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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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      <title>Advanced InSAR–UAV-LiDAR Flood-Deformation Risk Monitoring for Efficient Mobility</title>
      <link>https://rip.trb.org/View/2669656</link>
      <description><![CDATA[El Paso’s critical transportation corridors face compounding risks from ground deformation and flash flooding that can severely disrupt efficient mobility, impede traffic flow, and challenge infrastructure reliability. Such infrastructure disruptions compromise public safety by delaying emergency response access and increase collision risk on compromised roadways. Despite advances in satellite monitoring and hydrologic modeling, no integrated system currently provides transportation agencies with rapid and actionable, near-real-time alerts for combined flood-deformation hazards. This project is designed to support uninterrupted mobility directly by developing and demonstrating a unified monitoring framework that fuses millimeter-precision Interferometric Synthetic Aperture Radar (InSAR) deformation maps with Unmanned Aerial Vehicle–Light Detection and Ranging (UAV-LiDAR) terrain models and Synthetic Aperture Radar (SAR)-derived soil-moisture indices to deliver actionable risk assessments. The research addresses a core challenge in maintaining efficient mobility: predicting when and where infrastructure vulnerabilities will coincide with flood conditions. Using validated Persistent Scatterer (PS) and Small Baseline Subset (SBAS) InSAR processing chains, high-resolution UAV-LiDAR surveys, and machine learning algorithms trained on historical events, the proposed system will provide transportation agencies with advanced warning, which enables proactive response and traffic management. The project will produce a composite flood-deformation risk index with demonstrated 90% accuracy in hazard detection. An edge-computing prototype will be deployed in partnership with the Texas Department of Transportation (TxDOT) to operationalize the fusion algorithms, enabling 24-hour processing turnaround and secure web-based risk visualization. Through formal partnerships with TxDOT and El Paso Water, the system will integrate real-time flow gauge data and infrastructure databases to enhance model calibration and validation. The project includes comprehensive technology transfer components, such as Docker-containerized software, training workshops for state Department of Transportation (DOT) engineers, and a commercialization brief outlining licensing pathways for rapid deployment across additional corridors.  ]]></description>
      <pubDate>Sun, 15 Feb 2026 16:40:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669656</guid>
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      <title>Enabling Mobility of Emergency Medical Service through Connected and Automated Vehicle Preemption</title>
      <link>https://rip.trb.org/View/2669655</link>
      <description><![CDATA[Emergency Medical Service (EMS) vehicles, typically ambulances, have time-critical transportation roles when responding to traffic incidents by bringing first medical responders and equipment from their bases to the incident scenes, and transferring injured persons from the scenes to medical facilities. Addressing the mobility of EMS vehicles supports but public health and safety goals, as well as those related to efficient mobility.     

The traditional way for EMS vehicles to reach their destinations faster is to use audible sirens to alert drivers of their presence. Upon hearing an EMS vehicle’s siren, drivers must yield the right of way to facilitate its passage. Previous research on traffic signal preemption for EMS vehicles has demonstrated its effectiveness in reducing delays at signalized intersections. With the advent of Connected and Automated Vehicle (CAV) technology, vehicles can now communicate directly with each other. EMS vehicles equipped as CAVs could leverage vehicle-to-vehicle (V2V) communication technology to transmit warning messages to the CAVs downstream along their routes, beyond the range of audible sirens. The CAVs that have received these messages can proactively move aside to create a clear lane for the EMS vehicle to pass. This “CAV preemption” concept has the potential to significantly improve EMS mobility, resulting in faster response times, earlier on-scene medical aid, and quicker patient transfer to hospitals. Furthermore, the proposed CAV preemption will accelerate incident clearance and the restoration of highway capacity.  

This research is based on an envisioned CAV preemption system in which an EMS vehicle broadcasts its impending arrival to downstream CAVs, while simultaneously sounding its siren and emitting high-intensity strobe light to request signal preemptions. All CAVs receiving this V2V message will automatically move to the right lane, while only a portion of the non-CAV drivers will comply and respond to the siren. The efficiency of this system depends the following factors: (1) The broadcast range of the warning messages to CAVs, (2) The market penetration rate of CAVs, (3) The move-aside compliance rate of non-CAV drivers, (4) The level of traffic congestion.  

This research will simulate and quantify the efficiency of the proposed CAV preemption system under varying operating conditions. An agent-based simulation model of the El Paso highway network will be used to assess the EMS vehicle’s travel time. Mobility efficiency is defined as the percentage reduction in the average travel time. The travel times of EMS vehicles from their bases (selected fire stations that house ambulances) to multiple incident sites (selected highway locations) will be simulated, extracted, and analyzed. The analyses will assess the impacts of broadcast range, CAV market penetration, non-CAV compliance rate, and traffic volume.   ]]></description>
      <pubDate>Sun, 15 Feb 2026 16:34:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669655</guid>
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    <item>
      <title>Enhancing Urban Micromobility Safety and Adoption through Biometrics and Mobile Sensing Technologies in El Paso, TX and New Brunswick, NJ</title>
      <link>https://rip.trb.org/View/2459052</link>
      <description><![CDATA[This project will explore how street-level infrastructure design factors affect the perceived safety of e-scooters in El Paso, Texas, and New Brunswick, New Jersey, using advanced biometric sensing technologies like eye-tracking glasses, galvanic skin response sensors, heart rate trackers, and video cameras. Researchers at the University of Texas El Paso (UTEP) and Rutgers will conduct e-scooter riding experiments with varied environments, infrastructure, demographics, and micromobility policies. This analysis aims to identify stress patterns, safety issues, and congestion challenges faced by micromobility users. Thirty participants will be recruited in each city, with diverse demographics, to ride e-scooters on pre-defined paths featuring different travel environments, such as bike lanes, varied land uses, shaded areas, and topographies. The post-trip questionnaire survey data will be collected to calibrate/validate sensor results. The sensor data on the perceived travel environment will be digitized using advanced segmentation and object detection algorithms applied to video and gaze data. Statistical and machine learning models will analyze gaze behavior and perceived stress levels by environment, providing insights on improved infrastructure design and transportation policies for e-scooters.]]></description>
      <pubDate>Thu, 21 Nov 2024 16:37:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2459052</guid>
    </item>
    <item>
      <title>Enhancing Transit Access and Safety Through Equitable Micromobility Solution</title>
      <link>https://rip.trb.org/View/2283488</link>
      <description><![CDATA[Micromobility refers to transportation enabled by small, low-speed, human- or electric-powered transportation devices, such as bicycles and scooters. Micromobility may be organized and deployed as a shared vehicle system, as the first and last-mile transportation mode to supplement transit. This project will investigate two major issues associated with the use of micromobility as a solution to improve the accessibility to transit in underserved communities. The first issue is related to the identification of micromobility stations in areas that are underserved by the fixed-route transit system. The second issue is the safety impacts of implementing micromobility in the abovementioned neighborhoods, and the related infrastructure improvements. A Concept of Operations (ConOps) of micromobility will be proposed to address the needs of the first and last-mile travel in consideration of traffic safety and infrastructure needs. The research team will collaborate with the City of El Paso’s bus service operator (Sun Metro), Street and Maintenance Department, the El Paso Metropolitan Planning Organization (MPO) to use El Paso, Texas as the case study, with safety data from the Texas Department of Transportation (TxDOT), and operational experience of GLIDE Scooter.]]></description>
      <pubDate>Mon, 30 Oct 2023 22:40:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2283488</guid>
    </item>
    <item>
      <title>Development of a Framework to Estimate Crashes Involving Pedestrians in Urban Areas Using Parking, Transit, and Infrastructure Factors</title>
      <link>https://rip.trb.org/View/1925802</link>
      <description><![CDATA[Urban areas tend to have higher concentrations of pedestrians. Accordingly, there are more pedestrian related traffic crashes. During the morning and evening commute hours, pedestrian trips are generated largely by travelers walking from their parked vehicles, transit stops to the final destinations, and vice versa. The risk of a pedestrian being involved in a traffic crash is related to the exposure and conflicts. Both exposure and conflicts are related to pedestrian routes. A pedestrian route may be characterized by the origin, destination, distance, elevation gains, number of street crossings, type of crossing (e.g., signalized versus unsignalized crossings), paved versus unpaved sidewalk, etc. The objective of this project is to develop a framework to predict the rate of crashes involving pedestrians in urban areas. The research team will relate the pedestrian related crash rate in a defined pedestrian analysis zone as a function of the parking demand, transit ridership, and pedestrian infrastructure. The developed model may be used by engineers and planners, as well as potentially by the City of El Paso, to predict the rate of pedestrian related crashes. By analyzing the contributing factors in the model, engineers and planners may identify ways to reduce pedestrian involved crashes, and/or improve walkability.]]></description>
      <pubDate>Thu, 10 Mar 2022 15:41:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/1925802</guid>
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    <item>
      <title>Green Transportation Infrastructures in Desert Cities</title>
      <link>https://rip.trb.org/View/1803018</link>
      <description><![CDATA[The research team proposes to use the semi-arid urban environment of the City of El Paso to explore the transportation-ecologic-environment-community nexus of distributed, multi-objective Green Transportation Infrastructure Initiative (GTI). The overarching objective of the project will be to develop a framework for southwestern urban areas to identify locations for green infrastructure and rank them based on a series of criteria corresponding to the myriad benefits that can be taken from GTI. These benefits include, but are not limited to stormwater management, groundwater recharge, traffic calming, pavement protection, reduction in heat island effects, and community stakeholder engagement, all while incorporating southwestern design elements and addressing the unique challenges of the region (e.g., flash floods surface drainage). The team will implement the framework for El Paso as a demonstration case, identifying and ranking locations for GTI implementation. The team will quantify the potential benefits for the city and the community, and the team will conduct outreach activities focused on fostering community investment and excitement about GTI. The work will be scalable and transferrable to other southwestern urban areas, and transformable to other regions of the United States. The following tasks will be undertaken in working toward this objective, with the overall goal of establishing a bottom-up, distributed approach to improving quality of life that cuts across domains and stakeholders: Task 1 - Literature review and data collection (Month 1-3); Task 2 -  Advisory committee formation (Month 1-3); Task 3 - Develop a framework for GTI site selection and ranking (Months 3-8); Task 4 - Scalability and feasibility assessment (Months 8-10); and Task 5 - Dissemination and stakeholder engagement (Months 10-12). 

The team will produce a framework for GTI site selection and ranking for use on existing infrastructure networks that utilizes a quantitative decision-making approach to accommodate a multi-objective approach. This project will increase the understanding about the transportation/GI intersection. It will also help to increase adoption of new practices and techniques in practice. The team expects this project to garner interest both at the neighborhood level, but also the district (city council) level, and throughout certain departments at the city (e.g., streets and maintenance, planning and construction, capital improvement department). This could lead to pilot studies and demonstrated successes that will contribute to the state of the art in GTI in the southwest and beyond. The team will seek partnerships locally to continue this work, both with nonprofit organizations to find new and creative ways to continue to implement (i.e., finance) these projects throughout the city. 
]]></description>
      <pubDate>Wed, 03 Mar 2021 19:38:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/1803018</guid>
    </item>
    <item>
      <title>Urban Connector Year 3: Field Tests</title>
      <link>https://rip.trb.org/View/1607557</link>
      <description><![CDATA[In the past 2 years, initial surveys were conducted in El Paso and in New York City to understand the lifestyles and mobility needs of the senior adults. A smartphone application prototype named Urban Connector (UC) was developed to cater to the seniors in El Paso. A follow-up survey was conducted to gather feedbacks on the UC application prototype. Subsequently the UC prototype was improved to its beta version. This project is continuing with the following objectives:
-To customize the beta version of the UC application for New York City
-To perform a beta test in New York City and gather user feedbacks
-To fine-tune the UC application, based on the information collected in El Paso in Year 2 (the third survey) to release Version 1.0
-To collect a set of UC application usage data through an anonymous pilot test
-To explore a data analysis framework that will characterize a UC application user's mobility patterns without knowing the person's identity]]></description>
      <pubDate>Wed, 22 May 2019 13:26:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/1607557</guid>
    </item>
    <item>
      <title>Automated Truck Lanes in Urban Area for Through and Cross Border Traffic</title>
      <link>https://rip.trb.org/View/1583778</link>
      <description><![CDATA[Autonomous trucks will soon be operational across the nation’s roadways. Yet, it is unclear how the design of highway infrastructure should be modified to accommodate autonomous trucks, to enable them to operate in such a way to maximize the economic, capacity and safety benefits. The University of Texas at El Paso (UTEP) is proposing to develop and demonstrate, through microscopic traffic simulations, the concept of operations of autonomous truck lanes along the interstate freeways. Using the I-10 Freeway in the El Paso, TX region as the testbed, the research team will: (i) assess the existing structural, geometric and traffic designs in handling fully automated trucks,  including the entrances, exits, and connectors; (ii) perform microscopic traffic simulations at critical locations to demonstrate design issues and the recommended design improvements; (iii) conduct a preliminary cost estimation on such infrastructure improvements.]]></description>
      <pubDate>Thu, 14 Feb 2019 09:05:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/1583778</guid>
    </item>
    <item>
      <title>Development of A Mobile Navigation Smartphone Application for Seniors in Urban Areas</title>
      <link>https://rip.trb.org/View/1485723</link>
      <description><![CDATA[Many seniors face mobility issues and changes in life-style, for example, switching from driving to using a carpool, taxi or fixed route or demand responsive public transportation. There are few smartphone applications that cater to the mobility needs of seniors (such as information on Americans with Disabilities Act (ADA) compliant infrastructure), and the few that exist have limited functions. The objectives of this project are (a) to understand the lifestyle and mobility needs of seniors; (b) to develop a prototype smartphone smart mobility application that caters to the needs identified; (c) to conduct pilot tests in El Paso and New York.]]></description>
      <pubDate>Tue, 17 Oct 2017 13:10:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/1485723</guid>
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