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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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    <item>
      <title>Integration of a Real-time Traffic State Estimation and a Decentralized Game-Theoretic Traffic Signal Controller</title>
      <link>https://rip.trb.org/View/2447006</link>
      <description><![CDATA[This project proposes to enhance a decentralized traffic signal controller based on a Nash Bargaining game-theoretic framework, integrating a Kalman filtering (KF) algorithm for real-time traffic state estimation. By combining KF with the traffic signal controller, the project aims to optimize signal phasing sequences at intersections based on turning movements and traffic density, thereby reducing queue lengths and delays. The approach involves traffic data collection through loop detectors and probe vehicle data, and it will address saturation flow rates for shared lanes. This integration intends to achieve efficient system performance across varying probe vehicle market penetration levels, ultimately providing a robust solution for improved traffic flow and reduced environmental impact at intersections.]]></description>
      <pubDate>Wed, 30 Oct 2024 14:41:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2447006</guid>
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    <item>
      <title>BikePed Portal: Pedestrian Volume Estimation Based on Push Button Actuations from Signals Data</title>
      <link>https://rip.trb.org/View/2361978</link>
      <description><![CDATA[This project translates research from Oregon DOT's "Active transportation counts from existing on-street signal and detection infrastructure" (SPR 857), into a practical application on BikePed Portal. ]]></description>
      <pubDate>Tue, 02 Apr 2024 13:42:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2361978</guid>
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      <title>Evaluation of the Traffic Signal Timing Manual, Third Edition</title>
      <link>https://rip.trb.org/View/1957089</link>
      <description><![CDATA[The Federal Highway Administration (FHWA) Traffic Signal Timing Manual (STM) has been the most widely accepted reference across the traffic signal timing field. Since the release of the second edition in 2015 (STMv2), there have been significant advances in signal timing research and practices, and several NCHRP and FHWA initiatives have been implemented. Major industry references and standards have been updated with new computational methods and operational practices incorporated. New technological trends are emerging, such as applying new computational approaches to the signal timing process, developing signal timing plans using novel datasets, and implementing new signal timing paradigms for connected and autonomous vehicles (CAV) and connected intersections. The traffic signal timing community has highlighted important topics to be addressed in a new version of the STM, including the signal timing of unconventional intersection geometries; advanced bicycle, pedestrian, and transit signal timing; cybersecurity risks tied to the signal timing procedures; and innovative signal timing design using standards-based controller features.

The STM has served as a primary reference for the FHWA Traffic Signal Timing Concepts course. The course presents a signal timing workflow that starts with goals, explores context with a focus on vehicle flow, and then selects strategies and tactics that support attainment of objectives.  It is envisioned that an update to the STM’s structure could better support this workflow, inclusive of performance measurement to validate objectives and demonstrate progress towards goals and enhance the coverage of pedestrians, bicycles, transit, Complete Streets, safety, and equity. The update should consider how signal timing fits in with the overall traffic signal program, as other elements within the program (e.g., maintenance, equipment health) may directly impact the success of signal timing activities.

The objective of this research is to provide guidance on utilizing up-to-date effective practices and research outcomes that have been successfully implemented after STMv2.]]></description>
      <pubDate>Thu, 26 May 2022 16:54:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/1957089</guid>
    </item>
    <item>
      <title>SPR-4548: Traffic Signal Detection Systems INDOT Evaluations</title>
      <link>https://rip.trb.org/View/1758176</link>
      <description><![CDATA[The Indiana Department of Transportation (INDOT) continues to evaluate new products for vehicle detection at traffic signals. Accurate and low-latency vehicle detections are central to ensuring efficient and safe operations at actuated traffic signals. New products in this field become available on a regular basis. Having additional detection technologies available aids INDOT in finding the most cost-effective system for given site constraints. This project will evaluate the performance of up to three new vehicle detection systems and compare their results to INDOT’s established standards.]]></description>
      <pubDate>Thu, 17 Dec 2020 13:19:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1758176</guid>
    </item>
    <item>
      <title>Green traffic controller cabinet</title>
      <link>https://rip.trb.org/View/1700471</link>
      <description><![CDATA[The objective of the program is to reduce the power consumption of NYC traffic control equipment and to improve the quality of the intersection operation monitoring such that it can provide more reliable and sustainable operation. It is estimated that the power consumption of the intersection – which includes the signal heads and the controller and cabinet could be reduced from 30-50% which could result in operational savings of more than $1M per year and a reduction of more than 10 MWh per year in power consumption. However, to take advantage of these types of savings, the cabinet design must be altered to use lower power devices and improved monitoring. In addition, with the available LED signal heads, it is now possible to consider an entire intersection design that operates at 48 Volts or less – which is more typical of the telephone line operation – and hence can be serviced by technicians which has the potential to make repairs more efficient since the same staff that troubleshoot the electronic equipment can now service the traffic controllers.TransCore will work with the New York City DOT and one or more vendors and the standards development organizations to develop and deploy a “green” traffic controller which can operate at lower voltages (below 50 volts), support lower power signal heads, integrate more comprehensive monitoring, and eliminate the need for forced ventilation. The net effect should be lower costs of operation, a much smaller cabinet, and lower power consumption for the entire intersection. Further, it could reduce the overall cost of maintenance by allowing
signal technicians, rather than electricians to perform most conventional high-tech
maintenance since there will be no line voltage in the cabinet or field wiring. This could produce a compact, safer, and greener cabinet. The project will proceed through with the procurement of 5 sample cabinets from each of 2
suppliers to verify both the procurement specification and the interchangeability of the major subassemblies. The cabinets will consider the communications now in use (NYCWiN) and the future (fiber) and support such additional features as digital CCTV, network devices, and video analytics. Further, this cabinet is expected to support the deployment of the connected vehicle technology as described by the AASHTO Footprint analysis and guidelines to prepare for the next generation connected vehicle development.]]></description>
      <pubDate>Wed, 22 Apr 2020 14:33:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/1700471</guid>
    </item>
    <item>
      <title>Uncertainty Quantification of Cyber Attacks at Intelligent Traffic Signals</title>
      <link>https://rip.trb.org/View/1575260</link>
      <description><![CDATA[Description: The primary goal for the project is to develop, and validate detection models for system control failures involving connected vehicle applications. The secondary goal is to establish long-term collaborative research between the C2M2 partners and Benedict College to provide re-search and career opportunities for underrepresented minority students. To achieve these goals, the following objectives are identified: We anticipate the proposed research will lead to significant levels of collaborative research, including large multi-institutional grants that will be needed to help the state of South Carolina become the ‘silicon valley’ of the South East in vehicular and manufacturing technology. 

Intellectual Merit: (1) Develop an appropriate system model representation, including a characterization of a set of anomalies; (2) Develop predictive methods and training sets such that anomalies can be classified quickly by vehicles or edge nodes; and (3) Create a working group of interested faculty and students at participating universities to engage undergraduate students in educational activities that are synergistic and supportive of the proposed projects goals and objectives. 

Broader Impacts: The models developed in this proposed research can be extended to autonomous vehicles, different traffic systems as well as complexity of these systems. Although signalized networks are focused in this project, any other CV application can be analyzed similarly: vulnerabilities can be identified and detection tools/sensors can be deployed for a reliable application.]]></description>
      <pubDate>Tue, 18 Dec 2018 11:51:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/1575260</guid>
    </item>
    <item>
      <title>Testing MS Sedco INTERSECTOR Radar Detectors for Car/Bike Differentiation</title>
      <link>https://rip.trb.org/View/1441872</link>
      <description><![CDATA[The California Vehicle Code (CVC) 21450.5, effective January 1, 2008, states that bicycles must be detected at new or modified traffic actuated signals, or else the traffic signal must be set to vehicle recall for all phases without bicycle detection.  The Traffic Operations Policy Directive 09-06 and subsequent implementation memo mandate that bicycles must be detected and given extra initial green time if present, or else the traffic signal must be set to always give an initial green time sufficient for bicycle passage.  Therefore, the California Department of Transportation's (Caltrans’) Division of Traffic Operations is searching for technology capable of detecting both vehicles and bicycles as well as distinguishing between them.  Caltrans currently uses inductive loop detectors almost exclusively, but they cannot distinguish between bicycles and vehicles.  Using an off-pavement detection technology such as radar that can distinguish between them would allow Caltrans to only give additional initial green time to bicycles when detected.   Use of off-pavement detection technology would also help to responsibly manage California’s transportation assets through preservation of funding and environmental resources.  The lifetime cost of radar detection, including procurement, installation and maintenance, is less than that of loop detectors.  Pavement integrity would be preserved by eliminating loop cutting, which would reduce the need for congestion-causing lane closures during detector installation and maintenance.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:55:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441872</guid>
    </item>
    <item>
      <title>Signal Phase and Timing and Related Messages for Connected Vehicle Applications
</title>
      <link>https://rip.trb.org/View/1367008</link>
      <description><![CDATA[This project is to identify the necessary interfaces for two-way communication of traffic signal information between the traffic signal controller and a mobile device, provide the concept of operations for the use of the interfaces, and develop prototypes of the interfaces using signal controllers from two different manufacturers. The interfaces and prototypes shall be for use by the connected vehicle applications that require signal phase and timing (SPaT) and its related messages.
]]></description>
      <pubDate>Thu, 27 Aug 2015 15:58:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/1367008</guid>
    </item>
    <item>
      <title>Mathematical Analysis of the Empirical Mode Decomposition

</title>
      <link>https://rip.trb.org/View/1366735</link>
      <description><![CDATA[This study consists of two broad fronts of studies: to improve the presently available Empirical Mode Decomposition algorithms and to establish a rigorous mathematical foundation for the generalized adaptive data analysis methodology. The success of the first research area will enhance immediate improvement of information management in a complex or significantly rich signal data system, such as the Integrated Safety System being considered by the Federal Highway Administration or for full-scale traffic control systems. The success of the second research area would enable drastic improvement of robustness and reliability of the algorithm and guarantees its further applications.
]]></description>
      <pubDate>Mon, 24 Aug 2015 15:02:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/1366735</guid>
    </item>
    <item>
      <title>Smart Bus System under Connected Vehicles Environment</title>
      <link>https://rip.trb.org/View/1353743</link>
      <description><![CDATA[This research proposes Smart Bus System (SBS) powered by bus-to-devices wireless communications technology including, but not limited to, 3G, 4G/LTE, Wi-Fi, Dedicated Short Range Communications (DSRC), and Bluetooth. SBS is an innovative urban bus operation system integrated with Information Technology (IT) to enhance the efficiency of bus operation, to encourage bus ridership, and to improve the mobility and sustainability of urban transportation. SBS enables 1) a bus to take a shorter path to catch up the schedule when it is behind the schedule and no passengers need to get off or get on and 2) passengers to send a hold request so that the next transfer bus, if at all possible, waits for the transfer passenger. The proposed project will be initially conducted within a simulation environment realizing actual hardware devices such as traffic signal controller, mobile devices (e.g., smartphone, tablet PC), and virtual transit management center. The goal of this project is to demonstrate that the proposed innovative Smart Bus System can improve transit system reliability and increases ridership. The increased bus ridership likely decreases the number of passenger cars on roadway, thereby resulting in the improvement on mobility and air quality and fuel consumption. Thus, the potential benefits of the smart bus system will be gained from the aspects of both mobility and environment.]]></description>
      <pubDate>Fri, 15 May 2015 01:00:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/1353743</guid>
    </item>
    <item>
      <title>Development of a New Connected Eco-Driving Technology at Signalized Intersections with Adaptive Signal</title>
      <link>https://rip.trb.org/View/1346331</link>
      <description><![CDATA[The advances of wireless communication and information technology have enabled the technological foundation and provided an unprecedented data-rich environment known as "big data". One emerging transformative technological initiative is Connected Vehicle, which aims to enable networked wireless communications among vehicles, infrastructure and passengers' personal devices. The proposed research aims to develop a new connected vehicle technology that enables eco-driving of vehicles at signalized intersections where adaptive control is instrumented. The work capitalizes on the emerging advanced technologies including Connected Vehicle, Adaptive Traffic Signal Control, and Big Data Analytics. The outcome includes smoother vehicle movement trajectories, reduced fuel consumption and green-house gas emissions, hence system-wide better mobility, efficiency and environmental benefits. The proposed work is extremely timely and significantly different from other on-going connected vehicle research, in that it aims to integrate the developed technology with New York City's real-time adaptive control system, applying big-data analytics on the already available big traffic data. Mostly notably, New York City's big traffic data environment include millions of records of per-trip travel times from 8 million daily commuters, volumes and occupancies from a wireless sensor network, and detailed historical and real-time controller status data for more than 10,000 ASTC controllers. One of the team members, namely, KLD is the developer of New York City's adaptive control system. This enables the proposed work as an innovative solution providing practical and workable contributions to New York's transportation community.  The proposed research involves developing the following methodologies and evaluating them using microscopic traffic simulation:  * Data fusion of real-time large-scale multi-source traffic, vehicle and environmental data. The data includes traffic conditions, network-wide signal operational status, real-time adaptive signal timing information, registered Transit Priority Preemption Request, vehicle dynamics and engine economy data. The sources of the data include ITS roadway sensors, Electronic Toll Collection (ETC) tag readers, connected vehicle equipment's and central adaptive signal control systems at Traffic Management Center.  * Big Data Analytics to synthetize the data and evaluate traffic and environmental parameters and develop operational strategies for individual vehicles at signalized intersections, focusing on smoother vehicle trajectories, and reducing real-time fuel consumption and emissions.  * Connected Eco-Driving. By virtue of V2I and V2V, real-time adaptive signal timing data (and relevant transit signal priority request, if any) from the central TMC are synthesized with vehicles mechanical dynamics and engine-economy status. These data are analyzed to generate customized driving advice to drivers so that they can adjust their driving behavior for a smoother movement trajectory, save fuel and reduce emissions, while clearing the intersection safely and efficiently.  * Test the methodologies through rigorous microscopic traffic simulation, explore the feasibility of a commercializable system prototype, and outline steps to the implementation of such a prototype.]]></description>
      <pubDate>Tue, 17 Mar 2015 01:00:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/1346331</guid>
    </item>
    <item>
      <title>Evaluation of Transit Signal Priority Strategies Through Microsimulation</title>
      <link>https://rip.trb.org/View/1341471</link>
      <description><![CDATA[The District of Columbia Department of Transportation (DDOT) is planning and designing a transit signal priority system (TSP) at over 100 signalized intersections where a majority of the intersections are located within the downtown core area. This will be the first major TSP implementation in an urbanized and grid system. This project will develop a microsimulation model of a portion of the study area to assess, test, and refine TSP strategies with DDOT's traffic signal controller logic.]]></description>
      <pubDate>Sat, 24 Jan 2015 01:00:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/1341471</guid>
    </item>
    <item>
      <title>Heavy Vehicle Safety at Traffic Signals (Phase A)</title>
      <link>https://rip.trb.org/View/1233054</link>
      <description><![CDATA[This project will develop new traffic signal control logic to improve the safety of heavy vehicles on high speed approaches to signalized intersections using wireless communication between a heavy vehicle and a roadside traffic signal controller. The project will build on the Trusted Truck™ onboard computer system using the Vehicle Infrastructure Integration (VII) concept for deployment of communication technology between vehicles and roadside infrastructure. This technology for heavy vehicles can also be migrated to emergency responders.]]></description>
      <pubDate>Thu, 03 Jan 2013 14:50:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/1233054</guid>
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