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    <title>Transport Research International Documentation (TRID)</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>Transport Research International Documentation (TRID)</title>
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      <title>Terrestrial laser scanner for the analysis of airport pavement geometry</title>
      <link>https://trid.trb.org/View/1580400</link>
      <description><![CDATA[The knowledge of the geometric features of an airport’s pavement surface is essential to ensuring the safety and comfort of the driving users. For this purpose, it is important to find the most suitable survey methods and computation procedures for determining these geometric features and their evolution over time. In this study, the authors used a terrestrial laser scanner (TLS) to survey a stretch of a taxiway of an international airport. The authors designed the survey with the goal of defining the optimal parameters for the scans and the spacing between the TLS station points, combining high efficiency with data quality and accuracy. An algorithm for the semi-automatic extraction of the longitudinal and transverse profiles of the track from the digital elevation model (DEM) has been implemented. Longitudinal and cross slopes have been computed from the profiles using a linear fit, assessing the conformity of the values to the standards. The algorithm allows the verification of irregularities and the assessment of the severity of deviations from a linear trend. The authors' approach is suitable for obtaining an accurate reconstruction of the road surface that can be measured in post-processing and that is geo-referenced in a way that allows monitoring over time. The authors believe that the surveying technique that they analysed and assessed could improve the effectiveness of the measurements, and it could be used wherever pavement geometry control cannot be performed on discrete elements but rather a continuous approach is needed.]]></description>
      <pubDate>Tue, 05 Mar 2019 16:03:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1580400</guid>
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    <item>
      <title>Detecting and Classifying Roadway Pavement Cracks, Rutting, Raveling, Patching, and Potholes Utilizing Smartphones</title>
      <link>https://trid.trb.org/View/1495414</link>
      <description><![CDATA[Civil engineers face numerous challenges in monitoring roadway deterioration and in assuring roadway pavement maintenance to the preferred level of serviceability. The paper presents a data-driven framework and related field studies on the use of supervised machine learning and smartphone sensor technologies for the detection, classification and georeferencing of common roadway pavement surface anomalies. The study proposes a low-cost and automated method to obtain up-to-date information about roadway pavement surface anomalies, with the use of smartphones mounted on vehicles. Robust regression analysis and bagged trees classification models are used to compliment smartphone-based data collection. The technology for the suggested system is readily available and accurate, and can be utilized in crowd-sourced applications for pavement management systems (PMS) and geographical information system (GIS) implementations. Further, the proposed methodology has been field-tested (detection and classification of five types of pavement surface anomalies, exhibiting accuracy levels higher than 90%) and at this time it is expanded to include larger datasets and a bigger number of common roadway pavement surface defect types. The proposed system is of practical importance since it provides continuous information about roadway pavement surface condition which can be valuable for pavement management systems and public safety.]]></description>
      <pubDate>Tue, 13 Mar 2018 12:30:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/1495414</guid>
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    <item>
      <title>Earth-Referenced Aircraft Navigation and Surveillance Analysis</title>
      <link>https://trid.trb.org/View/1414856</link>
      <description><![CDATA[This document addresses a basic function of aircraft (and other vehicle) surveillance and navigation systems analyses — quantifying the geometric relationship of two or more locations relative to each other and to the earth. Here, geometry means distances and angles, including their projections in a defined coordinate frame. Applications that fit well with these methods include (a) planning a vehicle’s route; (b) determining the coverage region of a radar or radio installation; and (c) calculating a vehicle’s latitude and longitude from measurements (e.g., of slant- and spherical-ranges or range differences, azimuth and elevation angles, and altitudes). The approach advocated is that the three-dimensional problems inherent in navigation/surveillance analyses should, to the extent possible, be re-cast as a sequence of sub-problems: Vertical-Plane Formulation; Spherical-Surface Formulation; Three-Dimensional Vector Formulation; and Non-Linear Least-Squares (NLLS) Formulation. These techniques are applied, in the context of a spherical earth, to a series of increasingly complex situations, starting with two problem-specific points (e.g., a route’s origin and destination) and extending to three or more points (e.g., an aircraft and multiple surveillance/navigation stations). Closed-form solutions are presented for measurements involving virtually every combination of ranges, pseudo ranges, azimuth/elevation angles and altitude. The Gauss-Newton NLLS methodology is employed to address the most complex situations. These include circumstances where there are more measurements than unknowns and/or the measurement ‘equations’ cannot be inverted analytically (including those for an ellipsoidal-shaped earth) and/or are not analytic expressions (e.g., involve empirical data).]]></description>
      <pubDate>Wed, 06 Jul 2016 13:14:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1414856</guid>
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    <item>
      <title>An application of the Sequential Monte Carlo to increase the accuracy of travel time estimation in urban areas</title>
      <link>https://trid.trb.org/View/1354549</link>
      <description><![CDATA[This paper presents an application of the Sequential Monte Carlo that will help to increase the accuracy of travel time estimations in historical data. The authors' estimation filter is based on the Monte Carlo Method and was modeled in such a way as to be applicable to their new kind of data in order to estimate travel time per section of road. The authors took into consideration the delay time while changing the sections to symbolize the delay due to traffic lights or crossroads. The authors worked on an urban zone of Rouen, a French city, to evaluate their application. In this application, information is collected from a specific Global Positioning System (GPS) that warns drivers of the location of both fixed and mobile speed radars. Unlike the classical GPS system, this system is characterized by the data flow frequency where the GPS data are received from the probe vehicles at one minute intervals. After receiving the data the authors apply the map matching method in order to correct the GPS errors. Also, the authors' geo-referencing system has special features; each road or section of road is formed by nodes and segments, and the intersection between each section is called a PUMAS point. The PUMAS Points are GPS coordinate points on a digital map which can be propagated or moved without cost, providing total flexibility to mesh a city or rural area. Overall the performance of the filter estimator is around 85% if the threshold is set at 50%.]]></description>
      <pubDate>Mon, 08 Jun 2015 16:00:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1354549</guid>
    </item>
    <item>
      <title>Development of a Pavement Management System</title>
      <link>https://trid.trb.org/View/1335499</link>
      <description><![CDATA[The goals of the project were (1) to develop a multimedia based highway information system, and (2) to evaluate the current practice of pavement management at the Arkansas State Highway and Transportation Department (AHTD), make recommendations, and calibrate the application of a pavement management system (PMS) for the State of Arkansas. Part One of the report presents the development of a multimedia service that can be applied in a state highway department environment. This Multimedia-based Highway Information System (MMHIS) utilizes state-of-the-art technologies in digital video, high-speed networking, and the video server. A data-synchronization algorithm was developed to dynamically display digital video frames along with traditional engineering data sets that contain information such as as-built data, pavement condition and performance, traffic safety, geometric features, and other infrastructure data. Geo-referencing capabilities were also developed into MMHIS. Part Two of the report presents the calibration of dTIMS® for AHTD. The data collected with the ARAN vehicle is used as input values for the PMS software, dTIMS®. The calibration of dTIMS® focused on the Interstate and NHS (National Highway System) of Arkansas. The following tasks were completed in this research: (1) segmentation of highway sections, (2) development of traffic loading history, (3) development of necessary performance prediction curves, (4) setting up dTIMS® for optimization analysis, and (5) documenting optimization runs for pavement rehabilitation with Arkansas data. Further updates as new data are collected are required for the PMS to be useful to the AHTD.]]></description>
      <pubDate>Mon, 22 Dec 2014 19:11:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1335499</guid>
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    <item>
      <title>Auto-Matching Traffic Message Channel (TMC) Paths and Travel Demand Model Network Links</title>
      <link>https://trid.trb.org/View/1287801</link>
      <description><![CDATA[Given the emerging availability of private-sector probe-based speed and travel time data, there is an increasing need to utilize such data to validate and improve travel demand models. One obstacle often hindering such utilization is that the probe data are usually geo-referenced by Traffic Message Channel (TMC) paths -- an industry standard for location referencing along road segments -- while a travel demand model has its own definition of network and links. Segmentation differences and directionality inconsistencies between the TMC paths and travel model network links are the two main challenges in matching the two location referencing systems.  This paper introduces a novel approach to overcome these challenges so that TMC path-based speeds and travel times can be transferred automatically to the travel demand model links. This approach can be applied to other highway network and TMC paths as long as they possess similar geometry.]]></description>
      <pubDate>Mon, 10 Mar 2014 09:24:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/1287801</guid>
    </item>
    <item>
      <title>Vehicular traffic lights priority system based on a geo-reference analysis</title>
      <link>https://trid.trb.org/View/1279529</link>
      <description><![CDATA[Globally, and as a result of increased population and its concentration in large cities, it is essential to improve mobility and promote the use of public transport; therefore, priority intelligent vehicle is one of the paths that leads to sustainable mobility in cities. One reads or hears in the media that it is necessary to encourage the use of public transport to the detriment of private cars to reduce air pollution; applying technological innovation and engineering, one can state that promoting the use of urban surface transport ensures  citizen timeliness, quality and reliability of service. Therefore, based on experience in implementation of different systems for vehicular priority, the authors define the Geo-referential analysis as the most effective method to achieve this. The introduction of vehicle priority system geo-referencing, allows not only prioritization of urban transport on the surface, but uses infrastructure to get the fire engines, ambulance and police the right of way at certain intersections in the city. The data was obtained in Spanish cities like San Sebastian and Albacete in order to demonstrate the effectiveness of this system. Specifically in this document the authors highlight the implementation of the priority system in the city of San Sebastián. It is the head of Spain in bus use, since it has the highest ratio of travelers per capita; each person makes 152.9 trips per year.]]></description>
      <pubDate>Mon, 23 Dec 2013 11:06:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/1279529</guid>
    </item>
    <item>
      <title>Evaluation and Development of Unmanned Aircraft (UAV) for DOT Needs</title>
      <link>https://trid.trb.org/View/1257235</link>
      <description><![CDATA[This research involved the use of high-resolution aerial photography obtained from Unmanned Aerial Vehicles (UAV) to aid UDOT in monitoring and documenting State Roadway structures and associated issues. Using geo-referenced UAV high resolution aerial photographic imagery, the project documented the before, during and after stages of the Southern Parkway construction near the new Saint George International airport, in addition to photographing and classifying wetland plant species in the Utah Lake wetland mitigation bank on the NE corner of Utah Lake.]]></description>
      <pubDate>Thu, 01 Aug 2013 11:01:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/1257235</guid>
    </item>
    <item>
      <title>The Alpcheck2 Project –Development of a Transport Decision Support System Using a Common Anchor Network</title>
      <link>https://trid.trb.org/View/1216914</link>
      <description><![CDATA[Alpcheck2 is a project executed in the framework of the alpine space programme of INTERREG. The projects main output will be a transport decision support system, allowing decision makers for trans-alpine traffic to access various data from different sources. A common georeferencing system will enable the use of data from different regions in a combined and consolidated way. This system will make use of a transportation network that is capable of linear referencing to combine the different data sources. The network serves as an “anchor” to link different networks and data. The anchor network has been created by combining and consolidating different networks. It consists of a network with unique IDs and a logical network for the linear referencing.]]></description>
      <pubDate>Mon, 22 Oct 2012 09:14:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/1216914</guid>
    </item>
    <item>
      <title>Evaluation and Development of Unmanned Aircraft (UAV) for UDOT Needs</title>
      <link>https://trid.trb.org/View/1147966</link>
      <description><![CDATA[This research involved the use of high-resolution aerial photography obtained from Unmanned Aerial Vehicles (UAV) to aid the Utah Department of Transportation (UDOT) in monitoring and documenting State Roadway structures and associated issues. Using geo-referenced UAV high resolution aerial photographic imagery, the project documented the before, during and after stages of the Southern Parkway construction near the new Saint George International airport, in addition to photographing and classifying wetland plant species in the Utah Lake wetland mitigation bank on the North East corner of Utah Lake.]]></description>
      <pubDate>Wed, 22 Aug 2012 15:37:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1147966</guid>
    </item>
    <item>
      <title>Airborne Traffic Flow Data and Traffic Management</title>
      <link>https://trid.trb.org/View/1112845</link>
      <description><![CDATA[Imagery collected from airborne platforms has long been used to document the evolution of traffic congestion over time and across extended areas. The authors have documented such published research dating all the way back to 1927, and these activities continued in various periods of activity up through the late 1980s. Beginning in the late 1990s, many important ideas, new and old, on the use of airborne imagery for traffic analysis were investigated and tested in the field by a number of research teams around the world. Through detailed image processing techniques, this imagery can be used to automatically determine traffic flow measures. Prototype software tools have been developed to automatically estimate queue lengths at intersections, to estimate vehicle speeds, and to estimate vehicle flows and densities. Similar research has integrated traffic flow data from airborne imagery into formal data collection programs, where the data from the imagery is fused with ground detector data to enhance the estimates and forecasts of traffic flows. Some of these research teams have also “architectured” approaches to automatically, in real-time, georeference images from remote cameras for managing traffic. This is done by integrating the imagery with information on the height, location, and orientation of the camera. Using these camera data, in combination with a geographic representation (latitude–longitude) of the area to be studied, lead to an explicit way to georeference the road and vehicle locations. Absolute values of vehicle positions, speeds, accelerations, decelerations, and lane changes can be determined. There have been a wide variety of experiments in this area; these tests have extracted individual vehicle trajectories from digital video imagery. Uses of the obtained airborne traffic data are many: (a) off-line analyses can be used for transportation planning purposes, (b) online, real-time analyses can be used for traffic management, especially in areas where ground sensors are not available and for large-scale incidents, and (c) one can develop data sets of vehicle trajectories for use in the calibration–validation of micro-, meso-, and macroscopic traffic flow models.]]></description>
      <pubDate>Mon, 15 Aug 2011 11:04:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1112845</guid>
    </item>
    <item>
      <title>Transferring Community-Based, Active Transportation GIS Assessment Tools Nationwide</title>
      <link>https://trid.trb.org/View/1106556</link>
      <description><![CDATA[“Livability” has recently been declared one of four top priorities by the Secretary of the U.S. Department of Transportation (USDOT), and the USDOT, the Environmental Protection Agency (EPA), and the Department of Housing and Urban Development (HUD) have entered into an historic partnership to address the issue. Ultimately, this term refers to the quality of life within one’s community and the ease, comfort, and joy with which one can access places he or she wants to go. For most Americans, their neighborhoods have been designed to predominantly accommodate the automobile, and more active forms of transportation such as walking and biking have been neglected. Previous and current Oregon Transportation Research and Education Consortium (OTREC) work has developed a suite of geographic informaiton system (GIS) tools focused on assessing these environments in a fine-scaled, field-based, geo-referenced format so that local communities can better identify gaps in their networks and work to make appropriate improvements. This work explicitly focuses on the role and capacity of a general citizenry to conduct built environment active transportation audits and engage in facilitated discussions about the data and maps resulting from their community data collection.]]></description>
      <pubDate>Tue, 19 Jul 2011 08:15:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/1106556</guid>
    </item>
    <item>
      <title>Development of Georeferenced System for Machine-Controlled Construction Equipment</title>
      <link>https://trid.trb.org/View/1091813</link>
      <description><![CDATA[Machine controlled construction equipment continues to garner support from the construction industry due to shortages of skilled labor, constant technological advances and the importance of construction to the overall economy. However, in order to achieve machine control, reliable geo-referencing/positioning of the equipment and end-effector must be achieved. This can also lead to several other benefits, including safety on the construction site, optimization of construction tasks, precision construction and real-time updating of construction records. A methodology for a reliable, stand-alone, real-time geo-referencing system for construction equipment is proposed in this paper. The method consists of a fully integrated Differential Global Positioning System (DGPS)/Inertial Navigation System (INS) to geo-reference the main body of the construction equipment. Inertial Measurement Units (IMU) attached to each operational joint will provide orientation information. This information is used in the Denavit-Hartenberg (DH) convention, describing the position of the equipment in 3D space, to create a link between the geo-referenced main body of the equipment and end-effector. There are distinct advantages to this type of approach. It is a more complicated, yet cost-effective, system because lower grade (less expensive) IMUs can be made to perform as more stable IMUs by constant re-calibration using DGPS measurements. It is an autonomous system, unaided by line-of-sight survey based equipment (i.e. total stations or laser levels). Finally, it creates a unified model approach for geo-referencing multi-sensor systems that can be applied without accounting for a different set of parameters for each sensor. This is especially advantageous when dealing with construction equipment with varying degrees of freedom.]]></description>
      <pubDate>Mon, 28 Mar 2011 07:45:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/1091813</guid>
    </item>
    <item>
      <title>ITS 2015 – Masterplan for ITS Implementation in Bavaria</title>
      <link>https://trid.trb.org/View/911445</link>
      <description><![CDATA[The Bavarian Road Authorities have conducted several research projects regarding intelligent transportation system (ITS) in the past years. One of the outcomes of those projects was the experience that all ITS services have to be placed on a common technical platform. Thus the multimodal georeferencing system INTREST was developed. After the extensive research phase, the phase of technical implementation of the project results was started with the foundation of the public-private partnership agency VIB (“Transport Information Agency Bavaria”), which was tendered to run all traffic information services in Bavaria the coming 10 years. It has the task to provide traffic information for the public and to assist the Bavarian Road Administration in fulfilling its legal obligations for traffic control and road planning. Starting from this organizational structure, the future developments in Bavaria’s ITS will be implemented stepwise into the running systems. For the implementation of these developments and to cover future plans and visions of a ITS master plan will be elaborated.]]></description>
      <pubDate>Wed, 27 Jan 2010 08:18:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/911445</guid>
    </item>
    <item>
      <title>ITS 2015 - Masterplan for ITS Implementation in Bavaria</title>
      <link>https://trid.trb.org/View/903124</link>
      <description><![CDATA[The Bavarian Road Authorities have conducted several research projects regarding ITS projects in the past years. One of the outcomes of those projects was the experience that all ITS services have to be placed on a common technical platform. Thus the multimodal georeferencing system INTREST was developed. After the extensive research phase, the phase of technical implementation of the project results was started with the foundation of the public-private partnership agency VIB (“Transport in Bavaria”), which was tendered to run all traffic information services in Bavaria the coming 10 years. Starting from this organizational structure, the future developments in Bavaria’s ITS will be implemented stepwise into the running systems. For the implementation of these developments and to cover future plans and visions an ITS master plan will be elaborated.]]></description>
      <pubDate>Tue, 17 Nov 2009 14:59:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/903124</guid>
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