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    <title>Research in Progress (RIP)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Selection, Integration, and Effectiveness Study of Input Data for Nebraska Variable Speed Signs on I-80</title>
      <link>https://rip.trb.org/View/2507247</link>
      <description><![CDATA[Variable Speed Signs (VSS) are critical for enhancing road safety and traffic efficiency, particularly under adverse weather and traffic conditions. VSS dynamically adjusts speed limits based on real-time data inputs such as traffic flow, weather conditions, and visibility, providing drivers with contextually appropriate speed recommendations. The implementation of VSS systems has been shown to improve traffic safety, reduce crash rates, and enhance overall roadway efficiency, particularly on high-volume corridors such as Nebraska’s I-80.
Several studies highlight the efficacy of VSS systems [1 - 3]. Research conducted by state Departments of Transportation (DOTs), such as Minnesota and Wyoming, has demonstrated that VSS systems can reduce crashes by accounting for real-time environmental factors (e.g., wet or icy road conditions). Similarly, academic studies underscore the importance of integrating advanced sensing technologies and reliable algorithms for speed recommendation, which enhance the credibility and acceptance of VSS by drivers.
Despite their proven benefits, VSS implementations face challenges, including selecting optimal data inputs, integrating various sensor technologies, and evaluating system performance under extreme conditions. In Nebraska, where I-80 serves as a critical freight and passenger corridor, these challenges are amplified by frequent adverse weather conditions, including snow, ice, and fog. These conditions necessitate a robust approach to data collection, algorithm development, and system integration to ensure the VSS recommendations align with real-world conditions and driver behavior]]></description>
      <pubDate>Mon, 10 Feb 2025 14:01:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2507247</guid>
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    <item>
      <title>Semi-Automation of Interstate-90 Variable Speed Limit (I-90 VSL) Corridor in Ohio's Advanced Traffic Management System (ATMS)
</title>
      <link>https://rip.trb.org/View/2431342</link>
      <description><![CDATA[The current process to adjust speeds on the corridor includes utilizing various data/tools such as speed sensors, CCTV cameras, road weather information systems (RWIS), and communications from local authorities.  A Statewide Traffic Management Center (TMC) Specialist has to manually monitor the information from the sources then make a decision as to whether speeds should be adjusted in the corridor.  Ohio Department of Transportation (ODOT) would like to remove the subjectivity of this process by creating a set of thresholds/criteria to change speeds based on data-driven research.

The goal of this research is to provide data-based decision support in a semi-automated fashion to improve the efficiency and effectiveness of managing the I-90 Variable Speed Limit (VSL) Corridor.                ]]></description>
      <pubDate>Tue, 17 Sep 2024 14:37:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2431342</guid>
    </item>
    <item>
      <title>Automating Variable Speed Limits Using Weather, Traffic and Friction Data</title>
      <link>https://rip.trb.org/View/2342045</link>
      <description><![CDATA[Variable speed limits (VSLs) are useful in promoting highway safety. Along these lines, the Federal Highway Administration (FHWA) mentions, “the use of VSLs during inclement weather or other less than ideal conditions can improve safety by decreasing the risks associated with traveling at speeds that are higher than appropriate for the conditions.”

The goal of this proposal is to automatically recommend speeds for various weather conditions (rainfall, snow, ice, fog, etc.) at roadway segments that are good candidates for VSL. This means that the roadway segments should frequently experience adverse weather conditions (such as snow, rain, fog, etc.), high traffic, or safety hazards. The crash rate at such road segments should generally be higher than average. The research team expects to gather road weather information system (RWIS), traffic, friction, incident, and potentially other data sets over one or more seasons that typically exhibit adverse weather. The team will then utilize the collected data and develop analysis methodology in establishing VSL algorithms that consider different terrain types, roadway geometries, and weather conditions (rainfall, snow, ice, fog, etc.). The team will explore the usage of machine learning (ML) algorithms and other approaches in establishing VSL. The speed limits will be set to satisfy the driver’s visibility and stopping sight distance requirements and also prevent lateral slippage at curved sections considering the loss of friction due to inclement weather conditions.]]></description>
      <pubDate>Mon, 19 Feb 2024 18:55:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342045</guid>
    </item>
    <item>
      <title>Dynamic Coordinated Speed Control and Synergistic Performance Evaluation in Connected and Automated Vehicle Environment</title>
      <link>https://rip.trb.org/View/2010010</link>
      <description><![CDATA[Due to inherent restrictions in human driving behavior and information access, freeway congestion and stop-and-go behavior are nearly unavoidable. The adverse impacts include increased safety risks, longer travel times, and excessive fuel consumption. Various techniques (e.g., Variable Speed Limit (VSL), which is also known as Dynamic Speed Harmonization (DSH)), have been proposed to dampen traffic oscillation and smooth traffic speed.
However, the effectiveness of the VSL is related to the compliance rates of drivers. In addition, there are delays in the collection of information, and control strategies can only affect a small area. Fortunately, new opportunities are emerging with the development of Connected and Automated Vehicles (CAVs) that can completely comply with the control system. Numerous CAV applications are explored as part of the Intelligent Transportation Systems (ITS) to enhance a range of Measures of Effectiveness (MOEs), such as safety, mobility, and environmental sustainability.
The objective of this study is to investigate the effects of coordinated speed control in mixed traffic flow involving Human-Driven Vehicles (HDVs) and CAVs on the freeway. Therefore, a dynamic two-phase strategy based on Deep Reinforcement learning (DRL) is developed to better understand how CAVs can improve operational performance. To evaluate and quantify the impact, a comprehensive performance framework is formulated. A series of numerical experiments will be conducted under different traffic demands and market penetration rates (MPRs) under various simulated scenarios. The overall intent of this study is to inform practitioners about the potential interactions between MOEs in implementing specific control strategies in CAV environment.]]></description>
      <pubDate>Fri, 19 Aug 2022 15:10:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2010010</guid>
    </item>
    <item>
      <title>Reinforcement Learning for Optimal Speed Limit Control Over Network</title>
      <link>https://rip.trb.org/View/1870420</link>
      <description><![CDATA[The goal is to optimize variable speed limit control (VSLC) strategies over network to improve both traffic safety and mobility. The investigators propose to use graph-based deep reinforcement learning to improve the control effectiveness and scalability. The proposed research will advance the current knowledge and practice of VSLC in two aspects. First, this research will enlarge the scope of VSLC from link-based to network-based control to bring a new understanding about its system-level safety implications. Second, it will optimize the impact of VSLC using multi-objective learning approaches considering both safety and mobility.]]></description>
      <pubDate>Wed, 04 Aug 2021 14:49:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/1870420</guid>
    </item>
    <item>
      <title>SPR-4636: Research Support to INDOT on I-465 Southeast Variable Speed Limit and Ramp Meter Project</title>
      <link>https://rip.trb.org/View/1858258</link>
      <description><![CDATA[This project will develop analysis techniques and performance measures for the variable speed limit (VSL) and ramp meter deployment for I-465 on the southeast side of Indianapolis. These performance measures will be used to provide agile adjustments to the VSL deployments and inform the agency on expected benefits in future
deployments on urban freeways elsewhere in the state.]]></description>
      <pubDate>Thu, 10 Jun 2021 15:39:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/1858258</guid>
    </item>
    <item>
      <title>Evaluating the Impacts of Real-Time Warnings and Variable Speed Limits on Safety and Travel Reliability during Weather Events







</title>
      <link>https://rip.trb.org/View/1854164</link>
      <description><![CDATA[Road Weather Management (RWM) has advanced significantly with new sources of road weather data and greater opportunities for more active management of roadways through direct communication with drivers. Pilot RWM applications and strategies have proven effective during weather events. Actively managing the system using variable speed limits (VSL) and real-time motorist warnings (RTW) based upon real-time weather and road condition data have proven to be effective strategies. However, additional research is needed to advance the practice and application of VSL and RTW nationally.

 Because the effectiveness of these solutions depends on driver behavior, infrastructure owner operators (IOO) must understand the operational environment and the anticipated responses of drivers. For either VSL or RTW to be effective, the IOOs must know the current and anticipated environmental conditions, understand their impacts on mobility and safety, and formulate effective traffic management strategies to alert drivers. IOOs must understand how drivers receive VSL and RTW messages; interpret and integrate these messages with their own observations of roadway conditions; and react during different types of weather events. IOO’s must also understand the best ways to capture drivers’ attention; learn whether drivers respond differently to advisory or regulatory messaging; and understand the influence of other human factors and driver behaviors. Consistent and effective messaging would help IOOs achieve safer, more reliable transportation during adverse weather.

 OBJECTIVES: The objectives of this research are to (1) identify strategies and information needed to formulate effective messaging (including VSL and RTW) to elicit appropriate driver behavior and aid highway safety and mobility; (2) describe how to convey messaging with consideration of message locations, content, platform, and timing; and (3) identify the means to determine the effectiveness of the deployment of real-time messaging, including VSL and RTW, on safety and travel reliability.]]></description>
      <pubDate>Tue, 25 May 2021 12:20:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1854164</guid>
    </item>
    <item>
      <title>Integration of Ramp Metering, Variable Speed Limit, and Off-Ramp Progression</title>
      <link>https://rip.trb.org/View/1592822</link>
      <description><![CDATA[The primary objective of this project is to construct an integrated freeway control system that can effectively guide the potential users to timely activate key system components either concurrently or sequentially in contending with daily recurrent congestion in real-time operations. The system shall have the following key features:
(1) Taking full advantages of state-of-the-art developments on freeway traffic controls, including dynamic coordinated ramp metering, variable speed limits, off-ramp signal progression, and on-line detection of congestion patterns; (2) Identifying missing links that prevent existing freeway control models from effective use in practice, and developing essential algorithms to integrate such models/strategies to function reliably under operational constraints; (3) Having a real-time congestion detection module; and
(4) Offering a user-friendly advisory module to assist responsible agencies in selecting proper traffic control strategies and activating them in proper sequences in real-time operations.]]></description>
      <pubDate>Fri, 15 Mar 2019 14:20:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1592822</guid>
    </item>
    <item>
      <title>Implementation of SHRP2 Results within the Wyoming Connected Vehicle Variable Speed Limit System SHRP2 Implementation Assistance Program (Round 4)</title>
      <link>https://rip.trb.org/View/1571600</link>
      <description><![CDATA[The primary objective of the second phase is to model drivers responses to various adverse weather and road conditions, to specifically address: (1) Can trips occurring in inclement weather be identified efficiently and effectively using NDS and RID data? (2)  Can driver behavior during inclement weather conditions be characterized efficiently from the NDS? (3) What are the best surrogate measures for weather-related crashes that can be identified using the NDS data? (4) What type of analysis can be performed and conclusions be drawn from the resulting dataset? and (5) Can the NDS data be extrapolated to provide real-time weather information in the context of the Road Weather Connected Vehicle Applications?  

The vital purpose of Phase 2 is to generate models representing driving behavior changes as a function of weather conditions and includes investigation into speed selection, lane changing, and car following models.  ]]></description>
      <pubDate>Wed, 05 Dec 2018 12:40:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/1571600</guid>
    </item>
    <item>
      <title>Field Test of Variable Speed Advisory (VSA) for Freeway Traffic Control</title>
      <link>https://rip.trb.org/View/1427378</link>
      <description><![CDATA[The objective of this project is to do a field test of Variable Speed Advisory (VSA) on SR78 in California Department of Transportation (Caltrans) District 11 in San Diego. If the field test results are favorable, this could provide the basis for future widespread adoption of VSA control strategies to improve mobility and safety and reduce energy and emissions impacts of freeway congestion. The main tasks of the project will involve: (1) microscopic simulation of the algorithm for the corridor for parameter selection; (2) real-time traffic data retrieving and processing to generate required traffic state parameters; (3) ConOps development and iterative refinement; (4) VSA system development, implementation and integration; (5) project outreach to the public drivers; (6) progressive field test; and (7) performance evaluation. The test site was selected as SR 78 between Interstate 5 and Interstate 15 in District 11. Caltrans District 11 Traffic Operation Division has agreed to support the test.]]></description>
      <pubDate>Tue, 25 Oct 2016 10:31:40 GMT</pubDate>
      <guid>https://rip.trb.org/View/1427378</guid>
    </item>
    <item>
      <title>SPR-3900: Variable Speed Limit Feasibility Study</title>
      <link>https://rip.trb.org/View/1357042</link>
      <description><![CDATA[A combination of spot mean speed (laser) and space mean speed (INRIX) will be used to evaluate the impact of variable speed limit signs deployed on I65. Statistical analysis of mean, median and variance will be performed.]]></description>
      <pubDate>Wed, 10 Jun 2015 01:01:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1357042</guid>
    </item>
    <item>
      <title>Bounded Acceleration and Capacity Drop at Merging Bottlenecks</title>
      <link>https://rip.trb.org/View/1239205</link>
      <description><![CDATA[The objective of this research is to prove the conjecture that bounded acceleration rates of vehicles can lead to capacity drop inside a merging area. Capacity drop is one of the most puzzling traffic phenomena occurring near such bottlenecks as lane-drop and merges. While it has been suspected that such a capacity drop is caused by drivers' acceleration behaviors inside various bottleneck areas, there have been no systematic studies on the relationship between drivers' acceleration process and the magnitude of capacity drop. In this research the aim is to develop, calibrate, and validate a macroscopic model of acceleration behaviors inside a merging bottleneck and quantify their impacts on capacity drop. From observed vehicles' trajectories, the project will calibrate acceleration rates and distances inside such an acceleration zone and calculate the magnitude of capacity drop using the macroscopic acceleration behavior model. The result will be compared with the observed capacity drop from loop detector data. Such a research can improve our understanding of the mechanism and magnitude of capacity drops at freeway bottlenecks. The knowledge can then be employed towards improving ramp metering, variable speed limits, and other control strategies to reduce congestion and vehicle emissions in a road network.]]></description>
      <pubDate>Thu, 31 Jan 2013 01:01:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/1239205</guid>
    </item>
    <item>
      <title>Preparations for Field Testing of Combined Variable Speed Limit and Coordinated Ramp Metering for Freeway Traffic Control</title>
      <link>https://rip.trb.org/View/1234187</link>
      <description><![CDATA[The proposed effort will conduct a limited scale field test of a freeway traffic control strategy combining Variable Speed Limits (VSL) and Coordinated Ramp Metering (CRM) to determine its ability to increase the effective capacity of a recurrent bottleneck. This addresses an urgent problem for California's congested urban freeways, offering a potentially inexpensive way of increasing the achievable capacity of the recurrent bottlenecks that limit traffic flow and speed during busy periods. If successful, it can be deployed in congested freeway corridors throughout the state. The proposed effort will prepare the way for future field testing of Variable Speed Advisory (VSA) and Coordinated Ramp Metering (CRM). The work will include: (1) Refinement of site selection criteria and selection of proper site for field testing; (2) Extensive literature review focusing on the experiences of field testing and practice of VSL/VSA and CRM in the U.S., Europe and world-wide; (3) Preparations for process control computers and single functionality Variable Message Signs (VMS) that will be needed for the subsequent tests; (4) Data collection and microscopic traffic modeling of selected site; and (5) Validation of the previously developed VSL and CRM simulation and algorithm for the selected site. The VSA and CRM strategies are expected to relieve congestion by avoiding or delaying traffic flow breakdowns at recurrent freeway bottleneck locations, based on results of prior research. The new research and testing are needed to determine how well the previous theoretical results and the actual experiences with these strategies in other countries can be extended to real-world operations in California. The deployable outcome of the project will be the detailed plans for field testing of VSA and CRM on a California freeway corridor, developed in close coordination with the local Caltrans District traffic operations personnel. This will provide the basis for a subsequent field test, and assuming success of the field test the strategies could then be deployed by Caltrans. Constraints: The project needs cooperation with the local District traffic operations staff, but interest has already been expressed by both District 4 and 7.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:08:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/1234187</guid>
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