>https://rip.trb.org/View/2413900</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Mon, 05 Aug 2024 19:24:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2413900</guid>
    </item>
    <item>
      <title>A New Optimization Approach to Distributed Manufacturing System Design</title>
      <link>https://rip.trb.org/View/2342037</link>
      <description><![CDATA[Distributed manufacturing is gaining traction in various industries with fast growth of sensor, Internet of Things (IoT) and advanced manufacturing technologies. It is a promising new business paradigm to achieve mass customization and facilitate the shared and circular economy. The goal of this proposed project is to develop a new optimization approach for the strategic design of distributed manufacturing system (DMS) in terms of facility locations and dynamic sharing of manufacturing resources to meet time-varying demand, while considering autonomous/distributed planning decisions of supply-production networks (SPNs) in the DMS. The main challenge and technical advancement of the project is the design and implementation of a decision-game-theoretic model to capture the autonomous decision-making feature of each local SPN and to satisfy time-varying customer demand in a dynamic way. Advanced computational algorithms will also be developed to obtain quality solutions efficiently. This project aligns with DOT’s strategic goals of economic strength and global competitiveness, safety and equity, and supports MATS-TSE’s themes on resilient supply chains and transportation systems of the future.]]></description>
      <pubDate>Mon, 19 Feb 2024 18:24:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342037</guid>
    </item>
    <item>
      <title>Building a Secure Electronic Control Unit Hardware Platform for Connected Vehicles</title>
      <link>https://rip.trb.org/View/2334605</link>
      <description><![CDATA[In this project, the research team aims to develop a secure Electronic Control Unit (ECU) hardware platform for connected vehicles utilizing the RISC-V architecture. The core innovation lies in integrating the Trusted Execution Environment (TEE) and Moving Target Defense (MTD) into the ECU. Specifically, the team plans to perform the following tasks: (1) Tailoring the Keystone TEE: The team will adapt the Keystone TEE specifically for ECU applications. This task involves creating a new firmware-level security monitor optimized for the CAN bus to enable device authentication and message encryption. The team will also modify FreeRTOS to function as the enclave runtime, efficiently managing resources. (2) Implementing a Randomization Module: To facilitate MTD, the team will incorporate a randomization module within the RISC-V core. This step will include modifying the core to include instruction set randomization logic and developing a new firmware-level configuration manager for key generation and secure storage. (3) Developing a Recovery Mechanism: A key component of the project is developing a robust recovery mechanism to ensure uninterrupted vehicle operations during an attack. This will involve setting up a fail-safe enclave that contains backup programs for each essential controller and integrating a recovery module within the configuration manager to activate these backup controllers as needed. 
Moreover, the team will implement the proposed platform on FPGA boards and demonstrate its effectiveness against potential attacks under the environments created in autonomous vehicle simulators. This project aims to provide a comprehensive hardware solution capable of protecting connected vehicles from a range of cyber threats, even in the presence of software vulnerabilities. 
]]></description>
      <pubDate>Mon, 05 Feb 2024 16:13:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2334605</guid>
    </item>
    <item>
      <title>System Design for Highly Accurate and Efficient Target Detection in Triaxial Testing</title>
      <link>https://rip.trb.org/View/2289621</link>
      <description><![CDATA[For photogrammetry-based volume measurement, existing coded target (CT) recognition and identification algorithms have limitations in perspective deformation, freely rotated CTs, and unfavorable light conditions. This study will develop an innovative system design for highly accurate and efficient target detection in triaxial testing. The proposed method will remain all the merits in existing methods and have several improvements, including blob analysis, automatic outlier identification, and an increased number of points on the membrane for more representative 3-D results. The developed photogrammetry-based volume measurement method with the target detection technology will be applied in the widely used triaxial tests to evaluate stress-strain behavior of geomaterials. The method will improve the testing accuracy and efficiency. The low-cost testing system has the potential to be widely adopted by government agencies, contractors, and research institutes.]]></description>
      <pubDate>Tue, 14 Nov 2023 20:26:03 GMT</pubDate>
      <guid>https://rip.trb.org/View/2289621</guid>
    </item>
    <item>
      <title>Emerging Land Mobile Radio Communications Guide</title>
      <link>https://rip.trb.org/View/2197876</link>
      <description><![CDATA[Transportation agencies and public safety organizations frequently lack the subject-matter expertise to select appropriate technology, including communications systems. State, local, tribal, and territorial departments of transportation (DOTs) have invested heavily in land mobile radio (LMR) communications systems to support their field staff during daily activities and incident response or emergencies, and LMR communication continues to be essential to public safety practitioners, including for infrastructure protection, coordination, operations, and emergency response.

NCHRP Project 03-129, "Essential Communications: A Guide to Land Mobile Radio," produced a 483-page guide. Research is complete, but the guide needs to be revised to be suitable for AASHTO consideration.

The objective of this research is to revise the NCHRP Project 03-129 guide and to prepare the final guide for publication under the proposed title Emerging Land Mobile Radio Communications Guide.]]></description>
      <pubDate>Mon, 19 Jun 2023 16:37:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2197876</guid>
    </item>
    <item>
      <title>System Dynamics Models of AV Impacts</title>
      <link>https://rip.trb.org/View/2062790</link>
      <description><![CDATA[A clear understanding of autonomous vehicle (AV) impacts, and how AV adoption will affect the public interest, is of great importance to federal, state and local policy-making. As the impacts of automation are far-reaching, complex and uncertain, it is critical to have a systems-level model for evaluating the potential implications of these new technologies on the transportation system. System dynamics is a quantitative method for modeling complex systems that takes into account feedback effects and changes over time.  This project will build on the results of HW9EA4, HW9EA5 and HW9EA6. These projects developed, respectively, simple quantitative models of the mobility and equity aspects of new modes; a high-level system dynamics model of transportation service providers and transportation demand in an AV world, including vehicle-miles traveled under various policy scenarios; and a model of wider impacts such as changes in vehicle ownership and land use.  This project will support managing uncertain futures in performance-based planning and programming, with a focus on providing methods useful to MPOs, state DOTs, and cities as appropriate.  Outcomes will include (1) a review of relevant research by others, and (2) system dynamics models for exploratory scenario planning that meet the needs of these stakeholders, are sensitive to the current U.S. transportation planning process, and, to the extent possible, are open-access, easy to learn, and quick to run.]]></description>
      <pubDate>Thu, 17 Nov 2022 11:56:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2062790</guid>
    </item>
    <item>
      <title>Guidebook for Truck Parking Information Management Systems</title>
      <link>https://rip.trb.org/View/1707205</link>
      <description><![CDATA[Truck parking demand is driven by economic demand, safety considerations, and the need for adequate rest for commercial vehicle operators. Recent studies of truck parking demand and capacity constraints reflected a consensus that truck parking demand exceeds the available supply in many public rest areas and private truck stops across the nation. Some state departments of transportation (DOTs) have developed truck information management systems to better address commercial vehicle parking needs by reducing parking search time and providing safer parking options through the collection and dissemination of real-time parking availability using a variety of technologies.
There was a need to (1) explore issues such as planning, design, operations, procurement and selection of technologies, the means and format for reporting information, life-cycle considerations, interoperability, and interagency coordination; and (2) develop a guide that presents rational practices for truck parking information management systems. Such guide should be a resource for state DOTs in implementing information management practices that address commercial vehicle parking needs, thereby reducing the challenges associated with the search for safer parking options.

OBJECTIVE: The objective of this research was to develop a guide of suggested practices for the development, connectivity, and management of truck parking information systems. At a minimum, the guide will address planning, design, operations, procurement and selection of technologies, the means and format for reporting information, life-cycle considerations, and interagency coordination.
]]></description>
      <pubDate>Wed, 20 May 2020 14:57:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/1707205</guid>
    </item>
    <item>
      <title>A Handbook for Effective Signaling in Air Traffic Control</title>
      <link>https://rip.trb.org/View/1670686</link>
      <description><![CDATA[The Federal Aviation Administration’s air traffic control organization (ATO) encompasses a variety of facilities that include towers, terminal radar approach control facilities (TRACONs), and air route traffic control centers (ARTCCs). Air traffic controllers continually evaluate the impact of such factors as weather, converging traffic, and emergency situations, using this information to prioritize tasks and solve problems before they can impact flight safety. Controllers generally rely on prospective memory, trying to anticipate events and working proactively to avoid loss of separation or other situations in which an alarm or alert would be required. The purpose of an alarm is to get the immediate attention of a human operator when an abnormal event occurs. Alarms are therefore designed to be intrusive and distracting. Frequent interruptions from nonactionable alarms can disrupt the controller’s prospective memory, and there is evidence that improving the design of alarms and alerts can prevent errors (Loft, 2013). There are additional important reasons to improve the sensitivity and specificity of alarms and to harmonize alarms across equipment and the ATO. Alarm systems that are perceived to be unreliable are likely to provoke the so-called cry-wolf effect (Breznitz, 1984), especially during periods of high workload (Bliss, 2000). A critical first step for solving the problems described above is to create a handbook to guide signaling practice across all ATC facilities. The project team will leverage results of past scientific research regarding signal effectiveness to build an informative resource for controllers and signal designers. After completion of the handbook, the project team will plan to develop a training program for air traffic controllers that provides guidance on how to make the best use of signaling functions to ensure safety. This program will help air traffic controllers to anticipate signals and rely on them appropriately during critical periods, while minimizing the risk of alarm fatigue. Ultimately, well trained controllers should exploit alarms, alerts and warnings to build situation awareness and to lessen cognitive workload.
]]></description>
      <pubDate>Fri, 06 Dec 2019 08:55:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/1670686</guid>
    </item>
    <item>
      <title>Enabling the Shared Transportation Revolution (Project Q2)</title>
      <link>https://rip.trb.org/View/1584716</link>
      <description><![CDATA[The transportation industry is rapidly forming an image of the future that is autonomous, connected, electric and shared. Although electric vehicles may help us make great strides in the area of point-source emissions, and autonomous vehicles may further efforts to improve safety, the congestion impacts of these technologies will be limited and may actually worsen conditions in urban areas. Although transportation network companies (TNCs) offer shared ride services, including LyftLine and UberPool, the number of carpool trips is far less than their typical non-shared services. Shared ownership of vehicles is not enough to mitigate most issues in the transportation system (congestion, inefficiencies, emissions, etc). Pushing toward shared usage is critical in urban areas, however shared usage is dependent on the ability to link travelers to one another and their willingness to share the ride. This research will assess people’s willingness to share space with strangers and those with a social connection and how design of the system and the physical infrastructure can better facilitate this sharing dynamic.]]></description>
      <pubDate>Sat, 23 Mar 2019 12:58:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1584716</guid>
    </item>
    <item>
      <title>Resident Space Object (RSO) System Mechanics Task 372</title>
      <link>https://rip.trb.org/View/1537231</link>
      <description><![CDATA[Effective space situational awareness faces the challenge of bringing together observations from disparate sensors and sources, developing computationally efficient dynamic propagation schemes for orbits and their uncertainty distributions, and formulating accurate estimation methods for the purpose of quantifying and qualifying space-based activities.]]></description>
      <pubDate>Wed, 22 Aug 2018 13:03:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/1537231</guid>
    </item>
    <item>
      <title>Design and Ops Considerations for Human Space Flight Occupant Safety - FIT Task 353</title>
      <link>https://rip.trb.org/View/1537225</link>
      <description><![CDATA[This task involves a normative review and enhancement of the FAA’s Recommended Practices for Human Space Flight Occupant Safety document (Version 1.0, TC14-0037 dated August 27, 2014) from the collective perspectives of each research group spanning vehicle design and outfitting (CU), medical care and health concerns (BCM), and Human Centered Design (Florida Tech).

Two top level aims encompassing general feedback on the Recommended Practices document followed by a systematic approach to provide considerations for design and operational solutions capable of addressing the needs stated in each subject area as a step toward identifying standards.

The Florida Tech’s focus in this collaborative effort was on the Human-System Integration (HSI), interaction and human-system control inside the spacecraft cockpit and cabin. Utilizing Human-Centered Design (HCD) approach (prioritizing human safety, efficiency and comfort throughout the system design). This research effort builds on the previous research in areas of Human-Computer Interaction, Human Factors vehicle cockpit/cabin operations and related aspects of Mission Planning (Task 333 – Onboard Context-Sensitive Informational System).]]></description>
      <pubDate>Wed, 22 Aug 2018 13:03:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1537225</guid>
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