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    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMTYiIC8+PC9wYXJhbXM+PGZpbHRlcnM+PGZpbHRlciBmaWVsZD0iaW5kZXh0ZXJtcyIgdmFsdWU9IiZxdW90O1RpbWluZyZxdW90OyIgb3JpZ2luYWxfdmFsdWU9IiZxdW90O1RpbWluZyZxdW90OyIgLz48L2ZpbHRlcnM+PHJhbmdlcyAvPjxzb3J0cz48c29ydCBmaWVsZD0icHVibGlzaGVkIiBvcmRlcj0iZGVzYyIgLz48L3NvcnRzPjxwZXJzaXN0cz48cGVyc2lzdCBuYW1lPSJyYW5nZXR5cGUiIHZhbHVlPSJwdWJsaXNoZWRkYXRlIiAvPjwvcGVyc2lzdHM+PC9zZWFyY2g+" 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>
    </image>
    <item>
      <title>Enhancing Traffic Signal Controller Performance using LiDAR data.</title>
      <link>https://rip.trb.org/View/2742142</link>
      <description><![CDATA[Enhancing Traffic Signal Controller Performance Using LiDAR Data applies software-in-the-loop testing to a previously developed approach for optimizing traffic signal timings to reduce vehicle delays and increase throughput at signalized intersections, serving as a first step prior to field deployment. Field data will be gathered at a single signalized intersection using LiDAR equipment to investigate the potential of LiDAR data for the field evaluation of traffic signal controllers.

Using the field data, optimized signal timings will be computed and implemented in a simulation environment along a segment of a major arterial. Conducted in collaboration with the Virginia Department of Transportation (VDOT), the study builds on the team’s prior work demonstrating that traditional methods such as the Webster formulation overestimate cycle lengths and fail to minimize delay under congested conditions, and applies a new Laguna-Du-Rakha (LDR) formulation that minimizes delay while reducing stops, deceleration, and acceleration at signalized intersections.

The project will collect LiDAR field data at the signalized intersection of Cloverdale Road and Lee Highway to evaluate the suitability of these data for the field evaluation of signal control strategies. The team will compute optimum cycle lengths using the LDR formulae, extract vehicle trajectory data for the computation of queue lengths, delays, stops, and fuel and energy consumption, and construct and calibrate a simulation network of the intersection. Four signal timing plans, fixed-time and actuated control based on both the Webster and LDR methods, will be implemented and evaluated across ten traffic demand levels, with emphasis on high-demand conditions where the LDR formulation provides the greatest benefit. Pedestrian data will also be collected and incorporated.]]></description>
      <pubDate>Sat, 01 Aug 2026 09:50:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2742142</guid>
    </item>
    <item>
      <title>Portable Tool for Periodic Evaluations of Intersection Signal Timings</title>
      <link>https://rip.trb.org/View/2725460</link>
      <description><![CDATA[The safety and efficiency of traffic-signal-controlled intersections rely on having appropriate timing signals for intersection users. Yellow, all-red, and crosswalk timings that are too low for users create the potential for intersection conflicts. Similarly, effective green times that are too small for volumes create long queues and congestion. However, signal timings are typically only evaluated every 2-5 years when signals are retimed through an often time-consuming process. The proposed solution is a portable device containing low-cost off-the-shelf radar and camera sensors that will record the trajectories of intersection users differentiating between pedestrians, bicycles and vehicles.]]></description>
      <pubDate>Wed, 08 Jul 2026 16:36:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/2725460</guid>
    </item>
    <item>
      <title>Guidance for Selecting Pedestrian Safety Treatments at Signalized Intersections to Address Permitted Turn Conflicts</title>
      <link>https://rip.trb.org/View/2712202</link>
      <description><![CDATA[State departments of transportation (DOTs) and local agencies work to improve pedestrian safety at signalized intersections while maintaining efficient vehicle operations. Traditional signal timing practices often allow pedestrians to cross concurrently with permitted turning vehicles, which can create unsafe or stressful conditions for pedestrians, particularly at intersections with high turning volumes and speed or complex geometries. Agencies have implemented treatments such as leading pedestrian intervals (LPIs), delayed-turn strategies, and protected-only turn phases, but these applications are often applied without nationally consistent, data-driven guidance.

Existing resources identify available pedestrian safety treatments but provide limited guidance on when specific strategies are most appropriate. This can lead to inconsistent practices and difficulty balancing pedestrian safety improvements with operational impacts to vehicles.

The objective of this research is to develop a data-driven guide for selecting pedestrian safety treatments at signalized intersections to address conflicts with permitted turning vehicles. Using field-collected data, the research will evaluate treatments under varying traffic, geometric, and signal timing conditions, with results to help agencies identify appropriate strategies.]]></description>
      <pubDate>Wed, 10 Jun 2026 11:11:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2712202</guid>
    </item>
    <item>
      <title>Optimizing Signal Timing Through New Technologies</title>
      <link>https://rip.trb.org/View/2640688</link>
      <description><![CDATA[Traditional signal timing optimization is time consuming and requires engineering expertise, often resulting in long delays between optimization cycles. New technologies could provide an opportunity to make the process more efficient by early identification of locations where reoccurring congestion is occurring.  The objectives of this research project are to do a detailed feasibility study of technologies that can aid in identifying locations where current signal timing is causing delays and a process document for implementation of the technology.]]></description>
      <pubDate>Tue, 16 Dec 2025 09:06:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640688</guid>
    </item>
    <item>
      <title>AI Powered Conflict Detection and Signal Optimization for Right Turn FYAs in Mixed Modal Intersections</title>
      <link>https://rip.trb.org/View/2640185</link>
      <description><![CDATA[Right turn Flashing Yellow Arrows (FYAs) can support efficient traffic movement, but they also introduce uncertainty for drivers who must judge when to yield to pedestrians and cyclists. This uncertainty can increase the number of near miss interactions at mixed modal intersections. This project will create an artificial intelligence framework that uses video based detection to monitor turning vehicles, pedestrians, and cyclists in real time. The system will compute surrogate safety measures such as post encroachment time and time to collision to identify conditions that may increase the likelihood of a conflict.

The project will use these safety measures to support a signal timing optimization engine that balances safety with delay reduction. The research team will test the framework in simulation and explore opportunities for pilot deployment with the Connecticut Department of Transportation. The resulting tools will give agencies a practical method to assess right turn FYA performance, adjust timing plans when needed, and improve intersection safety through proactive conflict identification.]]></description>
      <pubDate>Thu, 11 Dec 2025 13:35:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/2640185</guid>
    </item>
    <item>
      <title>Sequencing for Phases with Flashing Yellow Arrow</title>
      <link>https://rip.trb.org/View/2608463</link>
      <description><![CDATA[When the Utah Department of Transportation (UDOT) first implemented flashing yellow arrows (FYA) for left-turn phasing, high crash rates were observed with lagging FYA operations. As a result, current UDOT policy for FYA operations for protected/permitted left turn phasing is to not “lag,” meaning to allow the protected left turn phase to follow the opposing through movement, due to a “perceived yellow trap.”

The purpose of this research is to evaluate current UDOT policies on leading/lagging left turn sequencing to determine if more flexibility could be provided, while still maintaining an acceptable level of safety. This will include reviewing the operation of FYA signal heads in other states, along with reviewing potential driver behaviors leading to the “perceived yellow trap.” The research will compare UDOT policies with other state DOT policies on leading/lagging left turns with FYA. Design and hardware factors will also be analyzed for safety impacts.
]]></description>
      <pubDate>Mon, 13 Oct 2025 18:57:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2608463</guid>
    </item>
    <item>
      <title>Impact of Leading Pedestrian Intervals on All Users</title>
      <link>https://rip.trb.org/View/2608462</link>
      <description><![CDATA[A leading pedestrian interval (LPI) refers to a traffic signal phase wherein pedestrians receive the right-of-way prior to vehicular movements that are required to yield. During the remainder of the pedestrian phase, both vehicle and pedestrian movements may occur simultaneously. The Utah Department of Transportation (UDOT) signal timing team regularly receives requests to implement LPIs, which are traditionally considered straightforward measures to enhance pedestrian safety at intersections. Nonetheless, UDOT has encountered varying research findings regarding LPIs, with some studies highlighting potential safety concerns. As a result, UDOT remains cautious about widespread LPI implementation. According to the Federal Highway Administration (FHWA), theoretical benefits of LPIs include improved visibility for crossing pedestrians, fewer conflicts between vehicles and pedestrians, and increased motorist yielding. However, potential drawbacks include the possibility of increased pedestrian-vehicle interactions, necessary restrictions on right turn on red (RTOR), reduced green time for vehicles, decreased operational efficiency, and greater complexity in signal timing. The primary concern is the risk of conflicts between right-turning vehicles and pedestrians, particularly regarding the need for "No Right Turn on Red" (NRTOR) restrictions when LPIs are implemented. UDOT is also interested in evaluating compliance with NRTOR controls.
The purpose of this research is to assess LPI installations within Utah through a before-and-after analysis. The outcomes will inform the development of formal departmental guidance for future LPI implementations, addressing the current absence of documented procedures due to inconclusive evidence on the efficacy of LPIs.
]]></description>
      <pubDate>Mon, 13 Oct 2025 17:38:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2608462</guid>
    </item>
    <item>
      <title>Field Deployment and Testing of Enhanced Fixed- and Actuated-Traffic Signal Control Systems</title>
      <link>https://rip.trb.org/View/2606409</link>
      <description><![CDATA[This research conducts field deployment and testing of enhanced traffic signal control systems using the Laguna-Du-Rakha formulation to optimize signal timings for reduced vehicle delays and fuel consumption at signalized intersections. Building on previous work demonstrating that traditional Webster formulation methods produce cycle lengths nearly three times longer than optimal under congested conditions, the study implements and validates improved signal timing approaches through real-world field testing in collaboration with Virginia Department of Transportation. The methodology involves identifying candidate intersections in the Blacksburg and Salem area, with primary focus on the Beamer Way and Southgate Drive intersection equipped with LiDAR surveillance instrumentation tracking objects within 150 meters. Optimized cycle lengths will be calculated using multi-objective optimization balancing delay minimization and fuel consumption reduction through adjustable weighting factors. Field implementation includes one-week deployment of optimized signal timing plans with LiDAR-based trajectory data collection for performance quantification including queue lengths, vehicle delays, stops, and fuel consumption measurements. VISSIM microsimulation modeling creates digital twins of selected intersections for validation against field data and sensitivity testing across various traffic demand levels and cycle length weight combinations, enabling assessment beyond observed field conditions and identification of optimal control strategies.]]></description>
      <pubDate>Thu, 02 Oct 2025 15:18:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2606409</guid>
    </item>
    <item>
      <title>Research Project Name: Development of a CAV Testbed-enhanced Smart Campus at Morgan State University - Phase III</title>
      <link>https://rip.trb.org/View/2606401</link>
      <description><![CDATA[This research advances Connected and Automated Vehicle (CAV) infrastructure through Phase III expansion of an established testbed, integrating LiDAR-powered safety applications with signal control systems and conducting comprehensive CAV market penetration analysis in partnership with Maryland Department of Transportation. Building on previous phases, the study coordinates signal phasing and timing across three campus intersections equipped with LiDAR and roadside unit infrastructure, implementing dynamic all-red extensions based on vehicle speed and red-light violation risk detection. The methodology develops pedestrian signal extensions activated by real-time crosswalk occupancy detection and creates Safety Data Sharing Messages compliant with SAE J2735 standards for broadcasting object-level data to vehicles. Portable LiDAR deployments collect trajectory data at additional intersections and work zones for solution validation. The market penetration analysis component catalogues CAV data sources, develops quality assurance frameworks, and compares traditional probe data with connected vehicle information. Collaboration with Maryland Motor Vehicle Administration provides vehicle registration cross-referencing with automation levels, while commercial vendor partnerships supply dynamic usage patterns. The research creates geographic information system (GIS)-based visualizations representing regional CAV penetration and develops interactive dashboards for transportation planning support.]]></description>
      <pubDate>Thu, 02 Oct 2025 14:53:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2606401</guid>
    </item>
    <item>
      <title>SPR-5018: Connected Freeway and Signalized Corridor Pilot: C-V2X Technologies Deployment for Enhanced Safety and Efficiency in Indiana</title>
      <link>https://rip.trb.org/View/2590602</link>
      <description><![CDATA[This project will deliver a field-tested pilot deployment of C-V2X technologies along two critical corridors in Columbus, Indiana, supported by vehicle demonstrations and real-world data collection. By integrating physical and virtual roadside units, developing Signal Phase and Timing (SPaT) based CAV applications such as trucking ecoapproach and departure and extended green functionality, emergency vehicle pre-emption, and validating Rampcast for freeway ramps, the study will generate actionable insights for Indiana Department of Transportation (INDOT) on deployment strategies, performance metrics, and scalability. A Purdue-led multidisciplinary team will carry out the proposed work in collaboration with INDOT and industry partners. Outcomes will inform statewide infrastructure planning and accelerate Indiana’s readiness for CAV technologies.]]></description>
      <pubDate>Tue, 19 Aug 2025 15:00:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2590602</guid>
    </item>
    <item>
      <title>Automatic Signal Retiming Using Vehicular Trajectory Data</title>
      <link>https://rip.trb.org/View/2562295</link>
      <description><![CDATA[Traffic signal optimization is a cost-effective method for reducing congestion and energy consumption in urban areas. However,
due to the high installation and maintenance costs of detection systems, most intersections are controlled by fixed-time traffic
signals that rely on manual data collection and are not regularly optimized. More cost-effective methods for signal optimization
need to be explored, such as the use of vehicle trajectory data that is now available. Research is needed to determine if this
process can provide optimized timings at more frequent and regular intervals, yielding better overall signal performance.]]></description>
      <pubDate>Fri, 06 Jun 2025 15:12:39 GMT</pubDate>
      <guid>https://rip.trb.org/View/2562295</guid>
    </item>
    <item>
      <title>Innovative Signal Timing Design and Operation Strategies to Improve Nighttime Arterial Safety</title>
      <link>https://rip.trb.org/View/2536079</link>
      <description><![CDATA[Nighttime fatalities, injuries, and crashes are overrepresented in Florida. To significantly reduce these incidents, greater efforts must be invested to make nighttime travel safer for all road users. This research will investigate innovative traffic signal timing design and operation strategies and their effectiveness in mitigating nighttime fatalities, serious injuries, and crashes on urban and suburban arterials in Florida.]]></description>
      <pubDate>Tue, 08 Apr 2025 12:57:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2536079</guid>
    </item>
    <item>
      <title>Development of a Scalable, Low-Cost, Environmentally-Friendly Adaptive Traffic Signal Control (SLE-ATSC) System</title>
      <link>https://rip.trb.org/View/2495005</link>
      <description><![CDATA[As an enhanced method for vehicle detection at signalized intersections, it is possible to use vehicle-probe data from smartphones, Global Navigation Satellite System (GNSS) receivers, and other types of mobile devices to complement existing traffic sensing and signal control, resulting in lower energy consumption. Using these additional data, it is now possible to estimate reliable traffic queue lengths at high-density traffic intersections. Given real-time reliable traffic queue lengths, it is possible then to dynamically adjust the signal phase and timing of an intersection, with the goal of minimizing traffic queues, waiting times, and energy use. Using UC Riverside’s Innovation Corridor as a target arterial roadway, the research team will develop a scalable, low-cost, environmentally-friendly adaptive traffic signal control (SLE-ATSC) system based on receiving real-time traffic data from sources such as TomTom and INRIX. The signal control system will be implemented for several of the key intersections along the corridor, using a calibrated state-of-the-art traffic simulation platform. Various metrics will be evaluated, comparing the existing traffic signal phase and timing to the new dynamic signal phase and timing resulting from the adaptive signal control system. Using the calibrated simulation model, traffic system metrics will be estimated. In addition, part of the research team (TSU) will utilize their driving simulators as part of a “Hardware-in- the-Loop” testing system for the proposed adaptive traffic signal control system. The traffic simulation model developed at UCR will interface directly with the TSU driving simulators, allowing the research team to see more realistic driving behavior operating in the simulation platform. This will provide more realistic measures of the overall system performance, with a focus on safety, mobility, and environmental metrics.]]></description>
      <pubDate>Fri, 31 Jan 2025 16:35:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2495005</guid>
    </item>
    <item>
      <title>Safety Impacts of Signal System Retiming to Improve Progression</title>
      <link>https://rip.trb.org/View/2494743</link>
      <description><![CDATA[North Carolina Department of Transportation (NCDOT) owns and maintains coordinated traffic signal systems throughout the state in primarily rural and suburban areas. NCDOT’s Signal System Timing and Operations office assists the local Divisions with the signal system retiming program to update traffic signal settings of existing coordinated corridors. This program has primarily focused on identifying locations with the input of Division Engineers and operational summary data to prioritize the corridors updated each year.

To date, with the ability of signalized intersections to manage vehicle and multimodal conflicts, the crash rate has been significantly reduced compared to the past. However, as traffic volume continuously increases, drivers who arrive at a signal at the end of the green period are very likely to speed up to proceed to the intersection. This yields crash hotspots at signalized intersections, which could increase if traffic is not able to progress
smoothly. According to the Federal Highway Administration (FHWA, 2023), about one-third of crashes occurred at signalized intersections, among which rear-end crashes and right-angle crashes are the most common types. Therefore, minimizing the safety risk at signalized intersections has been an important issue for DOTs to address in the last century, with many potential treatments depending on the issues identified.

In recent decades, signal coordination has been utilized as a method to effectively improve the performance of the traffic control system, especially in high density urban areas. It has been widely used as a measure to mitigate congestion, reduce travel time, and eliminate travel delays. On the other hand, however, it may change the traffic flow feature at intersections, which could lead to potential safety issues. As signal coordination has been extensively implemented into urban signalized arterials, safety concerns were unsurprisingly raised by both transportation engineers and the public. Since traffic coordination may result in higher mainline speeds than non-coordinated conditions, most of these opinions came up with the worries that a higher speed may increase the risk of being involved in a traffic crash, particularly injury or fatal crashes. Inversely, improved progression of traffic may reduce the total crash count by reducing rear end collisions that can occur in start-stop traffic. To date, there is neither solid  theoretical-level models to analyze this issue, nor solid evidence from the field to support the concern. In this regard, this research effort aims to assess the effects of traffic signal coordination on the safety performance of North Carolina coordinated arterials. The research is anticipated to develop predictive model(s) that can estimate or predict crashes based on the operational or site characteristics of North Carolina signalized corridors. ]]></description>
      <pubDate>Tue, 21 Jan 2025 10:22:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2494743</guid>
    </item>
    <item>
      <title>Automatic Signal Retiming for Large Scale Networks with Vehicle Trajectory Data</title>
      <link>https://rip.trb.org/View/2425176</link>
      <description><![CDATA[Traffic signal optimization is known to be a cost-effective method for reducing congestion and energy consumption in urban areas without changing physical road infrastructure. However, due to the high installation and maintenance costs of detection systems, most intersections in practice are controlled by fixed-time traffic signals that rely on manual data collection and are not regularly optimized. Readily available vehicle trajectory data offers unprecedented opportunities for a more efficient use of existing infrastructure and resources. The recently developed OSaaS (Optimizing Signals as a Service) system uses vehicle trajectory data as the only input to optimize traffic signals. OSaaS allows us to easily monitor traffic performance, diagnose signal timing issues, and optimize signal timing parameters. However, to put OSaaS into practice, an automated process needs to be developed so that manual effort can be minimized. For example, traffic flow parameters such as saturation flow rate and free-flow speed can be calibrated automatically by using historical vehicle trajectory data. Therefore, the project will further develop OSaaS into a data-driven automatic signal retiming system that will update signal timing parameters for fixed-time and coordinated-actuated signalized intersections on an iterative basis (i.e., bi-weekly, monthly).]]></description>
      <pubDate>Wed, 04 Sep 2024 17:22:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/2425176</guid>
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