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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Advanced InSAR–UAV-LiDAR Flood-Deformation Risk Monitoring for Efficient Mobility</title>
      <link>https://trid.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://trid.trb.org/View/2669656</guid>
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    <item>
      <title>Enabling Mobility of Emergency Medical Service through Connected and Automated Vehicle Preemption</title>
      <link>https://trid.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://trid.trb.org/View/2669655</guid>
    </item>
    <item>
      <title>Impacts of bus rapid transit (BRT) on income-segmented housing markets in El Paso, Texas: A spatial hedonic and difference-in-differences analysis</title>
      <link>https://trid.trb.org/View/2611209</link>
      <description><![CDATA[This study evaluates the impact of introducing the Bus Rapid Transit (BRT) system on housing market dynamics across three diverse urban corridors in El Paso, Texas, utilizing spatial hedonic pricing and AITS-DID models. The research aims to understand how the BRT system influences property values, hypothesizing that the effects vary between developed and underdeveloped areas. Initial findings reveal an increase in property values in the affluent Mesa area until the BRT opening in 2014, followed by a decline, suggesting a shift in market perceptions post-implementation. Conversely, less affluent areas along the Alameda and Dyer corridors exhibit a reduction in the negative impact on property values over time, indicating growing appreciation for the BRT and associated urban improvements. The study contributes to urban planning and policy by highlighting the mixed impacts of BRT systems on property values across different urban fabrics and underscores the importance of context-sensitive transit planning. It also points to the necessity for comprehensive communication with stakeholders to ensure transit solutions meet community needs and support equitable urban development.]]></description>
      <pubDate>Wed, 14 Jan 2026 17:40:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611209</guid>
    </item>
    <item>
      <title>Premature casual carpooling in Texas: analyzing customer churn in the Metropia experiment with survival analysis and machine learning</title>
      <link>https://trid.trb.org/View/2593147</link>
      <description><![CDATA[This study makes a timely contribution to peer-to-peer mobility research by employing a hybrid analytical framework that integrates survival analysis (Cox Proportional Hazards model) with advanced machine learning techniques (XGBoost and SHAP values) to uncover nuanced patterns of user churn in the Metropia app. The Metropia experiment, a peer-to-peer carpooling program, was conducted in Austin and El Paso, TX, with a sample of 3,227 users who first engaged with the app between January 1, 2016, and December 31, 2018. By connecting sociodemographic factors, trip characteristics, and app incentives to user retention, this study offers a data-driven view of behavior on mobility platforms. Results show that older users, females, and telecommuters are more likely to stay, while higher-income households, larger families, long commutes, and experienced drivers show higher churn. Several app features show complex, non-linear effects on disengagement. Interpreted through the lenses of transaction cost economics, network effects, and prospect theory, these findings highlight the importance of reducing perceived user costs and enhancing value through thoughtful app design. The study not only identifies critical behavioral and structural challenges facing casual carpooling but also sheds light on its premature development stage. It offers actionable insights for platform developers and planners to enhance engagement and retention, while calling on local governments to support shared mobility through strategic policy and urban design. This research ultimately advances the discourse on sustainable urban transportation and the future of the sharing economy.]]></description>
      <pubDate>Tue, 30 Sep 2025 08:34:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2593147</guid>
    </item>
    <item>
      <title>Forecasting Traffic Characteristics for Air Quality Analyses</title>
      <link>https://trid.trb.org/View/2570761</link>
      <description><![CDATA[This research intends to develop techniques for estimating and forecasting three critical mobile source emission related travel indicators: vehicle age distribution, mileage accumulation rates by vehicle type, and vehicle miles traveled (VMT) & mix. As for modeling the vehicle age distribution, two model types were used; each of which contains the linear model, nonlinear model and time series model. Age distributions for the 8 counties in Houston-Galveston Area Council (HGAC) area and in EI Paso, Texas were used to validate the model structures and parameters. As for modeling the mileage accumulation rate, a practical algorithm for adjusting the default mileage accumulation rate for site-specific application based on a small sample field survey was developed. Applications in two Texas cities (Houston and EI Paso) were conducted and the whole operation process and its impacts on the estimates of emission factors were presented. As for VMT & mix, extensive efforts were made on collecting information on VMT & mix estimation. A nationwide survey through e-mail was conducted to ascertain what kinds of methodologies were used by other states. Accordingly, a practical improvement to the VMT & mix estimation methodologies was developed. Link volume estimates were modeled as the function of both the traffic count data and the link attributes. A case study in southwest Houston was illustrated to show the estimation process and the effectiveness of the proposed approach. Impact analysis shows that the emission factors generated by local improved VMT estimation are closer to the ideal one, and better than both the nationwide default and the Traffic Count Method.]]></description>
      <pubDate>Sat, 30 Aug 2025 16:09:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2570761</guid>
    </item>
    <item>
      <title>Traffic Simulation at the International Ports of Entry: El Paso-Mexico Case Study</title>
      <link>https://trid.trb.org/View/2567176</link>
      <description><![CDATA[According to recent studies, over 75% of the US-Mexico overland trade flows through Texas. International traffic is channelized through 18 border sectors, many of which experience congestion caused primarily by lack of effective interaction among inspection procedures and traffic management. This situation requires a case-study approach, which is conducive to efficient problem solving in complex situations. This project reports the development of a computer simulation model of the first case study investigated in this study, namely the Zaragoza Bridge in El Paso, Texas. To achieve this objective, real time queuing data, such as interarrival times of vehicles and service times of inspectors, were sampled, collected, and tested. In addition to the actual case, three case studies were studied under current traffic volumes and under a 50 percent increase in volume.]]></description>
      <pubDate>Mon, 18 Aug 2025 12:11:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567176</guid>
    </item>
    <item>
      <title>Quality Management of Asphalt-Concrete Layers Using Wave Propagation Techniques</title>
      <link>https://trid.trb.org/View/2567162</link>
      <description><![CDATA[Highway agencies spend significant amounts of money and time coring and in-situ testing flexible pavements to implement a rigorous quality control/quality assurance program. The quality of the asphalt concrete (AC) pavement is assessed through field inspections, laboratory testing of pavement cores, thickness determinations, and compacted density measurements. To successfully implement a mechanistic pavement design procedure or to develop realistic performance-based specifications, a method of monitoring the modulus of a laid-down AC layer is needed. The modulus of an AC layer can be either indirectly predicted by using physical and volumetric properties of the mixture, which are measured in the laboratory, or obtained directly from field testing. Seismic nondestructive testing methods can potentially offer an efficient, economical, reliable, and repeatable way of measuring the modulus of AC layers. In addition, seismic methods are the only means of measuring the same moduli in the field and in the laboratory. In this study, a laboratory method and a field seismic method for determining the modulus of AC layers are introduced, and their instrumentation and theoretical aspects are presented. The impacts of the gradation, asphalt viscosity (asphalt grade), void in total mix, temperature, and thickness of the AC layer on the modulus are introduced. The preliminary protocol proposed for quality management of AC, based on seismic methods, is included.]]></description>
      <pubDate>Sat, 16 Aug 2025 16:59:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567162</guid>
    </item>
    <item>
      <title>Bus Rapid Transit Impact on Property Prices: Comparing Two Natural Experiments in El Paso, TX</title>
      <link>https://trid.trb.org/View/2516316</link>
      <description><![CDATA[Bus Rapid Transit (BRT) has been increasingly popular recently. This study compiles longitudinal house transaction data and carries out two natural experiments in El Paso, TX, to explore the effect of BRT stations on residential property values. A synthetic control methodology, which creates counterfactual groups for identifying matching controls, has been used. Transportation corridors are used as our spatial control pool. The results reveal a significant variation in the impact of BRTs on housing prices even within the same City. It appears that BRT may have greater benefits in lower-income neighborhoods and less popular housing markets.]]></description>
      <pubDate>Fri, 23 May 2025 15:34:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2516316</guid>
    </item>
    <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://trid.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://trid.trb.org/View/2459052</guid>
    </item>
    <item>
      <title>Partial Construction Report of a Bonded Concrete Overlay on IH-10, El Paso, and Guide for Expedited Bonded Concrete Overlay Design and Construction</title>
      <link>https://trid.trb.org/View/2449514</link>
      <description><![CDATA[Expedited bonded concrete overlays offer an economical alternative to rehabilitating concrete pavements. The construction of a bonded concrete overlay in El Paso has provided the opportunity to research pavement design, mix design, construction methods, and specification development for use in future overlay construction. This report documents the valuable information collected during the construction of the bonded concrete overlay on IH-10 in El Paso. Although this project did not proceed as an expedited overlay, it was planned and researched as such. Unfortunately, a combination of factors led to delamination in some areas of the overlay. This report identifies the causes of these delaminations that occurred during this construction and makes recommendations for future overlay construction. Project selection, design, construction, and quality control are addressed in an included guide for expedited bonded concrete overlays. Also addressed is the scheduling of the construction in such a way as to avoid marginal or severe environmental conditions. The methods presented in this report may be used to construct bonded concrete overlays that can be opened to traffic 12 to 24 hours after concrete placement.]]></description>
      <pubDate>Mon, 18 Nov 2024 17:16:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2449514</guid>
    </item>
    <item>
      <title>Prototype Data Dashboard for Multi-Source Transportation and Community Health Data Analytics</title>
      <link>https://trid.trb.org/View/2389918</link>
      <description><![CDATA[This study had a primary objective of creating a versatile and scalable data dashboard prototype that highlights transportation and community health data, using El Paso as a case study. The dashboard serves as a centralized hub for various data sources within the city, facilitating visual analysis to uncover the intricate connections between these two crucial domains. It’s important to note that the primary aim was not to develop a final product for the city, but rather to establish a proof-of-concept, engage potential users, and conduct scenario analysis. The true impact of this study is expected to extend beyond the creation of the dashboard itself, as it has the potential to influence significant city-wide or regional policy changes based on the valuable insights derived from the comprehensive data analysis. This initiative aims to provide a robust tool for decision-makers and stakeholders to make informed choices that could ultimately benefit the community’s transportation and health outcomes.]]></description>
      <pubDate>Thu, 22 Aug 2024 15:11:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389918</guid>
    </item>
    <item>
      <title>Quantification of Traffic-Related Emissions and Exposures at U.S.- Mexico Border Crossings Using Real-Time Portable Sensors</title>
      <link>https://trid.trb.org/View/2389835</link>
      <description><![CDATA[Air monitoring was conducted at the Bridge of the Americas (BOTA) in El Paso, Texas, using continuous Federal Equivalent Method (FEM) instruments for four criteria pollutants (PM₂.₅, PM₁₀, O₃, and NO₂) to assess exposure levels of facility operators and users of the BOTA. Concurrent monitoring of PM₂.₅ in the nearby community using low-cost sensors provided citizens with real-time pollution levels. Air dispersion modeling was conducted using seasonal traffic emission rates to predict PM₂.₅, PM₁₀, and NO₂ levels at the BOTA and the surrounding areas. Monitored average concentrations at the BOTA of PM₂.₅, O₃, and NO₂ were 2 percent higher, 15 percent lower, and 20 percent higher, respectively, than concentrations observed at a nearby reference station 0.4 km away. The dispersion modeling of wait-time effects at the BOTA showed that on-site air pollution reaches a maximum level when the queue length is 270 m and concentrations decrease tenfold as the cross-BOTA distance reaches 200 m. Modeled estimates indicate that individuals traveling along the pedestrian walkway experience 75 percent of the impact of the emissions relative to the concentrations inside the BOTA. Modeled estimates indicate that toll booth workers experience 66 percent of the pollutant concentrations estimated inside the traffic lanes of the BOTA. The modeled emissions contribute 51, 147, and 7 percent of the monitored all-period averaged PM₂.₅, PM₁₀, and NO₂ concentrations, respectively. Modeled concentration estimates provide a spatial heat map to assess the reach and direction of pollution exposure.]]></description>
      <pubDate>Sun, 30 Jun 2024 16:02:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389835</guid>
    </item>
    <item>
      <title>Railroad Investigation Report: Union Pacific Railroad Employee Fatality, El Paso, Texas, August 29, 2022</title>
      <link>https://trid.trb.org/View/2381668</link>
      <description><![CDATA[On August 29, 2022, about 9:14 p.m. local time, the conductor of Union Pacific Railroad train ISIEP 29 was killed during a shoving movement when two railcars of the train derailed in UP’s Alfalfa Yard in El Paso, Texas. The conductor was riding on the lead end of the first railcar when the train encountered a derail. The derail was placed on the yard lead earlier in the day to protect maintenance-of-way employees during an upcoming installation project. As the train entered the yard on the yard lead, the train encountered the derail device and two railcars derailed. One of these railcars overturned, landing on its side, then sliding into a residential property where it struck a natural gas line owned by Texas Gas Service. The railcar’s contact with the gas line did not result in a gas leak. The National Transportation Safety Board (NTSB) determined that the probable cause of the August 29, 2022, employee fatality was the failure of personnel to contact the employee-in-charge before granting train ISIEP 29 permission to enter the yard lead track. ​]]></description>
      <pubDate>Fri, 07 Jun 2024 16:59:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2381668</guid>
    </item>
    <item>
      <title>Enhancing Transit Access and Safety Through Equitable Micromobility Solution</title>
      <link>https://trid.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://trid.trb.org/View/2283488</guid>
    </item>
    <item>
      <title>Digital Twin Technologies Towards Understanding the Interactions between Transportation and other Civil Infrastructure Systems: Phase 2</title>
      <link>https://trid.trb.org/View/2265864</link>
      <description><![CDATA[The advent of Digital Twin (DT) technology signifies a significant stride towards the progressive transformation from physical to digital paradigms within the realm of civil engineering. Its predecessors, namely Computer-Aided Drafting (CAD) and Building Information Modeling (BIM), have revolutionized the industry by streamlining the documentation of designs, curtailing both time and cost investments. The primary objective of this research was to explore different ways to create Digital Twins for civil infrastructure and to explore the effectiveness of DT technology as a tool to create new visualizations and understand interactions between transportation and other related civil infrastructure systems. The authors used The University of Texas at El Paso (UTEP) campus as a living lab by creating DT models based on transportation network, structural modelling, and LiDAR scans of different parts of the campus. The transportation network and 3D model of the entire campus was combined for traffic simulation and real-time sensing at a roundabout, while the digital model of a pedestrian bridge was made for structural simulations with provisions for strain and tilt sensors. In addition, LiDAR scans of campus buildings were integrated into virtual reality (VR) applications for visualization in VR headsets. Multiple scenarios were tested for each DT to showcase how the technology can be applied to real world problems, resulting in greater ease of use and more informed design decisions. The project concluded with a stakeholder engagement workshop focused on utilizing DT technologies for research relevant to civil infrastructure in the El Paso region.]]></description>
      <pubDate>Mon, 30 Oct 2023 08:52:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2265864</guid>
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