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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>Using Connected Intelligent Transportation to Enhance Vulnerable Road User Safety: Phase II Real-world Testing and Deployment</title>
      <link>https://rip.trb.org/View/2425409</link>
      <description><![CDATA[As the development of Connected and Autonomous Vehicles (CAVs) becomes increasingly common on our roads, it is crucial to focus on the safety and equitable treatment of Vulnerable Road Users (VRUs). Building upon last year's development of a human-in-the-loop digital twin system, this project enters Phase II, transitioning to real-world applications by developing a hardware-in-the-loop system for real-world testing and deployment. By utilizing the lab-developed CAV fleet and an array of edge computing devices, including 4D cameras and edge computers, coupled with data fusion algorithms, the objective is to refine, test, and deploy a framework that significantly enhances the interactions between CAVs and VRUs. Central to this initiative is the commitment to ensuring equitable access and safety for all road users, addressing the unique vulnerabilities of VRUs. This phase involves developing advanced data structures for efficient data management, deploying edge computing infrastructure for minimized response times, and creating custom algorithms for real-time data analysis. Executing real-world demonstrations on controllable test tracks, and potentially extending these tests to live urban environments such as Park Street, Madison, WI, will allow the research team to validate and exhibit the framework's capacity for enhancing decision-making and ensuring both safety and equity in real traffic conditions.]]></description>
      <pubDate>Thu, 05 Sep 2024 17:09:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2425409</guid>
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    <item>
      <title>Implementing the ATSPM-In-The-Loop Simulation Solution with the TxDOT State-Wide ATSPM System Deployment Plan</title>
      <link>https://rip.trb.org/View/2420080</link>
      <description><![CDATA[This project will introduce automated traffic signal performance measures or ATSPM systems to all stages of traffic signal projects in Texas. The benefits of ATSPM systems have been broadly recognized by agencies. Texas Department of Transportation (TxDOT) is also in the process of state-wide ATSPM deployment. Nonetheless, the ATSPM system is poised to evaluate the traffic signal data generated by controllers. Therefore, access to the real ATSPM systems is limited to a small portion of traffic signal stakeholders, and these stakeholders may not take advantage of ATSPM during traffic signal planning and design due to a lack of data. In a research project sponsored by TxDOT, the research team demonstrated the use of a microscopic traffic simulation engine to generate the needed traffic signal data for real-world ATSPM systems to generate performance measures. With the developed insights and software tools from that project, the research team will assist and facilitate TxDOT to implement the delivered ATSPM-in-the-loop simulation engine toward a regular task for ATSPM-enhanced traffic signal planning and design. This project will also expand the developed ATSPM-in-the-loop simulation platform to meet all the practical needs for TxDOT's ATSPM deployment effort. This project will increase the TRL from 7 to 9 by assisting TxDOT to develop a practical solution to increase stakeholders' access to and acceptance of the ATSPM concept in various types of traffic signal projects.]]></description>
      <pubDate>Thu, 22 Aug 2024 17:19:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2420080</guid>
    </item>
    <item>
      <title>Enhancing Automated Vehicle Operation and Safety on Rural Roads and Underserved Areas: Challenges and Innovative Solutions</title>
      <link>https://rip.trb.org/View/2384857</link>
      <description><![CDATA[The potential of connected and autonomous vehicles (CAVs) to revolutionize transportation is undeniable. However, unlocking this potential requires addressing the unique challenges posed by rural roads. Rigorous testing and innovative solutions are key to enhancing CAV safety in these challenging environments. The proposed project will provide safe mobility and accessibility to underserved and minority populations in rural road areas. Given the operational challenges of CAVs in such settings, the project will 1) develop a conceptual framework by synthesizing the literature on CAV algorithms, 2) develop a CAV testing plan in rural settings utilizing a unique CAV-in-the-loop simulation setup, 3) engage in software development for simulation using CARLA and OpenPilot software, and 4) analyze the results and provide innovative solutions to address challenges, such as adverse weather conditions, complex terrain, hazard classification, and limited sensor range, to improve CAV performance on rural roads. ]]></description>
      <pubDate>Thu, 30 May 2024 18:21:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2384857</guid>
    </item>
    <item>
      <title>Improving Traffic Signal System Planning, Design and Management with Big-data-enhanced Automated Traffic Signal Performance Metrics (ATSPM) System</title>
      <link>https://rip.trb.org/View/2256333</link>
      <description><![CDATA[This project provides a guideline accompanied with the necessary software tools for the 
Texas Department of Transportation (TxDOT) and local agencies to better use the Automated Traffic Signal Performance Metrics System (ATSPM) in arterial traffic management. The ATSPM system came to traffic signal operations years ago and it can help agencies better understand arterial traffic signal performance. Many agencies are considering adopting the ATSPM systems because the ATSPM system(s) focuses on monitoring the traffic signal performance in the field. However, most traffic signal planning and design activities at present still rely on the traditional methods, such as Synchro, Highway Capacity Manual, etc. If agencies adopt different criteria between the planning/design stage and implementation stage, confusion will form and grow with the increase of ATSPM adoptions. To fill this gap, the research team plans to take a systematic approach to introduce the ATSPM concepts into all stages of traffic signal management. The research team will develop a series of software tools to establish a new "ATSPM-In-The-Loop" traffic signal simulation framework, accompanied by case studies that public agents or consultants can use to evaluate their future traffic signal timing plans in simulation before deployment. The outcomes of this project will nationally be the first of its kind.]]></description>
      <pubDate>Wed, 27 Sep 2023 17:15:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/2256333</guid>
    </item>
    <item>
      <title>Work Zone Safety: Behavioral Analysis with Integration of VR and Hardware in the Loop</title>
      <link>https://rip.trb.org/View/1700547</link>
      <description><![CDATA[Despite increased regulations, restrictive measures, and devices used for warnings, work zone injuries and fatalities are still observed at highway construction projects with alarms/notifications being ignored. With a vision to reduce the number of injuries and fatalities, Phase 2 of the research team's worker safety project extends the original scope and adds a Hardware in the Loop (HIL) component to simulate real traffic scenarios through simultaneous interactions with variety of vehicles and deployed sensor data in immersive virtual environments. The project aims to understand the key parameters (e.g., work zone location characteristics, personal vigilance levels, duration of construction work) that play roles in behaviors of workers in response to notifications received from various warning mechanisms (e.g., sound, vibration). Key questions this research answers are, at what conditions workers ignore/response to warnings at work zones? How we can calibrate notification systems for getting responsive actions from workers? What are the modalities, frequencies, and timings of pushing notifications in these calibrated systems? Through wearable sensors and hardware integrated realistic representations of work zones in virtual reality, the team plans to collect worker behavioral and physiological (heart rate) responses to alarms/warnings/notifications issued under various realistic scenarios and modalities of warning mechanisms (e.g., sensory, visual, audial) and analyze these captured data towards understanding human behaviors in response to modalities of notifications.]]></description>
      <pubDate>Thu, 23 Apr 2020 08:18:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1700547</guid>
    </item>
    <item>
      <title>HRDO-FY16-09 Hardware in the Loop Testing of CAV</title>
      <link>https://rip.trb.org/View/1512830</link>
      <description><![CDATA[Allows the potential impacts of connected automated vehicle applications currently under development by FHWA to be further assessed through use of recently developed hardware in the loop (HIL) tools that allow test vehicles from the Saxton Lab to operate through interaction with virtual traffic.]]></description>
      <pubDate>Thu, 17 May 2018 09:43:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1512830</guid>
    </item>
    <item>
      <title>Integrative Vehicle Infrastructure Traffic System (iVITS) Control in Connected Cities</title>
      <link>https://rip.trb.org/View/1485728</link>
      <description><![CDATA[A simulation-based approach is being used for the evaluation of traffic control algorithms that will utilize connected vehicle (CV) technologies. Given the ongoing CV pilot deployment in New York City (NYC), the proposed project will tie in to the objectives set out to be achieved as a part of the NYC CV pilot. The City College of New York (CCNY) team will work with New York University (NYU) and UW researchers to test the models and algorithms in microsimulation and hardware-in-the loop simulations on a NYC-specific network.]]></description>
      <pubDate>Tue, 17 Oct 2017 13:31:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/1485728</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>Leveraging Connected Vehicles to Enhance Traffic Responsive Traffic Signal Control</title>
      <link>https://rip.trb.org/View/1401178</link>
      <description><![CDATA[Actuated traffic signal controllers rely on sensors to detect vehicles so that green time can be allocated on a second-by-second basis. Traffic signals that are part of a closed loop system running coordination plans can also utilize detector information to select different pre-programmed plans based on the current traffic state. These Traffic Responsive Plan Selection (TRPS) algorithms currently rely on point detectors that only measure volume and occupancy. With the anticipated implementation of Connected Vehicles, sensors can be installed at signalized intersections to collect the trajectory of these vehicles, which will allow queue lengths to be estimated. Additionally, many radar-based sensors that are currently on the market are capable of tracking vehicles approaching an intersection, which can also be used to estimate queue lengths. This queue length information can be fused with the volume and occupancy data from point detectors to gain an even better understanding of the state of the signal system. This enhanced information could likely allow even better selection of pre-programmed coordination plans. When trajectory-based vehicle information becomes widespread and reliable, it is entirely possible that this information will be used by the controller logic to directly make decisions. In the meantime, this research will investigate whether this information can be leveraged to further enhance TRPS control, which is widely available in most traffic signal controllers. An existing Central system-in-the-loop simulation of a traffic signal system in Morgantown, WV will be utilized to implement and test algorithms for estimating queue lengths from vehicle trajectory data in real-time, estimating the state of the system in real-time, and communicating information back to the controllers to change the timing plans, when appropriate. The advanced TRPS will be compared to basic coordination timing plans and basic TRPS control across various volume scenarios to estimate improvements in delay, emissions, and fuel consumption.]]></description>
      <pubDate>Tue, 15 Mar 2016 18:37:41 GMT</pubDate>
      <guid>https://rip.trb.org/View/1401178</guid>
    </item>
    <item>
      <title>Development and Evaluation of Coordinated Traffic Signal Emergency Preemption System</title>
      <link>https://rip.trb.org/View/1364460</link>
      <description><![CDATA[The objective of this O&amp;E Grant is to quantify the operational benefits of preempting an entire corridor for emergency vehicle operations, rather than preempting each individual intersection as the emergency vehicle arrives. Arterial test segments will be selected and characterized for evaluation purposes. A micro-simulation model (in VISSIM) will be the primary evaluation tool. During the reporting period, research activities have included: 1) data collection and micros- simulation model development and calibration; 2) priority rules used to model yielding behavior of general traffic to emergency vehicles achieved in simulation; 3) volume calibration in simulation model completed; 4) controller transition types and measures of effectiveness identified for evaluation; 5) travel time data of emergency vehicles on typical arterials gathered from the fire department database; and 6) hardware in the loop system established, updated and tested for preemption call.]]></description>
      <pubDate>Sat, 08 Aug 2015 01:01:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/1364460</guid>
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