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    <title>Research in Progress (RIP)</title>
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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>
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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>Low-Cost AI-Based System for Temporary Traffic Control Review</title>
      <link>https://rip.trb.org/View/2717331</link>
      <description><![CDATA[Work-zone fatalities in the United States increased by about 50% between 2013 and 2022, with a surge of 33% in 2021 alone. To protect workers and guide drivers safely through modified traffic patterns, temporary traffic controls (TTCs) are used that must be regularly inspected for proper functioning. However, the current inspection process is manual and resource intensive, typically involving a three-person team: one person to drive, another to photograph, and a third to document observations. This staffing requirement limits the frequency and the geographic coverage of safety reviews. 

For NCHRP 20-30/IDEA 264, the research team will develop an open-source artificial intelligence (AI)-powered TTC inspection software that leverages Vision Language Models and requires just one inspector with a dashcam and an internet-connected computer. The inspector will drive through the work zone, upload dashcam footage for processing, and review AI-detected issues on an interactive video. The system will transform TTC reviews in several significant ways: (1) Convert a three-person operation into a streamlined, single-operator system, enabling more frequent inspections across wider geographic areas without additional labor cost. (2) Apply assessment criteria uniformly and objectively across all work zones. This offers the potential to deliver more consistent and accurate evaluations regardless of inspector fatigue, regional staffing differences, and complex work zones. (3)       Harness the growing availability of crowdsourced dashcam footage from commercial fleets and autonomous vehicles. This integration transforms work-zone monitoring by ensuring remote, widespread, continuous geographical coverage, including during challenging conditions such as nighttime and adverse weather.

The team will focus on high-priority deficiencies the Texas Department of Transportation identified that carry the highest penalties and represent significant safety hazards in work zones. A structured database of historical review reports will be created for use for training, validation, and prototype testing. Working with Texas Department of Transportation, an evaluation metric will be established and refined. This will be followed by a system engineering task in which core components or modules of the proposed system will be developed and tested individually and in end-to-end testing using a dataset. The system’s report generation component will synthesize component outputs into standardized inspection documentation, incorporating observations, images, regulatory citations, and location data for each identified deficiency. Finally, the AI-based system will be tested and validated across at least three active work zones in Texas that have ongoing, traditional TTC inspections.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:44:23 GMT</pubDate>
      <guid>https://rip.trb.org/View/2717331</guid>
    </item>
    <item>
      <title>Improving the Quality and Useability of Planned and Active Work Zone Data</title>
      <link>https://rip.trb.org/View/2683244</link>
      <description><![CDATA[Work zone data may be used to support efforts ranging from internal operational and safety analysis to public communications and connected vehicle navigation. Ensuring the quality and consistency of this data is vital to its usability. The Virginia Department of Transportation (VDOT)’s current systems,  VaTraffic and the Lane Closure Advisory Management System (LCAMS), require double entry of data, and the other data sets they feed into all display the data differently. This project will review data quality standards and create guidance that can be applied in LaneAware to ensure quality moving forward. In November 2024, the Federal Highway Administration (FHWA) updated its Work Zone Safety and Mobility Final Rule (23CFR630 Subpart J), which in part requires state departments of transportation (DOTs) to identify mobility and work-zone-exposure performance metrics that will be used to track performance and the statewide level and for specific major projects.  Best practices used by other DOTs will be gathered and recommended for adoption. Tools and scripts for data cleaning and analysis will improve the application of these data to operational and safety analysis, which is currently hampered by issues such as identifying data from planned work zones from active ones. By consulting with a wide range of stakeholders, these recommendations will consider the wide-ranging needs of both data producers and consumers in this system.     ]]></description>
      <pubDate>Tue, 24 Mar 2026 10:53:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/2683244</guid>
    </item>
    <item>
      <title>Road Network Restoration after Major Disruptions</title>
      <link>https://rip.trb.org/View/2447123</link>
      <description><![CDATA[This project develops practical optimization methods for selecting, sequencing, and scheduling restoration actions for disrupted road networks based on incomplete and gradually improving information. Road networks may be severely damaged by events such as hurricanes and earthquakes, and prompt restoration is often necessary for the resumption of emergency services, other essential services, and normal activities.

The proposed methods employ artificial intelligence heuristics such as genetic algorithms and particle swarm algorithms to optimize the schedules of restoration tasks. A hybrid optimization approach combines fast traffic assignment with microscopic simulation to refine solutions. The methods are designed to start with incomplete, uncertain information and adapt dynamically as additional data becomes available from weather forecasts, work crews, and the public. The project also develops methods for pre-planning purposes, including preparing effective restoration plans based on estimated probabilities of disruptions and their consequences.

The research team will collaborate with the Maryland State Highway Administration and other agencies to ensure the practical applicability of the methods. Technology transfer activities include journal papers, conference presentations, software with a user manual, a final technical report, and workshops for interested transportation organizations.]]></description>
      <pubDate>Wed, 11 Mar 2026 13:21:54 GMT</pubDate>
      <guid>https://rip.trb.org/View/2447123</guid>
    </item>
    <item>
      <title>OpenRoad Link: A Public-Private Data Exchange for Safer, Smarter Trucking </title>
      <link>https://rip.trb.org/View/2646948</link>
      <description><![CDATA[Work zones, lane closures, and traffic incidents significantly impact roadway safety and efficiency. When lanes are blocked due to construction, crashes, or other disruptions, roadways no longer function as designed—leading unexpected congestion, increased crash risk, and reduced operational reliability. Many work zones are established to perform critical maintenance on aging infrastructure—essential to improving durability and extending the service life of roadways—but they also introduce temporary risks and delays that must be better managed.  Effects of lane blockages are particularly severe for commercial motor vehicles (CMVs), which require more time and space to slow or reroute and are subject to strict hours-of-service regulations that make delays especially costly. 

This project proposes to develop and evaluate a data exchange framework—OpenRoad Link—to integrate and share real-time lane closure, work zone, and incident data from the Oklahoma Department of Transportation (ODOT), the Oklahoma City and Tulsa Traffic Operations Centers (TOCs), and other key transportation and traffic enforcement partners. To build this framework, the project will first identify and assess the roadway data already collected and shared by these agencies, as well as the types of information currently accessible to the CMV industry through private telematics platforms. Building on national standards such as the Work Zone Data Exchange and SAE J2735 (the standard message set for vehicle-to-everything communications), the project will extend the data scope to include lane-blocking crashes, maintenance activities, and other short-term or unplanned restrictions not currently emphasized in existing feeds. Through collaboration with ODOT, city TOCs, and trucking industry partners—including a pilot with a major trucking company such as ABF—the project will demonstrate the delivery of curated, high-value information directly to in-cab devices or fleet management systems.  

Key tasks will include identifying and cataloging roadway and incident data currently collected by the Oklahoma Department of Transportation (ODOT) and the Traffic Operations Centers (TOCs) of Oklahoma City and Tulsa, as well as evaluating what information is already being shared with the commercial vehicle industry through private telematics platforms. The project will establish partnerships with ODOT, city transportation and public safety agencies, and private industry stakeholders to design and implement a unified, standards-compliant data exchange framework. Following the design phase, the team will develop and deploy the OpenRoad Link data feed, ensuring compliance with existing national standards and verifying data accuracy and reliability. A pilot deployment will be conducted in collaboration with a trucking company using a selected in-cab device to deliver actionable, real-time information directly to CMV drivers.  

Anticipated outcomes include improved safety for CMV drivers, a reduction in secondary crashes, enhanced freight reliability, and a validated proof-of-concept for scalable public-private data exchange. By producing a replicable model for collaboration between state DOTs and private-sector technology providers, the project aims to accelerate national adoption of interoperable safety data systems and promote safer, more efficient freight transportation. ]]></description>
      <pubDate>Tue, 06 Jan 2026 08:59:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/2646948</guid>
    </item>
    <item>
      <title>Connected Corridors Advancement Initiative</title>
      <link>https://rip.trb.org/View/2645418</link>
      <description><![CDATA[The I-80 Corridor Coalition and I-35 Advancement Alliance are spearheading the Connected Corridors Advancement Initiative (CCAI) to address evolving challenges and leverage opportunities in corridor management and transportation technology. As critical transcontinental arteries, these corridors underpin national commerce and mobility, fostering regional connectivity and economic growth.

Building upon AASHTO NCHRP 20-24(138) recommendations and inspired by successful models such as the I-95 Corridor Coalition and the Eastern Transportation Coalition, the initiative seeks to establish a framework for open data standards, infrastructure modernization, and multi-state collaboration. The Nevada DOT SMART Grant Enhancing Corridor Communication Roadmap will serve as a foundation model, showcasing enhanced inter-agency coordination and scalable technology deployment. International efforts, including Europe’s NAPCORE and Canada’s CAV Standards, highlight best practices in data interoperability and advanced infrastructure.

To sustain economic competitiveness, ensure national security, and foster technological leadership, the United States must develop integrated, multi-state corridor frameworks focused on data sharing, operational efficiency, and resilient infrastructure. Enhanced collaboration will bolster domestic mobility, supply chain reliability, and national emergency response capacity. Corridor coalitions have demonstrated the effectiveness of public-private partnerships in addressing infrastructure needs, facilitating transportation planning, and improving operational efficiency across multiple jurisdictions.

OBJECTIVES: The CCAI aims to modernize corridor operations, enhance safety, and optimize economic efficiency by aligning efforts across state, federal, and private sectors. Objectives include developing and implementing open data standards for Work Zone Data Exchange (WZDx), Truck Parking Information Monitoring Systems (TPIMS), and national interoperability of communication data feeds to enable seamless communication across jurisdictions. Additionally, the initiative seeks to prepare the corridor for connected and automated vehicle (CAV) technologies by supporting data interoperability between states, agencies, emergency services, industry partners and the traveling public.]]></description>
      <pubDate>Wed, 24 Dec 2025 15:04:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2645418</guid>
    </item>
    <item>
      <title>Evaluating Method 2 Horizontal Curvature in Freeway Work Zones: Safety, Suitability, and Alternatives</title>
      <link>https://rip.trb.org/View/2608464</link>
      <description><![CDATA[In freeway design, Method 5 is the standard approach for determining horizontal curvature on high-speed highways, while Method 2 is intended for low-speed urban facilities where higher side friction values are acceptable. However, in Utah, Method 2 has been implemented in high-speed freeway work zones through Alternative Technical Concepts
(ATCs), most notably on the I-15 Technology Corridor project. Post-construction crash records revealed truck overturning incidents and other safety concerns, raising questions about the suitability of Method 2 in high-speed environments.

While Utah Department of Transportation (UDOT) has already developed a five-year statewide database of work zones containing crash data (AASHTOWare Safety) and project details (Masterworks), this database does not distinguish between projects that used Method 2 horizontal curvature versus standard lane-shift tapers (Method 5). Without this distinction, UDOT lacks the ability to directly assess whether Method 2 increases crash severity, particularly for heavy vehicles, in comparison to established design practices. This gap in knowledge is critical given the safety implications for drivers and workers in high-speed freeway work zones, as well as the need to guide ATC approvals on future Design-Build projects.

This research is needed to provide UDOT with a data-driven evaluation of Method 2’s risks, safety impacts, and design suitability in freeway work zones. Findings will clarify whether Method 2 should remain an acceptable option and under what conditions it might be safely applied.]]></description>
      <pubDate>Mon, 13 Oct 2025 19:12:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2608464</guid>
    </item>
    <item>
      <title>SPR-5010: Feasibility Study of Deploying Movable Barriers as Permanent Barriers and Temporary Traffic Barriers for Future Roadway Design, Construction, and Maintenance</title>
      <link>https://rip.trb.org/View/2601511</link>
      <description><![CDATA[Current highway designs typically rely on permanent barriers to separate lanes and on temporary traffic barriers and traffic control devices to establish work zones. Previous efforts have primarily focused on the safety/cost benefits of movable barriers only in work zones; however, the feasibility of deploying movable barriers as permanent barriers and temporary traffic barriers has yet to be studied through roadway life cycle. This research will conduct a comprehensive comparison to determine whether to adopt movable barriers as replacements/additions in future roadway design, construction, and maintenance.]]></description>
      <pubDate>Thu, 18 Sep 2025 16:09:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/2601511</guid>
    </item>
    <item>
      <title>Guide for UAS Deployment in Work Zone Lighting Applications</title>
      <link>https://rip.trb.org/View/2558408</link>
      <description><![CDATA[BACKGROUND: Lighting is essential for ensuring safety in work zones. Conventional lighting, which relies on fixed-position light towers, has notable limitations including restricted coverage, uneven illumination, limited adaptability in dynamic work environments, and operational inefficiencies. These limitations are especially pronounced in wide-area work zones where repositioning conventional light towers is difficult, often leaving sections of work zone areas inadequately lit and potentially increasing the risk of crashes. Unmanned aircraft systems (UAS), which can be tethered for power and equipped with floodlighting, offer a mobile alternative. Their ability to be repositioned quickly enables targeted, uniform illumination and helps reduce glare and shadows, improving visibility for workers and motorists. Although UAS lighting shows strong potential, its use in work zones is still emerging, and further research is needed to optimize its deployment and integration into safety protocols. 

OBJECTIVE: The objective of this research is to develop a guide for state departments of transportation (DOTs) to support UAS deployment in work zone lighting applications. 

TASKS: PHASE I: Task 1. Conduct a literature review on the use of UAS for lighting in transportation work zones. Task 2. Conduct a state of practice review of state DOTs use of UAS lighting in work zones and identify any potential operational licensing and permitting requirements for the use of UAS lighting. Task 3. Using the findings from Tasks 1 and 2, perform a gap analysis to discern what is needed to fulfill the research objectives. Task 4. Prepare a research plan for various use cases to evaluate and compare the use of UAS lighting systems and conventional work zone lighting in transportation work zones. The plan should determine how UAS lighting may be optimized to meet work zone project needs and be integrated into existing safety protocols. At a minimum, the research plan shall include: (1) A data collection and comparative analysis plan for evaluating UAS lighting in different work zone use cases; (2) Evaluation and comparison of UAS lighting systems and conventional work zone lighting in work zones; (3) Determination of how UAS lighting can be optimized to support work zone operations and safety; and (4) Integration considerations for incorporating UAS lighting into existing work zone safety protocols. The research plan shall incorporate the following elements for analysis: (1) Best flight patterns for maintaining consistent illumination; (2) Lumens required for adequate lighting; and (3) Procedures to safely operate tethered UAS near workers, equipment, and traffic. The research plan shall describe how the following factors are considered (including but not limited to): acceptable levels of luminance; airspace integration; cost analysis; equipment portability; funding and procurement strategies; project delivery impacts; project scalability; and road user and worker safety. Task 5. Prepare an annotated outline of a UAS lighting guide.
Task 6. Prepare Interim Report 1 that documents Tasks 1 through 5 and includes the proposed Phase II work plan.

PHASE II: Task 7. Execute Task 4 according to the approved interim Report 1 and document the effort in Technical Memorandum 1. Task 8. Develop a draft guide and outreach material. Task 9. Convene a virtual workshop to solicit feedback on the draft guide and outreach material. Summarize the results and update the draft guide based on the feedback obtained at the workshop. Task 10. Prepare a stand-alone memorandum with language suitable for consideration by the American Association of State Highway Transportation Officials (AASHTO) for use in developing standards and specifications for the use of UAS for lighting applications in work zones. Task 11. Prepare Interim Report 2 that documents the work completed in Tasks 7 through 10 and updates the Phase III workplan.

PHASE III: Task 12. Submit the final deliverables, which shall include, but not be limited to:    
a practical guide on UAS lighting in work zones; outreach materials; a stand-alone memorandum prepared for AASHTO; a final conduct of research report that documents the entire research process; a brief PowerPoint presentation describing the background, objectives, approach, summary of findings, conclusions, and speaker notes; and
a stand-alone technical memorandum titled “Implementation of Research Findings and Products” (see item IV). ]]></description>
      <pubDate>Tue, 27 May 2025 21:01:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558408</guid>
    </item>
    <item>
      <title>Missouri Work Zone Speed Study</title>
      <link>https://rip.trb.org/View/2548661</link>
      <description><![CDATA[This project will assess speeds driven by motorists in Missouri freeway work zones, including not only average speeds but also levels of work zone speed compliance and noncompliance. The research team will perform a literature review and conduct field work to collect and measure work zone speed data. This project will help improve work zones by providing Missouri Department of Transportation (MoDOT) with data to help inform decisions regarding how to focus work zone speed enforcement efforts.]]></description>
      <pubDate>Wed, 30 Apr 2025 09:40:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2548661</guid>
    </item>
    <item>
      <title>	Identifying Locations with High Wrong-Way Driving Risk and Effective Methods to Reduce Wrong-Way Driving at Non-Conventional Access Points and Construction Zones on Limited Access Roadways</title>
      <link>https://rip.trb.org/View/2526499</link>
      <description><![CDATA[The main goal of this research is to utilize a proven wrong-way driving (WWD) hotspot methodology invented by Professor Al-Deek and his University of Central Florida (UCF) research team to help Florida Department of Transportation (FDOT) identify WWD hotspot roadway segments and individual exits with high WWCR on limited access facilities in District 5, with additional focus on WWD at the various types of NCAPs previously mentioned and in construction zones. Exit ramps, different types of NCAPs, and construction zones have different characteristics, so potential WWD countermeasures specific to each of these locations will be identified, along with the potential for improved data practices to better detect and monitor WWD. This research will allow FDOT to prioritize locations in D5 for future WWD countermeasure deployments or enhancements to existing WWD countermeasures, better understand the characteristics of WWD behavior at NCAPs and construction zones, identify arterial interchanges for investigation, and develop appropriate deployment plans and treatment strategies for any future WWD countermeasure deployments and construction zone operations to proactively reduce WWD on the district’s transportation network in the most effective manner, saving lives and helping achieve FDOT’s goal of Target Zero. The methodology and results from this project could also be applied to other FDOT districts to help them combat the WWD problem.]]></description>
      <pubDate>Thu, 20 Mar 2025 11:25:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2526499</guid>
    </item>
    <item>
      <title>Enhancing Traffic Delay Prediction Utilizing Data-Driven Techniques</title>
      <link>https://rip.trb.org/View/2485374</link>
      <description><![CDATA[A model that accurately predicts both traffic delays and the queues that result from work zones would be a valuable tool to Arizona Department of Transportation (ADOT), helping the agency to manage traffic, enhance work zone planning, reduce congestion, and improve road safety. Currently, ADOT lacks the ability to generate estimates of congestion and delays that result from lane closures and other forms of planned or unplanned roadway capacity reduction. Instead, the agency relies on rough generalities to manage traffic and maintain safe operating conditions around work zones. 

Integrating a data-driven model—one that is based on roadway capacity and travel demand—into the work-zone management process would help the Traffic Operations Center (TOC) and other ADOT groups respond to both planned and unplanned traffic-delay events. Information that predicts potential problems before they occur could help the TOC prepare more efficiently for closures and other events by anticipating messaging and communication needs to the traveling public.]]></description>
      <pubDate>Fri, 03 Jan 2025 16:08:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2485374</guid>
    </item>
    <item>
      <title>RES2023-24: Informed Safety, Mobility and Driver Comfort Enhancement Practices for Work Zones</title>
      <link>https://rip.trb.org/View/2480317</link>
      <description><![CDATA[This study leverages high-fidelity observational data to analyze driver behavior and vehicle dynamics within work zones (WZs) on Tennessee’s interstate highways, aiming to evaluate critical aspects of safety, mobility, and driver comfort. Data were collected over several months from global positioning system (GPS), IMU sensors, and video recordings on commercial  vehicles traveling through two active WZs on I-40 near Jackson, Tennessee. By using precise, sensor-based measurements of speed, acceleration, heading, and lane position, this research offers a detailed, real-time perspective on how WZ conditions influence driver behavior. The observational data reveal distinct patterns, such as increased speed variability and frequency of lane changes within WZs, which are indicative of driver discomfort and potential evasive actions. The analysis also shows that specific WZ configurations, including barrier placement and lane narrowing, impact driver response differently across locations, underscoring the importance of tailored Temporary Traffic Control (TTC) strategies. This study suggests that by leveraging high-fidelity data, traffic 
management can adopt more adaptive measures—such as dynamic speed feedback and improved visual guidance—to enhance safety and driving experience in WZs. The findings contribute to a deeper understanding of driver-vehicle interaction under varying WZ conditions, offering valuable insights for future WZ design and management.]]></description>
      <pubDate>Fri, 03 Jan 2025 12:03:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2480317</guid>
    </item>
    <item>
      <title>Monitoring of Urban Roadway Safety Hazards from Existing Bus-based Video Imagery: Phase 2</title>
      <link>https://rip.trb.org/View/2440023</link>
      <description><![CDATA[Traffic safety is diminished by drivers’ changing lanes in queued traffic at signalized intersections, bus stops, and construction zones, mixes of vehicle classes, variability in speeds, and vehicle overtaking. Assessing locations with these recurring but dynamic hazards requires extensive and ongoing data collection. Traditional data collection methods rely on sensors at permanent or temporary fixed locations, which are costly, labor intensive, and provide limited collection over time and space and only of some hazard contributors. Moreover, the location of these sensors may be influenced by factors other than optimal sampling, such as requests from well-organized constituencies. Therefore, relying on the traditional methods could lead to missing high-risk conditions resulting in decreased safety and inequitable outcomes.

Transit buses operate regularly over wide networks, and most bus fleets are already equipped with cameras that record the environment inside and outside buses for liability, security, and safety purposes. Consequently, the imagery is available for other uses at near-zero marginal cost, and the extensive spatial coverage of transit fleets would provide comprehensive views that could be used to determine times and locations of regularly occurring safety hazards. Moreover, this imagery has been shown by the principal investigators (PIs) to be effective in monitoring traffic volumes across time and space, information that provides exposure-based context for identifying safety hazards. In the current phase 1 project (year-1), the PIs are investigating the use of available, repeated, and extensive imagery recorded by cameras mounted on transit buses in regular operation to identify “hazardous hotspots”. The proposed phase 2 project (year-2) would build on the phase 1 investigations.

The PIs have been obtaining transit bus-based video imagery to estimate traffic flows across the Ohio State University (OSU) campus and providing summary results to campus planners and operators on a regular basis. The OSU campus will again be used as a living lab testbed. The size and diversity of land uses make the campus representative of urban areas. Moreover, the campus has been undergoing major construction activities, which allows investigation of different infrastructure conditions that could influence traffic safety. Using the campus as an experimental testbed also allows for in-situ ground-truth observations to assess the accuracy of the video-based results.

Hazards being considered in phase 1 include lane specific queue lengths at intersections and bus stops and vehicle type mix with an emphasis on vulnerable vehicles (e.g., bicycles, scooters, and motorcycles). Frequency of lane-changing in the presence of queues, speeds, and speed variation where autos conflict with vulnerable vehicles are also important safety factors. In phase 2, the ability to measure these hazards from the imagery would be investigated, and methods to do so would be developed. In addition, changes in speeds at construction zones measured from the imagery would be explored given the safety hazards associated with these zones. Moreover, while the identification of hazards in phase 1 is being demonstrated using semi-automatic techniques based on a Graphical User Interface, in phase 2 automation of the identification of hazards will be pursued.]]></description>
      <pubDate>Sun, 13 Oct 2024 09:34:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440023</guid>
    </item>
    <item>
      <title>SafeSpeed: Enhancing Work Zone Safety through Speed Enforcement 
</title>
      <link>https://rip.trb.org/View/2440014</link>
      <description><![CDATA[The large number of work zone crashes has been a significant concern of transportation agencies and researchers. In the US, a work zone crash occurred every five minutes during 2015-2019. One approach for transportation agencies to reduce work zone crashes is to lower the speed within work zones, for example, posting speeding limits and installing speeding cameras. This approach is supported by studies that highlighted that average traffic speed is associated with crash risk. However, the findings of the relationship between traffic speed and crashes are inconsistent, which could lead to conflicting or even misleading interventions with the speed enforcement in work zones. Work zone presence could lead to the reduction of actual traffic speed that influences crash risk and, at the same time, directly impose effects on crash risks.  It is challenging to rigorously separate these direct and indirect impacts. Furthermore, the actual impact of speed enforcement countermeasures on work zone crash risk has been rarely studied among the literature, providing limited knowledge on whether these countermeasures are effective in reducing crash risk near work zones in practice.

In this research project, the research team will apply a comprehensive causal analysis and Web-Geographic Information Systems (GIS) approach to enhance work zone safety through speed enforcement in Pennsylvania and Maryland. It contains three core initiatives. First, it develops a causal inference model to analyze the impact of work zones on crash risk controlling for traffic speed with the equational g-estimation and regression discontinuity design (RDD), using multiple large-scale and high-granular data sets. Second, it examines the work zone impact on crash risk under different speed enforcement countermeasures. Lastly, the research team creates an interactive Web-GIS platform for comprehensive traffic safety analysis in work zones, enabling stakeholders to access and analyze crashes related to work zones, speed enforcement measures, and other important crash contributors, with continuous data updates planned until 2025. This platform aims to identify high-risk areas and provide insights for safety improvements in work zones.

First, the team will establish a rigorous causal inference model to infer the causal impact of work zones on crash risk when the traffic speed is controlled with high-granular and multi-source data sets. The team proposes to use an innovative approach, i.e., the combination of the sequential g-estimation and RDD, to examine the causal effect of the presence of work zones on crash occurrences when the traffic speed is controlled. The sequential g-estimation removes the effect of traffic speed on crash risk. RDD mitigates the potential confounding bias caused by roadway characteristics. The proposed method will be implemented using high-granular and multi-source data of thousands of work zones in Pennsylvania (PA) and Maryland (MD) between 2018 and 2023 to control for the complex built and natural environments and reduce the associated bias of the estimation. The results can provide insights for most desired and actual traffic speeds to reduce work zone crash risk.

Second, the team will examine the impact of work zones on crash risk under different speed enforcement countermeasures. The team will apply the same framework in the first step to examine the heterogenous causal impact of work zones on crash risk under different speed enforcement countermeasures, including no speed enforcement, posting speed limit, and posting speed limit along with enforcement (e.g., automated speed enforcement and high-visibility enforcement), and compare the impacts for the work zones in PA and MD. In addition, the team will further estimate these heterogenous impacts (by speed enforcement countermeasure) under various work zone characteristics, time of day, and traffic volumes. The results can offer information on how different speed enforcement countermeasures modify the causal impact of work zones on crash risk and, accordingly, provide implications for better deploying these countermeasures.

Third, the team will build an interactive Web-GIS platform for work zone traffic safety analysis using the safety data in PA and MD. The digital platform provides users with an online interactive interface to explore all work zones in PA and MD by multiple aspects, including speed enforcement countermeasures, average speed, traffic volumes, roadway characteristics. In addition, the platform can help users identify high-risk locations, highlight potential crash contributors, and offer suggestions on how to improve work zone safety for each work zone based on their characteristics and locations.  In addition, the team will continue to collect and archive up-to-date data from various data providers in both PA and MD from 2024 to 2025 and enhance the web platform. The safety data providers include Pennsylvania Department of Transportation (PennDOT), Maryland Department of Transportation (MDOT SHA), Waze, NOAA, and private data sources, including INRIX, TomTom, and Replica. The team will integrate and analyze large-scale crash data and develop an additional function to the platform to visualize and forecast crash types, frequencies, and severity for each road segment in the two states, especially those with work zones and different speed enforcement countermeasures. With that said, the platform allows transportation agencies and other related stakeholders, such as urban planning departments, local communities, consulting firms, and academic institutions, to access historical, real-time, and forecasted traffic safety metrics for all work zones. The team will continue to interview various data providers to enhance the quality and quantity of massive data in both states.
]]></description>
      <pubDate>Sat, 12 Oct 2024 12:18:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440014</guid>
    </item>
    <item>
      <title>Smart Work Zone Deployment Initiative (2025-2029)</title>
      <link>https://rip.trb.org/View/2437939</link>
      <description><![CDATA[The Midwest Smart Work Zone Deployment Initiative (MwSWZDI) was initiated in 1999 as a Pooled Fund Study intended to coordinate and promote research related to safety and mobility in highway work zones. The Iowa Department of Transportation (IowaDOT) has been the lead state since 2004. The program is an ongoing cooperative effort between State Departments of Transportation, universities, and industry. Commercial products are provided by private vendors for evaluation, although this is not the only focus of contracted projects. State DOTs provide funds, prioritize products with respect to the anticipated benefits to their construction and maintenance activities, and cooperate with researchers to identify test sites and conduct the evaluations. Each year, the Board of Directors (BOD, a.k.a. Technical Advisory Committee, TAC) collect and/or create problem need statements. Subsequent requests for proposals are developed and distributed to potential researchers at research institutions in contributing states. Partner state departments of transportation ()DOTs review, discuss and rank the proposals. 

OBJECTIVES: This program represents an on-going effort among cooperating states’ DOTs, the Federal Highway Administration (FHWA), universities, and industry to evaluate new products and conduct related research focused on the enhancement of safety and mobility in highway work zones. Over 100 studies and evaluations have been completed since the inception of the SWZDI.]]></description>
      <pubDate>Tue, 08 Oct 2024 15:33:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2437939</guid>
    </item>
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