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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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    <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>Understanding Risks and Opportunities for Ramp Metering Control in a Mixed-autonomy Future</title>
      <link>https://rip.trb.org/View/2651988</link>
      <description><![CDATA[Vehicle automation may change traffic flow dynamics. This will also impact the control of traffic flow via infrastructure-based systems such as ramp metering control. In this work the research team investigated the impact that different levels of automation and connectivity will have on ramp metering control, and proposed modifications to existing ramp metering algorithms to improve their performance under different automation scenarios. The team finds that low-level automation such as adaptive cruise control may decrease mainline throughput by up to 58% on average and increase travel time by 61%. However, full connectivity and automation may decrease travel time by up to 40%. Based on these potential impacts, modifications to the ramp metering algorithm settings were developed for each of the seven automation scenarios. These modifications are shown to improve operations in each scenario.]]></description>
      <pubDate>Thu, 08 Jan 2026 15:26:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2651988</guid>
    </item>
    <item>
      <title>Development and Implementation of Coordinated Adaptive Ramp Metering (CARM) in Southern California Interstates for Congestion Mitigation</title>
      <link>https://rip.trb.org/View/2506242</link>
      <description><![CDATA[The goal of this proposed Coordinated Adaptive Ramp Metering (CARM) implementation project is to mitigate congestion and improve traffic flow along the interstate I-15 corridor in the Southern California region. This advanced traffic management system aims to optimize freeway operations by dynamically adjusting ramp metering rates based on real-time traffic conditions across the entire I-15 corridor. By implementing CARM, the project seeks to increase average speeds, reduce travel times, enhance safety, and improve overall traffic efficiency. The existing ramp metering approach at key on-ramps such as Magnolia Ave, Ontario Ave, El Cerrito Road, and Cajalco Road lacks automatic responsiveness to crashes and lane-blocking events, coordination across multiple ramps, and optimal queue distribution to increase corridor throughput.

To address these issues, a Coordinated Adaptive Ramp Metering (CARM) system is proposed. CARM is an advanced traffic management strategy that dynamically adjusts ramp metering rates based on real-time traffic conditions across an entire freeway corridor. This system aims to optimize freeway operations by (a) Coordinating multiple ramp meters to work together, balancing the flow of vehicles entering the freeway (b) Using centralized adaptive algorithms to analyze data from the entire corridor and adjust metering behavior accordingly (c) Maximizing freeway throughput while minimizing queues on the ramps d) Responding in real-time to traffic incidents and congestion.

The project will implement the following objectives- (1) Develop and implement a CARM system on I-15 southbound between SR-91 and Cajalco Road to reduce PM peak period congestion by automatically adjusting metering rates in response to real-time traffic conditions, including crashes and lane-blocking events. (2) Optimize ramp metering algorithms to distribute queues across multiple on-ramps (Magnolia Ave, Ontario Ave, El Cerrito Road, and Cajalco Road) to increase overall corridor throughput during peak periods.


USDOT Priorities:

The USDOT Strategic Plan for FY 2022-2026 prioritizes strategies that improve system operations to increase travel time reliability, manage travel demand, and improve connectivity. This project directly aligns with those strategies by promoting the adoption of transportation management and operations (TSMO) practices. Also, this project improves travel time reliability on congested corridors. This project is aligned with Objective 1 of MCEEST’s goals - Create a safer, more reliable, and more resilient transportation system that improves equity through increased access to jobs, housing, services, and other opportunities for historically underserved communities. Interstate 15 in the San Bernardino and Riverside counties in California passes through historically disadvantaged communities. The congestion on I-15 is a major reason why these communities have difficulties accessing jobs and services.]]></description>
      <pubDate>Fri, 07 Feb 2025 16:07:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2506242</guid>
    </item>
    <item>
      <title>Design and evaluation of an Arterial-Friendly Local Ramp Metering System</title>
      <link>https://rip.trb.org/View/2250737</link>
      <description><![CDATA[To address the widespread concern of an on-ramp control’s negative impacts (e.g., ramp queue spillover) on a neighboring arterial’s traffic conditions, the research team, with the support of Maryland Department of Transportation State Highway Administration's (MDOT SHA’s) staff/engineers, has recently developed an innovative Arterial-Friendly Ramp (AF-Ramp) metering system, which aims to maximize the total benefits of the freeway and arterial users with both an optimized ramp metering rate and a coordinated signal plan for intersections within the ramp-impact area. Different from current ramp-metering models in the literature and in practice, the proposed AF-Ramp system includes the target freeway segment, its on-ramp, and neighboring intersections in one integrated control environment, and converts them from competing for available roadway capacity to a coordinated mode that maximizes their total benefits. To ensure the AF-Ramp system’s effectiveness in addressing complex, local-specific traffic patterns, it is essential that a rigorous and extensive field evaluation be conducted with respect to the system’s key model parameters and embedded assumptions. The coordinated relationship between the system’s three primary models, from estimating the freeway’s remaining capacity for ramp flows to the optimization of ramp metering rate and intersection signal plans, can also be assessed with the field data. 
]]></description>
      <pubDate>Thu, 21 Sep 2023 14:59:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2250737</guid>
    </item>
    <item>
      <title>Design and Demonstration of an Arterial-Friendly Local Ramp Metering Control System</title>
      <link>https://rip.trb.org/View/2071697</link>
      <description><![CDATA[Highways and arterials are highly inter-dependent, but may have their own operational strategies and systems that do not necessarily synchronize. As a result, traffic queues can spillover from highway to arterials, or the other way around, leading to substantial congestion that worsens the system performance. Coordinating the signal control system on arterials and ramp metering control on ramps are key to mitigating such congestion. Most signal or ramp metering systems can alleviate queues locally to some extent under non-recurrent congestion (being responsive or reactive), but are not designed to prevent queuing from the occurrence of incidents (being predictive) nor mitigate congestion for the joint network. Managing traffic predictively (or proactively) and coordinating ramp metering and street signals among all relevant highway on-ramps/off-ramps can effectively improve the joint network performance. This research project addresses two problems for an integrated Transportation Systems Management and Operations (TSMO) system: ahead-of-curve prediction and system-level signal and ramp metering coordination, and quantify the network benefits of operational strategies to improve mobility/safety.]]></description>
      <pubDate>Thu, 01 Dec 2022 10:56:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2071697</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>Development and Evaluation of Collaborative Ramp Metering Control for Congested Urban Freeways</title>
      <link>https://rip.trb.org/View/1844346</link>
      <description><![CDATA[Advanced Driver Assistance Systems (ADAS) and autonomous vehicles allow new control paradigms in traffic management. As the time horizon for driverless cars technology shifted forward in the future, collaborative driving and communication open new possibilities in the next 5-10y to realize control policies aimed at increasing safety, reducing congestion, and dissipate waves.

Collaborative driving results are available for vehicle-level controls and mostly focused on architecture and human-in-the-loop approaches. The research team aims at a macroscopic and network-level approach to exploit the potential impact of collaborative driving. 

The project will propose model and computational tools for collaborative driving at a macroscopic and network-level to exploit its potential for reduction of energy consumption and congestion.]]></description>
      <pubDate>Thu, 01 Apr 2021 19:33:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/1844346</guid>
    </item>
    <item>
      <title>Integrated Corridor Management: Cooperative Signal Control with Freeway Operations and Ramp Metering (Project B4)</title>
      <link>https://rip.trb.org/View/1843137</link>
      <description><![CDATA[Freeways and intersecting arterials often operate without coordination of their operation. However, demand at an on-ramp depends on the discharge of traffic from the upstream interchange or intersection. Innovative signal control strategies can help manage this on-ramp demand and the resulting downstream queues. Similarly, ramp metering strategies have been in place to improve the flow of traffic on freeway facilities. When the traffic congestion on the freeway facility is high, metering rates increase, resulting in longer queues along the on-ramp. Such queues may eventually spill back to the upstream intersection or interchange. When such intersections are along an arterial corridor with high traffic demands, queue spillback from ramps or downstream signals can disrupt operations on the entire facility. One way to remedy the long queues is to flush queued vehicles along on-ramps, which leads to deteriorating traffic performance on the freeway facility. 
There is a possibility to avoid these conditions when the traffic signals at the interchange and arterial corridor leading to it (see Figure 1) are controlled considering freeway operations and work together with the ramp metering signals. The interchange and arterial corridor signals can help ramp metering signals in regulating the flow toward the freeway. It can also avoid wasting green time to the movements entering the ramp when the storage area is full.   Strategies can be implemented such that instead of having a long queue on an on-ramp (or a downstream congested signal) that can spillback to upstream intersections, the queue can be distributed across the arterial corridor. This queue distribution will not only improve traffic performance on the freeway facility, but it can also improve progression on the arterial corridor. 
The main objective of this project is to develop an integrated corridor management tool that cooperatively coordinates the control of the signalized intersections and flow from the on-ramps aiming to reduce congestion along both the freeway facility and the arterial facility in an integrated corridor management (ICM) operation.  This research proposes to develop such a tool and test it for two on-ramps and associated arterial corridors under various operational scenarios to provide guidelines for state DOTs on how to manage traffic congestion on arterial corridors at the presence of on-ramp and/or arterial queue spillback. The tool will be capable of recommending optimal signal timings along the arterial corridor as a function of freeway operations; and cooperative signal timing and ramp metering at the on-ramps (if meters are present). NCSU has developed a theoretical tool for signal timing and traffic metering in urban street networks that will be used in this study as a benchmark. Also UF is currently developing methodologies for the HCM to analyze corridor operations (NCHRP 15-57) considering spillback from freeways into arterials.  We will leverage this work and incorporate the results of this proposed work into the NCHRP 15-57 engine and eventually into the HCS. Another related effort is a current STRIDE project conducted by FIU and UF that is developing a machine learning approach for the selection of signal timing plans.  
]]></description>
      <pubDate>Thu, 25 Mar 2021 20:37:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/1843137</guid>
    </item>
    <item>
      <title>Development and Tech Transfer of an Integrated Robust Traffic State and Parameter Estimation and Adaptive Ramp Metering Control System</title>
      <link>https://rip.trb.org/View/1700595</link>
      <description><![CDATA[The research team proposes a comprehensive effort to resolve several common issues associated with prevailing traffic state estimation algorithms based on discrete-time first-order kinematic wave traffic flow models and to develop an adaptive ramp metering control system based on the improved traffic estimation scheme. The effort is composed of traffic flow model modifications, development of a multi-modal adaptive filtering approach to traffic state and parameter estimation scheme, development of measures to integrate emerging traffic data with conventional fixed-point measurements, development of a measure for on-line estimation of capacity-drop-proportion, development of an adaptive discrete switching feedback controller for ramp metering, and implementations of the proposed schemes in both macroscopic numerical simulation and microscopic traffic simulation platform.]]></description>
      <pubDate>Tue, 05 May 2020 09:14:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1700595</guid>
    </item>
    <item>
      <title>Crash Modification Factors (CMFs) for Intelligent Transportation System (ITS) Applications</title>
      <link>https://rip.trb.org/View/1628621</link>
      <description><![CDATA[It is generally understood that Intelligent Transportation System (ITS) applications, such as variable/dynamic/changeable message signs, closed-circuit television (CCTV) cameras, traffic monitoring stations, ramp meters, and Road Weather Information Systems (RWIS), help manage traffic and improve incident response, thus enhancing roadway safety. However, actual data, specifically crash reduction data resulting from ITS applications, are very limited. Research is needed to develop crash modification factors (CMFs) for the various, typically deployed ITS applications.

OBJECTIVE: The objective of this research was to address a long-standing deficiency in safety related ITS data by developing (1) CMFs for commonly deployed ITS applications, independently and as a part of systems and (2) case studies of safety benefit/cost ratio calculations for such ITS applications. The CMFs shall be suitable for use by safety professionals in their analyses and shall meet at least a CMF Clearinghouse four-star quality rating.
 ]]></description>
      <pubDate>Thu, 06 Jun 2019 19:41:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/1628621</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>Addressing Fidelity Between Meso- and Micro-Simulations to Evaluate Traffic Flows in Multiresolution Modeling</title>
      <link>https://rip.trb.org/View/1465504</link>
      <description><![CDATA[Currently, traffic management strategies such as adaptive control and ramp metering systems go through simulation-based testing of the strategies, before field-testing of hardware/software systems, and implementation and evaluation of the system. Simulation testing have been quite successful for isolated intersections and single intersections, and small networks with 1-3 intersections – where the effect of re-routing due to incidents, major events that result in changes in traffic patterns, have none or only minor impacts on the simulations. For larger networks, when there is both lane based dynamics for intersection control and ramps, and link based dynamics for re-routing, integrated models have lack of fidelity between lane dynamics (microscopic simulations) and link dynamics (macroscopic simulation). Part of the lack of fidelity among the meso- and micro-models is due to scope; dynamic traffic assignment (DTA)-type models usually approximate links and path loads for planning purposes while scope of micro-simulation models is on traffic management through small networks. This project will attempt to develop a meso-type model that will approximate the spatial-temporal traffic patterns of a VISSIM model, a well-known micro-simulation model. In other words, instead of fitting a large DTA model based on fitting flows on a few measured links, we would develop a model, here on referred to Model X, which approximates all the flows of a VISSIM model albeit faster than VISSIM.]]></description>
      <pubDate>Wed, 26 Apr 2017 16:53:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/1465504</guid>
    </item>
    <item>
      <title>Developing and Testing Proactive Signal Control Strategies for Arterial-Freeway Diamond Interchanges</title>
      <link>https://rip.trb.org/View/1465505</link>
      <description><![CDATA[This project proposed to develop a proactive traffic control scheme for diamond interchanges based on the recently developed Microwave Density and Analysis System (MIDAS) framework (a RHODES-type DP with better demand predictions). This project showed each potential interchange phase in the dynamic programming (DP) logic is actually possible paired phases at the individual interchange. 

The MIDAS DP will go through the vast number of possible durations for each of these paired phases (meta-phases), in a computationally efficient manner, and select the durations that optimize jurisdictions objective function, be is minimize delays, minimize stops, or a combination of these objectives. Cycle-free traffic proactive strategies that set phase durations for measured vehicle demand, such as RHODES, and respond well to regular as well as intermittent traffic smoothly without any “transition” issues. In Phase 1 of the project will develop the algorithms and the codes to optimize the durations of phases at the interchange, in response to the traffic demand from upstream intersections and off-ramp, and evaluate those analytically and experimentally using simulation models. In Phase 2 of the project, the project will include adaptive ramp meters for the on-ramps to consider delays on the arterial and the freeway.
]]></description>
      <pubDate>Wed, 26 Apr 2017 16:45:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/1465505</guid>
    </item>
    <item>
      <title>Performance Analysis and Control Design for On-ramp Metering of Active Merging Bottlenecks</title>
      <link>https://rip.trb.org/View/1441909</link>
      <description><![CDATA[The complex interplay among merging, lane-changing, and accelerating behaviors plays an important role in determining the performance of a congested merging area. Especially, once a merging bottleneck is activated, the discharging flow-rate can drop by 10% (about 800 vph on a four-lane freeway); such a capacity drop can lead to excessive traffic queues and stop-and-go traffic patterns and increase fuel consumption and greenhouse gas (GHG) emissions. The objective of this research is to analyze the performance and design the control parameters for both pretimed and traffic-responsive on-ramp metering of congested merging bottlenecks. This research will: (1) quantify the congestion mitigation effects of different ramp metering algorithms at an active merging bottleneck; (2) design control parameters for efficient and robust traffic responsive ramp metering algorithms; (3) identify demand patterns when ramp metering algorithms are effective; and (4) develop a set of simple decision-support tools for ramp metering with both kinematic wave models and microscopic simulations. The research will help Caltrans to make decisions on the necessity, priority, algorithm, and parameter tuning related to ramp metering.  This research will lead to a set of decision tools that can help to answer a series of questions: Is a ramp meter warranted at a location? Which merge areas should be given higher priorities given a limited budget? Should pretimed or traffic responsive metering algorithms be implemented? What kind of control parameters are the best?]]></description>
      <pubDate>Wed, 04 Jan 2017 10:56:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441909</guid>
    </item>
    <item>
      <title>Integrating Meso- and Micro-Simulation Models to Evaluate Traffic Management Strategies - Year 2</title>
      <link>https://rip.trb.org/View/1404677</link>
      <description><![CDATA[Currently, traffic management strategies such as adaptive control and ramp metering systems can be tested in simulation using one of the several of-the-shelf-simulation packages such as VISSIM, CORSIM, AIMSUN, etc. Such models and simulation testing have been quite successful for isolated intersections and single intersections, and small networks with 1-3 intersections. Meso-models that simulate small to large networks, on the other hand, are used mostly at a planning level to evaluate long-term impacts of network wide transportation planning decisions. The integration of micro-and macro- models has been attempted before, but the integration is not as seamless as it should be. Results of a macro model are sent “down” to the micro-model to provide travel demand, usually in a straight-forward manner, but the results of the micro-model are not easily sent “up” to the macro model. The goal of the project is to develop a multi-resolution micro-/meso-simulation platform to test proactive traffic management strategies. In particular, to keep the project scope manageable and limited, we will integrate an easily available micro-simulation model VISSIM, with an open-source mesoscopic simulator being developed at Arizona State University (ASU), DTALite. In Phase 1 (year 1) the project will develop the integrated model referred to as METROSIM (MultirEsolution TRaffic Operations SIMulator) In Phase 2 (year 2) the project will evaluate two DMA/ATDM applications that appear to be useful and promising, both via software simulation and hardware-in-the-loop simulations using METROSIM. 
]]></description>
      <pubDate>Thu, 21 Apr 2016 13:19:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1404677</guid>
    </item>
    <item>
      <title>Distributed Traffic Control for Reduced Fuel Consumption and Travel Time in Transportation Networks </title>
      <link>https://rip.trb.org/View/1371683</link>
      <description><![CDATA[Current technology in traffic control is limited to a centralized approach that has not paid appropriate attention to efficiency of fuel consumption and is subject to the scale of transportation networks. This project proposes a transformative approach to the development of a distributed framework to reduce fuel consumption and travel time through the management of dynamic speed limit signs. The project proposes to integrate the roadway infrastructures equipped with sensing, communication, and parallel computation functionalities in the new traffic control paradigm.

The research approach was built on three essential objectives to establish an energy-efficient traffic control methodology:

·   Implementation of a distributed control framework in large-scale transportation networks

·   Simulation of dynamic traffic flow and performance tracking under implemented control signals using real-time traffic and vehicle data

·   Data analysis and sustained strategy improvement

Going beyond the existing distributed architectures where precise dynamic flow models and fuel consumptions have not been considered, the work generated traffic control strategies to realize real-time, macroscopic-level traffic regulation with high precision.

Simulation results demonstrated reduced fuel consumption and alleviated traffic congestion. The feasibility of the proposed optimization method was verified through Vissim simulation that considered different traffic volumes and random seed parameters.]]></description>
      <pubDate>Wed, 14 Oct 2015 12:48:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/1371683</guid>
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