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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>
    <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>From perception to preparedness: Virtual reality simulations of flooded roadways in coastal communities (UPRM)</title>
      <link>https://rip.trb.org/View/2663232</link>
      <description><![CDATA[Project Description: Coastal flooding regularly disrupts transportation networks, damages infrastructure, and limits access to essential services through storm surge, tidal inundation, and extreme precipitation. These events result in vehicle failures, stranded motorists, pavement damage, and delays in emergency response and daily mobility. Communities with aging infrastructure, limited resources, or constrained evacuation options face heightened vulnerability. The total annual economic burden of flooding in the U.S. ranges from $179.8 to $496.0 billion (US Congress JEC, 2024). In addition, the National Weather Service and the Centers for Disease Control and Prevention report that over half of all flood-related drownings occur when a vehicle is driven into hazardous floodwater. Understanding how drivers decide whether to cross or avoid flooded roads is essential for designing warnings, signage, and roadway treatments that reduce risky behavior and improve outcomes. The use of virtual reality (VR) and immersive 360° scenarios can let residents experience rising water, blocked routes, and mitigation measures without real-world risk, increasing realism and emotional stimulus. Scenario-based VR visualizations can help translate technical flood data into intuitive, actionable information for nontechnical audiences. Local resilience depends not only on infrastructure but also on household-level preparedness and decision-making, including how individuals interpret alerts and respond to flood risks. Chacon-Hurtado (2013) advocates for embedding community preferences and preparedness considerations directly into transportation decision-making frameworks, arguing that investments should be evaluated not only on engineering metrics but also on how they advance local capacity to act under hazard conditions. 
This project will employ virtual reality (VR) simulations of flooded highways that are being developed by the University of Puerto Rico at Mayagüez (UPRM) team to study human behavior and perception in flood scenarios, with three main goals: (1) Enhance public understanding of flood risks by immersing participants in realistic coastal flooding scenarios, (2) Evaluate driver decision-making when encountering flooded roadways, analyzing how variables such as water depth, roadway conditions, and alert systems (e.g., signage, ADAS, in-vehicle alerts) influence choices, and 
(3) Assess community preferences for flood mitigation strategies, using immersive experiences to gather feedback on potential interventions. 
Two VR approaches will be implemented. The first involves a driver simulator with 24–36 participants navigating flooded roadway scenarios to assess behavioral responses under controlled conditions. The second approach will engage community members from coastal municipalities like Isabela, Puerto Rico, in immersive 360° simulations to explore perceptions of flood risk and mitigation strategies. Pre- and post-tests will measure changes in knowledge, perception, and behavioral intent. Insights from both simulations will inform the design of more effective alert systems and flood mitigation strategies that reflect community preferences and improve safety. The findings will support transportation and emergency planning professionals in developing human-centered solutions for flood-prone coastal areas.

]]></description>
      <pubDate>Sat, 31 Jan 2026 12:03:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663232</guid>
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    <item>
      <title>Vulnerability assessment and durability of coastal freight networks (UPRM)</title>
      <link>https://rip.trb.org/View/2663230</link>
      <description><![CDATA[Project Description: Freight networks, including ports, coastal highways, bridges, and distribution hubs, are critical lifelines that sustain regional economies, enable everyday commerce, and support emergency response after catastrophic events. The coastal location of this essential transportation infrastructure makes these assets uniquely vulnerable to extreme natural events such as flooding, storm surge, coastal erosion, and compound hazards. The Puerto Rico’s 2050 Long Range Transportation Plan explicitly calls for reducing transportation vulnerabilities to extreme weather effects and improving connectivity. Puerto Rico could serve as a critical logistics hub for U.S. freight operations in the Caribbean, offering strategic access to regional markets and maritime routes. But recent storms Hurricane María (2017) and Hurricane Fiona (2021) have highlighted the freight network’s fragility and the urgent need for targeted resilience measures. 
The assessment of Puerto Rico’s freight network, one that relies solely on the performance of the highway system, can be a case study to evaluate the system vulnerabilities derived from natural flood hazards, aging infrastructure, urbanization in coastal areas, and congestion in strategic corridors. A rigorous vulnerability assessment combines data from hydrologic and coastal flood modeling with traffic flows, asset condition inventories, and safety records to identify critical and single-point-of-failure links. This integrated analysis can provide a method to reveal which corridors and nodes are most likely to fail under different flood scenarios, how congestion and limited redundancy amplify delays, and which assets require immediate reinforcement or operational changes. It can also uncover system-level interdependencies among ports, road networks, and distribution hubs that are not visible from isolated asset inspections. This project can assist local transportation agencies, freight operators, and decision-makers in identifying risks to the freight network, improving the assessment of infrastructure assets by including the interdependence between ports, road networks, and distribution hubs, and prioritize improvements in strategic planning and project development. This project is envisioned as a two-year program. Year 1 will define Puerto Rico’s primary freight network anchored at the ports of San Juan and Ponce, map major distribution points, and develop an interactive dashboard showing asset condition, corridor flows, crash hotspots, and flood-vulnerable links and nodes. Four analytical dimensions will be assessed: infrastructure condition, traffic flows, safety, and durability, using official data, operational reports, and geospatial analysis to identify hotspots and critical vulnerabilities. Year 2 will focus on network optimization and investment prioritization, applying stochastic and optimization models to produce a prioritized, implementable resilience strategy. A Texas State University team will collaborate in the review of stochastic and optimization approaches, the evaluation of data requirements and computational complexity, and provide recommendations about the best model(s) for optimizing freight flows and prioritizing investments from ports to distributors.

]]></description>
      <pubDate>Sat, 31 Jan 2026 11:32:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/2663230</guid>
    </item>
    <item>
      <title>Identifying and evaluating the most effective actions to prepare Puerto Rico’s primary ports and freight road transportation infrastructure for flooding disruptions using stochastic models</title>
      <link>https://rip.trb.org/View/2662990</link>
      <description><![CDATA[One of the seven issues listed in the freight assessment section of the 2050 Long Range Multimodal Transportation Plan (LRMTP, approved in 2023) encompasses the need for Puerto Rico’s ports and road freight transportation network (RFTN) to be less vulnerable to extreme weather events that affects the durability of the infrastructure and disrupts the movement of goods and services. Puerto Rico has an excellent geographic location for the transshipment of goods to other places in the Americas. Strategies to mitigate infrastructure damage to ports and roads resulting from overuse and to keep the system operating effectively will help Puerto Rico maintain its position as a global logistics hub. The development of an adaptable highway transport system is crucial, as railroads are not well-developed to undertake the freight transport needs, and the use of the marine-based freight M2 route connecting main and secondary ports is only emerging. 
The objective of this research project is to quantify and classify the impact of certain operational decisions made before and after flood-related weather events on four performance or optimization criteria: ports and RFTN infrastructure, traffic flows, safety, and flexibility to avoid delays and disruptions. The operational decisions to include are: increasing ports’ operating hours, locating regional hub-and-spoke points where freight coming from the ports is transferred from large trucks to smaller vehicles and routed to the distribution points, determining existing or to be developed alternative roads that reduce congestion at hotspots, and routing loads between ports. To accomplish the objective, TXST will develop a preliminary stochastic programming model to optimize a prototype of Puerto Rico’s RFTN, considering multiple flooding scenarios, forecasts of freight demand over 5 and 10 years, and the above-mentioned operational decisions and optimization criteria. A variant of the developed model, which represents the current operations of ports and roads without incorporating any of the proposed operational decisions, will be used for comparison purposes. The main freight distribution points and associated demands to input into the models will be identified in cooperation with the listed project partner faculty at UPRM.  Puerto Rico’s industry, government agencies, and consultants for these agencies will be sources to get the models’ input data, as well as information available online. If needed, the distribution points will be clustered.  In this preliminary model, the unavailable data will be identified and estimated. The model will demonstrate to the Puerto Rico Department of Transportation and Public Works, the Puerto Rico Highway and Transportation Authority, and other relevant agencies a process they can apply for making informed decisions to enhance the durability and resilience of port and RFTN infrastructure under uncertainty caused by flooding and the relevance of collecting any highly relevant and missing data.]]></description>
      <pubDate>Thu, 29 Jan 2026 16:19:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2662990</guid>
    </item>
    <item>
      <title>Comparing Pricing Mechanisms of Managed Lanes: Performance Assessment of PR-22 Dynamic Toll Lanes</title>
      <link>https://rip.trb.org/View/2589111</link>
      <description><![CDATA[A performance assessment and willingness-to-pay (WTP) analysis were conducted of the reversible dynamic toll lanes (DTL) of freeway PR-22 in Puerto Rico. This is the first managed lane facility of its kind in a toll freeway in Puerto Rico. Toll transactions from the year 2019 were used to calculate seven performance measures to assess the impact of the managed lanes on travel times and vehicle speeds on the 12 km-long (7.7 mi) segment. The results demonstrate that the dynamic pricing algorithm behaves as expected, increasing the price for the DTL as traffic increases and vehicle speeds decrease on the facility, and provided satisfactory performance for the conditions at PR-22. The DTL provided an average travel time savings of 7 minutes and enhanced travel time reliability when compared with the general toll lanes (GTL) during the morning peak period. Compared to six other managed lane facilities in the U.S., the results from the PR-22 DTL show higher travel time savings and reliability. A survey of PR-22 users was conducted to estimate their willingness-to-pay (WTP) and their attitudes and perceptions associated with the quality and usage of the DTL. The aggregate analysis of PR-22 users using the Van Westerndorp Price Sensitivity Meter resulted in a WTP range for the DTL of $1.00 to $2.79, which is less than the $4.95 maximum toll charged for the managed lane facility. Even though the maximum price exceeds their WTP, the level of congestion in the GTL during peak periods still motivates users to pay the extra fee for the DTL outside of their preference. A regression analysis found that the factors that significantly reduce the WTP of the freeway users include subjects from higher income levels, higher ages, and females. As stated by freeway users, the congestion in the GTL is the main factor that influence them to use the DTL. Therefore, a recommendation to increase the usage of the PR-22 DTL is to provide commuters with relevant information about the real-time benefits of the DTL. The implementation of a high-occupancy vehicle (HOV) policy for the freeway corridor should also be studied. A HOV policy could promote ridesharing on the corridor while providing economic relief and reducing or eliminating the premium toll fee of the managed lanes to some commuters.]]></description>
      <pubDate>Sat, 16 Aug 2025 23:49:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/2589111</guid>
    </item>
    <item>
      <title>Resilience Based Decision Support System for Critical Transportation Corridors</title>
      <link>https://rip.trb.org/View/2431338</link>
      <description><![CDATA[A comprehensive methodology for developing a decision-making support tool is proposed that assesses risks for transportation corridors, with a particular focus on infrastructure and services to support the blue economy. Central to this approach is the integration of coastal considerations into the Vulnerability Assessment Scoring Tool (VAST) and its application within vulnerability assessments. By augmenting VAST with a Coastal Category, the methodology aims to illuminate disparities and highlight vulnerable populations, ensuring their representation in decision-making processes. Through the inclusion of indicators such as income levels, disability prevalence, and accessibility during extreme events, the Coastal Category within VAST enables a nuanced understanding of vulnerability within coastal communities. Ultimately, by addressing coastal disparities head-on, this methodology not only enhances the accuracy and effectiveness of vulnerability assessments but also advances broader goals of resilience in coastal transportation planning.]]></description>
      <pubDate>Tue, 17 Sep 2024 16:37:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/2431338</guid>
    </item>
    <item>
      <title>Capacity Building and Workforce Development for Coastal Transportation Infrastructure Subjected to Multi-hazards (Phase 2)</title>
      <link>https://rip.trb.org/View/2431336</link>
      <description><![CDATA[This project aims to develop a decision-making tool to assess and enhance the durability of transportation corridors in coastal communities, crucial for supporting the blue economy. By focusing on the specific needs of these communities, the research will address the challenges posed by natural hazards and the importance of durable infrastructure in fostering economic growth. The initiative also seeks to advance transportation workforce development by integrating blue and green economy principles, emphasizing the need for collaboration among stakeholders, and providing education on designing infrastructure that withstands natural disasters. The project will identify key lessons and recommendations to help educators engage with this critical engineering field, ultimately driving regional economic growth and improving coastal transportation infrastructure durability..]]></description>
      <pubDate>Tue, 17 Sep 2024 16:34:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2431336</guid>
    </item>
    <item>
      <title>AI-supported Monitoring and Resiliency Analysis for the Coastal Area of the Luis Muñoz Marín International Airport in Puerto Rico</title>
      <link>https://rip.trb.org/View/2012462</link>
      <description><![CDATA[The Luis Muñoz Marín International Airport and its coastal area in Puerto Rico, an overseas US territory that needs resources to recover from Hurricane Irma and Maria and to face future devastating coastal hazards in the economic crisis, has been facing the challenge of coastal flooding, erosion, and storm damage. Field observation is needed to support the potential vulnerability assessment. The primary goal of this proposal is to develop a surveillance camera-based coastal monitoring system for the San Juan International Airport and surrounding areas to support a resiliency study. The intended outcome of the project is to produce a resiliency report with recommendations for the Luis Muñoz Marín International Airport and the surrounding area. This report will help the administrators to understand the current situation and adapt to improve the durability and extend the life of infrastructure. In a larger scale, the monitoring system will be useful to analyze the regional natural hazards to the transportation system that link to the airport safety and functionality.]]></description>
      <pubDate>Thu, 25 Aug 2022 15:53:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2012462</guid>
    </item>
    <item>
      <title>Assessing the Effect of Drivers’ Behavior in Rural Roads with Advanced Driver Assistance Systems Using a Driving Simulator</title>
      <link>https://rip.trb.org/View/1853636</link>
      <description><![CDATA[Traffic crashes in rural roads are a serious safety related issue because of the disproportionality between fatalities and the rural population. As a result of this concern, the safety of rural roads has been the focus of attention in recent years. According to NHTSA, 45% of all traffic fatalities in 2018 occurred in rural areas, while having only 19% of the total population, according to the U.S. Census. This percentage of traffic fatalities in 2018 is more significant in Puerto Rico’s rural road network with an alarming 58% of all fatalities. Furthermore, the fatality rate in rural roads in Puerto Rico is estimated at 16.53 per 100-Million VMT, which is 6.2 times greater than the highest fatality rate of any state in the U.S. 
The Federal Highway Administration (FHWA) in its Every Day Counts (EDC) initiative known as, FoRRRwD, recommends proven roadway departure countermeasures, such as rumble strips, friction treatments, and clear zones. However, additional countermeasures considering a systemic approach to rural highway safety, including speeding control, are needed.  A possible systemic approach countermeasure could be Advanced Driver-Assistance Systems (ADAS), which includes vehicle-related safety measures based on Information and Communication Technologies (ICT). 
This research project aims to assess the impact of implementing a Speed Monitoring Display (SMD), with and without voice messaging, as an ADAS strategy in a driving simulation study. The ADAS strategy will have the purpose of alerting “speeding” drivers in hazardous locations. High-risk roadway features will be identified from a representative rural road segment in Puerto Rico and used as a base condition to develop the simulation scenarios. The drivers’ behavior, including speed compliance, will be examined with and without the ADAS. The final goal will be to improve driver behavior in rural roads to improve safety using a systemic strategy to identify potential hazardous location that can assist in decreasing speeding related issues and reduce the frequency and severity of crashes.]]></description>
      <pubDate>Mon, 24 May 2021 11:36:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/1853636</guid>
    </item>
    <item>
      <title>Analyzing the Performance of Remote-Drivers on Transit Shuttle Short Routes</title>
      <link>https://rip.trb.org/View/1705308</link>
      <description><![CDATA[Using driving simulation, this project will study how a remote driver performs when operating a transit vehicle in complex scenarios that involve pedestrian-avoidance maneuvers. These types of maneuvers are typical at the University of Puerto Rico-Mayagüez campus due to the availability of satellite parking lots for students and the significant use of on-street parking by students. Transit shuttles traveling from the satellite parking locations constantly have to avoid pedestrians walking along the road. This type of scenario could be challenging to autonomous transit vehicles and can prompt the transfer of control to remote vehicle operators thus the focus of the project on the performance of a remote driver under such a scenario.
The type of maneuvers required to navigate the complex parking scenarios are often the result of localized behaviors which on its own present an interesting research challenge, e.g, understanding how the need for localized knowledge and understanding of cultural norms impact the feasibility of operating a vehicle remotely by drivers unfamiliar with the roadways. Driver performance, which will be primarily monitored through effective reaction time to events, will be studied using a driving simulator environment created in a game engine and which will be operated remotely using multiple vehicle views in a custom control environment. (UW)

Current autonomous vehicle technology has been trained in traditional roadway conditions that do not necessarily represent the aggressive road user behavior and nuances of driving transit vehicles in highly congested environments with the combination of cars, pedestrians, and roadside parking. Therefore, until fully autonomous vehicles become an effective transit solution for an environment with highly localized behavior, remotely operated passenger vehicles that operate autonomously on most of the roadway can be used to manage a more extensive fleet of vehicles to satisfy the existing transit demand. The proposed research project will study the safety performance of a remotely operated passenger transit vehicle in a simulation scenario that replicates vehicle and pedestrian behavior typical to local highways in the University of Puerto Rico at Mayaguez (UPRM) campus that will be used as a test-bed in this project. Transfer of control issues aside, the remote operation of a vehicle warrants studying as it is not a simple task with deterministic safety impacts. Latency in the network that makes communication between a control station and a remotely operated vehicle possible could be detrimental to safety. Initially, data will be collected to document the most concerning situations related to a potential implementation of autonomous transit vehicles. After identifying critical safety conditions, scenarios will be developed to generate the simulation test-bed. Simulation experiments will be conducted using a simulation control interface created at the University of Wisconsin Madison. Experiments will include a group of drivers that are knowledgable of the shuttle route and another group that would not be familiar. Analysis of the reaction time data to events will be performed using the data collected in the Simulation Control Cabin to compare the performance of both groups of drivers. (UPR)]]></description>
      <pubDate>Thu, 07 May 2020 12:57:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/1705308</guid>
    </item>
    <item>
      <title>Evaluation of Driver Workload and Training Strategies on a Diverging Diamond Interchange</title>
      <link>https://rip.trb.org/View/1705299</link>
      <description><![CDATA[The amount of information processed by drivers in freeways and arterials increases significantly at interchanges. The information includes changes in alignment and number of lanes, lane position, merging and diverging from the main road, change of safe vehicle speed according to the alignment changes, and the need for attention to various types of road signs. Therefore, negotiating interchanges is a very complex and demanding task. Many studies have been looking at innovative designs to improve safety concerns while reducing urban congestion. One of those innovative intersections is the Diverging Diamond Interchange (DDI) that will be implemented for the first time in Puerto Rico in the state road PR-30 Km 4.1 in Gurabo, PR. Since this is the first time that this type of intersection is implemented in Puerto Rico, the proposed research study aims to determine which training strategy is better suited to effectively communicate drivers the correct way to drive along with this type of intersection. To assess the safety and operational effectiveness of the training strategies, a detailed study on how local drivers behave and the mental workload experienced when driving through the proposed DDI for the first time will be performed. A new factor included in this research is the drivers’ cognitive workload or brain workload. This variable will be evaluated using various biosensors, included with the dry-electrode DSI-24 EEG headset and the algorithms to measure workload that has been developed by the providers of this type of equipment. The comparison of the effect of the strategies will be evaluated using the driving simulator of UPRM. The identification of the best training strategies would allow state, local, and federal institutions to use them in their educational and awareness campaigns.]]></description>
      <pubDate>Thu, 07 May 2020 12:37:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/1705299</guid>
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    <item>
      <title>Developing Generalized Linear Mixed Models For The Strategic Highway Safety Planning Process</title>
      <link>https://rip.trb.org/View/1352305</link>
      <description><![CDATA[Highway Safety has been identified as a very important problem worldwide. It has been found as the second cause of deaths in the world according to the United Nations (2010). In fact, only in the US, the effects of road crashes cost billions of dollars per year. The US Department of Transportation has established highway safety as one of their main priorities in their Action Plan. Several efforts are underway; however, in many states including Puerto Rico, most of the strategies implemented have a reactive or short-term planning approach. Such approach has generated some improvements in the current system, however, a proactive approach is necessary to consider highway safety aspects in the decision making process from the beginning of the generation of planning alternatives. The proposed research project will fit Generalized Linear Mixed Models (GLMM) to be used for the incorporation of highway safety in the strategic planning process. These GLMM have several advantages to predict crash rates including that they incorporate not only a set of explanatory variables but also random effects present in the system, which helps to explain possible correlation in the data. Therefore, these types of models offer great versatility in the modeling of crash rates and its related factors]]></description>
      <pubDate>Thu, 30 Apr 2015 01:00:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1352305</guid>
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