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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>Connected and Automated Vehicle (CAV) Readiness Survey: Are MDOT Roads Machine Readable</title>
      <link>https://rip.trb.org/View/2731918</link>
      <description><![CDATA[Considering Michigan Department of Transportation (MDOT) Mission, Values, and Vision, with the evolving landscape of technologies within the connected and automated
vehicle (CAV) industry, there is a pressing need to investigate the requisite support from DOTs to enable seamless integration of
CAVs with infrastructure. As core sensors and systems defining these technologies become more established, understanding the
precise infrastructure requirements becomes paramount. Therefore, the research aims to address the question: "What specific
support and infrastructure enhancements are necessary from MDOT to facilitate effective detection and interaction of connected and
automated vehicles with the surrounding infrastructure?]]></description>
      <pubDate>Fri, 17 Jul 2026 11:47:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/2731918</guid>
    </item>
    <item>
      <title>Preventing Rear and Side Crashes of Heavy-Duty Tractor Trailer Combinations with Smart Sensors and Vision Systems</title>
      <link>https://rip.trb.org/View/2440025</link>
      <description><![CDATA[The proposed project aims to prevent fatal rear and side crashes related to heavy-duty tractor-trailer combinations. Specifically, the research team proposes to develop and test smart trailer sensors/vision systems that infer "dynamic safety zones” and use lighting signals (or other communication modes) to alarm following and overtaking vehicles, pedestrians, or other non-occupant situations. The proposed trailer sensors/vision systems automatically analyze videos, vehicle size, and loading and brake data to infer collision risks between tractor-trailer combinations and approaching vehicles and people. From 2019 to 2021, fatal rear crashes with large trucks with trailers, where passenger vehicles travel under the rear of the truck, increased from 16.8% to 18.0%. In 2021, other vehicles in the large truck lane (26.5%) and others encroaching into the large truck lane (36.0%) were the two critical pre-crash events that caused such crashes. Drivers usually underestimate the required distance when the safe distance suddenly increases because of the large weights and sizes of the vehicles, unexpected pavement conditions, and terrains that require extra separations between vehicles. Inter-vehicle dynamic safety zones change and differ by situations and changes over time, so manually estimating the safe following and overtaking distances could be unreliable. Sometimes, illusions, slipperiness caused by weather, and poor lighting conditions can bias human estimates and make the reaction too late to stop. The recent integration of computer vision and motion sensors has shown the potential to improve passenger vehicles. However, heavy-duty vehicles, especially trailers, need special consideration of vehicle size, motion planning, road conditions, and occlusions to ensure a reliable assessment of side and rear collision risks in different positions of the tractors and trailers.
The proposed project will integrate the expertise of the project team and two industry partners in developing and testing an intelligent tractor-trailer sensor and vision system and provide benchmark datasets. In construction and airport safety, the project team has integrated computer vision, robotic motion simulation, and spatiotemporal analyses to implement dynamic safety zone estimation solutions for aircraft and construction equipment. The project team has also developed the technique to find safe actions when there is uncertainty in the dynamic system models or environments. The proposed project will adapt these intelligent dynamic safety zone estimation solutions to implement the proposed smart sensors and vision systems on tractor-trailer combinations. An industry collaborator, Clarience Technologies, will work with the project team to use their tractor and trailer fleet to collect video, vehicle, and telematics data to support the development and testing of the proposed smart safety system. Clarience will also leverage its automotive and vehicular engineering background to support the 4D simulation and motion analysis of heavy-duty vehicles in given road and terrain conditions. Another industry partner, Safety Emissions Solutions, has collaborated with the team in integrating inspection reports, crash, and telematic data into ‘vehicle deterioration models’ that predict the crash risks of heavy-duty vehicles. Integrating this expertise, software, data, and hardware from the researchers and industry will ensure the timely delivery of the proposed dynamic safety zone estimation solution and the benchmark data sets. ]]></description>
      <pubDate>Sun, 13 Oct 2024 09:43:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440025</guid>
    </item>
    <item>
      <title>Sensitivity and Reliability for Cybersecurity of Traffic with Autonomous Vehicle Participation</title>
      <link>https://rip.trb.org/View/2301342</link>
      <description><![CDATA[The use of Sensitivity and Reliability Analysis is not new in transportation studies, where it has been utilized in traffic flow related problems. However, in this project the research team proposes to use it for helping feedback control decisions in real-time. A basic reason for the use of feedback is to render a closed loop system less susceptible to the effects of plant parameter variations than an open-loop system having the same nominal input-output characteristics. The team will be leading to obtaining a method and generating software to identify which components either on the vehicle or infrastructure would need to be changed for the highly autonomous vehicle (HAV) to be more cybersecure. The team proposes to focus on three thrusts: (1) identify emerging cybersecurity threats to Highly Automated Transportation Systems (HATS); (2) analyze threat scenarios; (3) mitigation methods utilizing sensitivity functions. The team shall base this research on both their results in the previous University Transportation Center (UTC) at The Ohio State University and their earlier work on decentralized systems.]]></description>
      <pubDate>Fri, 01 Dec 2023 05:14:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2301342</guid>
    </item>
    <item>
      <title>SPR-4322: Development of an Intelligent Snowplow Truck that Integrates Telematics Technology, Roadway Sensors, and Connected Vehicles</title>
      <link>https://rip.trb.org/View/1577032</link>
      <description><![CDATA[There is a need to leverage the deployed fleet of trucks with spreader/plow data logging capability to monitor how winter operation assets are deployed, construct performance measures charts, and identify best practices for material application rates.]]></description>
      <pubDate>Thu, 03 Jan 2019 14:14:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/1577032</guid>
    </item>
    <item>
      <title>Impacts of Connected Vehicles and Automated Vehicles on State and Local Transportation Agencies--Task-Order Support. Infrastructure Modifications to improve the Operational Domain of Automated Vehicles</title>
      <link>https://rip.trb.org/View/1571373</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Mon, 03 Dec 2018 15:39:03 GMT</pubDate>
      <guid>https://rip.trb.org/View/1571373</guid>
    </item>
    <item>
      <title>SPR-4315: Develop and Deploy a Safe Truck Platoon Testing Protocol for
the Purdue ARPA-E Project in Indiana</title>
      <link>https://rip.trb.org/View/1563608</link>
      <description><![CDATA[Deploy platooning of two Class 8 trucks on Indiana interstate and US highways in both a test and production mode. Explore unique challenges and present potential solutions to the connected transportation sector. Provide guidelines for INDOT deployment to advance Indiana as a leader in transportation.
]]></description>
      <pubDate>Tue, 16 Oct 2018 13:44:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/1563608</guid>
    </item>
    <item>
      <title>Next Generation of Freight Planning and Operation Models To Incorporate Emerging Innovative Technologies </title>
      <link>https://rip.trb.org/View/1552815</link>
      <description><![CDATA[This project leverages expertise from three universities (FAU, PSU, UoM) and attempts to accomplish the project objectives to (1) quantify adoption of connected and autonomous trucks by freight organizations, (2) incorporate truck platooning in transportation planning and operation models, (3) analyze the emissions impacts of  last mile deliveries by delivery robots, (4) study how disruptive technologies are affecting intermodal transportation, and (5) outline future research necessary to address the opportunities and challenges created by disruptive technologies.
Recent rapid explosion of new technologies have created opportunities to address critical freight transportation challenges across all modes in urban, suburban and rural areas. Some examples of new technologies include expansion of e-commerce, last mile deliveries by unmanned aerial vehicles (UAVs) or delivery robots, and potential applications of automated and connected vehicles in freight transportation (e.g. truck platooning). These new technologies are also influencing consumer behavior and thereby reshaping freight supply chains at the urban, regional, and international level. First, the project will develop diffusion of innovation based models to predict how the adoption of autonomous trucks will be in the future by freight organizations. Second, the study will address how truck platooning will be incorporated in transportation planning models such as how many trucks will be allowed in a platoon, platoon speed, platooning hours, freeway platooning zones, etc. Third, the study will model the potential emissions impacts of last mile delivery robots. Fourth, assess the role and feasibility of technological innovations in intermodal transportation. Finally, the project will summarize the findings, challenges, and scope for future research. ]]></description>
      <pubDate>Wed, 03 Oct 2018 15:34:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/1552815</guid>
    </item>
    <item>
      <title>Modeling Adoption of Autonomous Vehicle Technologies by Freight Organizations</title>
      <link>https://rip.trb.org/View/1531770</link>
      <description><![CDATA[Over the last few years, a rapid explosion of new technologies has created opportunities to address critical freight transportation challenges in urban, suburban and rural areas. Some examples of new technologies include expansion of e-commerce, 3-D printing, deliveries by unmanned aerial vehicles (UAVs or drones), and potential applications of automated and connected vehicles in freight transportation (e.g. truck platooning). These new technologies are also influencing consumer behavior and thereby reshaping freight supply chains at the urban, regional, and international level. 

The autonomous vehicle technologies use new features including smartphones, vehicle fleet tracking (global positioning system (GPS), and location-based systems), sensors (vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I)), enhanced imaging technologies, and other sources that arise from broader smart city initiatives. While the fully autonomous vehicle technology is yet to come, some of the new features are already available and some freight organizations are already adopting them. These new technologies and data sources are creating new challenges for freight planners in identifying the potential non-adopters and adopters. In addition, how the adoption will vary over time. Adoption methods available from consumer behavior research are mostly based on individuals and limited to organizations. The general adoption methods cannot be directly used in modeling adoption of freight organizations. 

The main objectives of this project are to (1) review rapidly emerging technologies affecting freight planning and operations; (2) survey stakeholders to identify their inclination, and (3) outline future research steps necessary to meet future local agencies, metropolitan planning organizations (MPOs) and state departments of transportation (DOTs) freight planning and performance evaluation needs.]]></description>
      <pubDate>Sat, 11 Aug 2018 22:16:03 GMT</pubDate>
      <guid>https://rip.trb.org/View/1531770</guid>
    </item>
    <item>
      <title>Cybersecurity Analysis to Prepare VDOT Operations for Connected and Autonomous Vehicle Applications</title>
      <link>https://rip.trb.org/View/1526688</link>
      <description><![CDATA[In this research, a prototype ATM system along with a real-time cyberattack monitoring system were developed for a 1.5-mile section of I-66 in Northern Virginia. The monitoring system detects deviation from expected operation of an ATM system by comparing lane control states generated by the ATM system with lane control states deemed most likely by the monitoring system. This comparison provides the functionality to continuously monitor the system for abnormalities that would result from a cyberattack. In case of any deviation between two sets of states, the monitoring system displays the lane control states generated by the back-up data
source.
In a simulation experiment, the prototype ATM system and cyberattack monitoring system were subject to emulated cyberattacks. The evaluation results showed that the ATM system, when operating properly in the absence of attacks, improved average vehicle speed in the system to 60mph (a 13% increase compared to the baseline case without ATM). However, when subject to cyberattack, the mean speed reduced by 15% compared to the case with the ATM system and was similar to the baseline case. This illustrates that the effectiveness of the ATM system was negated by cyberattacks. The monitoring system however, allowed the ATM system to revert to an expected state with a mean speed of 59mph and reduced the negative impact of
cyberattacks. These results illustrate the need to revisit ATM system design concepts as a means to protect against cyberattacks in addition to traditional system intrusion prevention approaches.]]></description>
      <pubDate>Thu, 26 Jul 2018 19:30:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1526688</guid>
    </item>
    <item>
      <title>Administration of Highway and Transportation Agencies. Strategic Research in Support of the Connected and Automated Vehicle Executive Leadership Team</title>
      <link>https://rip.trb.org/View/1521555</link>
      <description><![CDATA[With the rapid advance of technologies for realizing connected and automated vehicles (CAV) suited for use on public roads, many stakeholders in the public and private sectors have recognized the value of maintaining active forums for discussion of common problems and seeking out potential solutions to those problems. The Connected and Automated Vehicle Executive Leadership Team (CAV-ELT), for example, is a self-organized group concerned with facilitating progress in development and adoption of connected and automated vehicle technologies.  The membership includes executives from state and local transportation agencies, automobile manufacturers, other private-sector entities, and the U.S. Department of Transportation (USDOT).  The Vehicle-to-Infrastructure Deployment Coalition (V2I-DC), another example, has been formed to serve as a single point of reference for stakeholders from public transportation agencies, the private sector, and academia to meet and discuss V2I deployment related issues.  Many state departments of transportation (DOTs) and the American Association of State Highway and Transportation Officials (AASHTO) have been actively engaged with these groups. In 2016, the CAV-ELT identified following seven high priority policy issues areas and developed concept definitions outlining research initiatives to address each issue:   National Guidelines, Early-Stage Risks, Interoperability, Industry-Government Information Exchange, Data Access Provisions, Public Outreach and Education, and   Planning Scenarios. With the leadership of AASHTO’s member DOTs, NCHRP research initiatives have been undertaken to address specific concerns in the first two of these policy issues areas: National Guidelines and Early Stage Risks.  Research is needed to refine the CAV-ELT concept definitions and advance policy development in the remaining 5 issues areas.  This research should build on continuing activities engaging CAV-ELT and V2I-DC members and others, such as the “AV Round Table” held in conjunction with the 2017 SAE Auto Show, meetings of the “IOO-OEM Forum” (collaboration of Infrastructure Owner Operators (IOOs) and the Original Equipment Manufacturers (OEMs)), and activities surrounding the “SPaT Challenge” (to deploy DSRC-based broadcasts of Signal Phase and Timing (SPaT) messages in about 20 intersections in each of the 50 states by 2020). The objective of this project will be to provide technical support for continuing DOT engagement with the CAV-ELT and V2I-DC in pursuit policy development in previously defined issues areas.  The work will be linked to ongoing activities of AASHTO and its member DOTs.]]></description>
      <pubDate>Tue, 03 Jul 2018 09:20:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/1521555</guid>
    </item>
    <item>
      <title>Assessing the Impacts of Automated Driving Systems (ADS) on the Future of Transportation Safety</title>
      <link>https://rip.trb.org/View/1516174</link>
      <description><![CDATA[Transportation agencies are charged with an increasingly complex task of balancing the needs to preserve and maintain assets while introducing new assets into an already overwhelmed transportation system. Gradually, organizations are recognizing that past practices of designing what is considered a safe traveling environment is changing as the vehicle fleet evolves to more connected, autonomous and automated driving. While it is understood that impacts are relatively minor today, the implications on the design and operational criteria of tomorrow will be substantial.
Research is needed to understand and plan for these impacts and to consider how they could change the way we plan, design, and operate to address the contributing factors for crashes on our facilities. Federal, state, and local public agencies recognize that there are challenges with maintaining the state of good repair on many assets with existing resources. Failure to adequately do so may have an impact on roadway safety and operations. Federal, state, and local public agencies will need to effectively manage resources given the opportunities that ADS brings, while maintaining safety and mobility throughout its adoption.
 
The objective of this research was to develop a framework for practitioners (e.g., transportation infrastructure owners, safety agencies, road users and ADS manufacturers) to use in current and future safety planning, design, operational decisions, and investments on multimodal infrastructure.
]]></description>
      <pubDate>Tue, 19 Jun 2018 10:19:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1516174</guid>
    </item>
    <item>
      <title>Leader-Follower TMA System</title>
      <link>https://rip.trb.org/View/1511448</link>
      <description><![CDATA[The Missouri Department of Transportation's (MoDOT's) mobile and slow moving operations, such as striping, sweeping, bridge flushing and pothole patching, are critical for efficient and safe operation of the highway transportation system.  MoDOT's slow moving operations have been crashed into over 80 times since 2013 resulting in many injuries to MoDOT employees.  The objective of this request for proposal (RFP) is to provide a National Cooperative Highway Research Program (NCHRP) 350 Level 3 compliant Leader-Follower truck mounted attenuator (TMA) System capable of operating a driverless rear advanced warning truck in mobile highway operations as described in Traffic Application TA-35a. The system shall consist of a Lead Truck (LT) and a Rear Advanced Warning Truck called the Follow Truck (FT).  The goal is to avoid operator injury by eliminating the need for a human operator in the FT. ]]></description>
      <pubDate>Fri, 04 May 2018 09:15:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/1511448</guid>
    </item>
    <item>
      <title>The Future of Mobility Workshop Series</title>
      <link>https://rip.trb.org/View/1508471</link>
      <description><![CDATA[The Future of Mobility is a series of three workshops about timely issues in transportation: 1) Autonomous, Shared and Electric Revolutions in New York City; 2) Women’s Challenges in Transportation; and 3) Startup Showcase.]]></description>
      <pubDate>Thu, 12 Apr 2018 00:16:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/1508471</guid>
    </item>
    <item>
      <title>Integrative Vehicle-Traffic Control in Connected/Automated Cities</title>
      <link>https://rip.trb.org/View/1508470</link>
      <description><![CDATA[In connected/automated cities, (some) vehicles can drive themselves and are connected with each other, with the infrastructure, and with the rest of the world (e.g., pedestrians). As a result, their individualized characteristics (such as vehicle types, dynamics, emission/fuel consumption characteristics) can be revealed in such a connected environment. This provides opportunities and challenges for both traffic signal control and vehicle control. It calls for integrative vehicle traffic control (iVTC) to simultaneously control vehicle (speed profiles, engine, battery management if electric vehicles are concerned) and signal timing to address the safety, mobility, and energy consumption issues. The proposed research aims to investigate the key issues for iVTC, which will lay the foundation for real world implementation of iVTC in the future.]]></description>
      <pubDate>Thu, 12 Apr 2018 00:12:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/1508470</guid>
    </item>
    <item>
      <title>Advisory Council on Automated Transportation</title>
      <link>https://rip.trb.org/View/1507570</link>
      <description><![CDATA[The State of Iowa has taken a proactive approach to preparing for increasing levels of vehicle automation on Iowa roadways. In partnership with the Iowa Department of Transportation (DOT), the University of Iowa (UI), and Iowa State University (ISU) have undertaken several activities and proofs-of-concepts to carefully identify and consider various elements of the deployments of connected and automated vehicles (AV) and advanced roadside technologies. These activities, along with recent developments, have highlighted the importance of establishing a cohesive working group or advisory council in Iowa dedicated to the strategic oversight of connected and automated transportation systems. This council would serve as the focal point of topics and
activities related broadly to connected and AV technologies as part of a “safe, reliable, and efficient transportation system that is AV Ready.” Organization of such a council provides the State the ability to not only strategically plan and consider the deployment of automated transportation technologies, but also quickly respond to unforeseen issues and topics that present themselves as these technologies continue to evolve. Under support and guidance from the Iowa DOT, the research team proposes that the UI take the support and administrative role in organizing the activities of an Iowa Advisory Council on Automated Transportation.]]></description>
      <pubDate>Mon, 02 Apr 2018 13:06:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1507570</guid>
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