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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>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <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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      <title>A Note on Mid Rules Optimization of Distance on the Sphere</title>
      <link>https://trid.trb.org/View/1400343</link>
      <description><![CDATA[In this article Mid-latitude and mid-longitude rules are used to find the free turning point along the Great Circle ensuing optimized distance. Namely, to reach Great Circle vertex with two rhumb line legs ensuing optimized distance, an initial rhumb line course equal to the orthodromic course at Mid-latitude may be used. The initial course is thereupon optimized by the incremental value steps. Alternatively, mid-longitude point at the same Great Circle can be beneficial in optimizing process. Optimized distance is achieved if the rhumb line course is altered towards the vertex at the orthodrome-loxodrome intersection point. © Faculty of Maritime Studies Rijeka, 2015.]]></description>
      <pubDate>Mon, 21 Mar 2016 16:47:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1400343</guid>
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    <item>
      <title>The age of sail : a time when the fortunes of nations and lives of seamen literally turned with the winds their ships encountered at sea</title>
      <link>https://trid.trb.org/View/1085451</link>
      <description><![CDATA[]]></description>
      <pubDate>Thu, 30 Dec 2010 10:19:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1085451</guid>
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    <item>
      <title>A Primer on the Global Positioning System and Its Application in Accident Reconstruction</title>
      <link>https://trid.trb.org/View/930597</link>
      <description><![CDATA[This article brings readers up-to-date on the global positioning system (GPS).  The authors discuss the history of the GPS, its operation, how commercially available GPS receivers interact with the satellite constellation, how GPS receivers present positional output, and the accuracy of the data obtained with GPS.  The discussion is framed from the perspective of the applications of GPS in accident reconstruction.  The article includes five case examples of the use of GPS data in accident reconstruction scenarios.  The authors then report on their field research, undertaken to evaluate the use of GPS in accident reconstruction.  The study used four handheld GPS receivers from three different manufacturers and took place in a series of locations in the metropolitan San Antonio (Texas) area.  The study found that the power up mode and initial position fix for the receivers can take significant time.  It can even require up to 15 minutes for the receiver to download almanac data if it has been turned off for some time prior to use.  Each GPS receiver reports a position fix nearly equal to the actual latitude and longitude values for the actual position, but, over time, the reported output tends to vary, so there was never an actual "static" position fix.  The authors conclude that it is appropriate to rely on GPS for an accurate representation of a general area; however, it is inappropriate to utilize GPS to define a specific point (such as point of impact in a collision).]]></description>
      <pubDate>Thu, 16 Sep 2010 12:43:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/930597</guid>
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    <item>
      <title>Geocoding Police Collision Report Data from California: A Comprehensive Approach</title>
      <link>https://trid.trb.org/View/925043</link>
      <description><![CDATA[This article considers the usefulness of geocoding police collision report data.  Collision geocoding is the process of assigning geographic descriptors, usually latitude and longitude coordinates, to a traffic collision record.  In this study the authors created a geocoded database of all police-reported, fatal and severe injury collisions in the California Statewide Integrated Traffic Records System (SWITRS) for years 1997-2006 for use by public agencies.  Prior to this, the police record collision location based on highway postmile markers or street intersections.  The authors describe the multi-step process needed to create the geocoded database: pre-processing to clean and standardize street name information; creation of a state highway network with postmile values; incorporation of the offset directions and distances; and intersection and address geocoding.  A total of 142,007 fatal and severe injury collisions were identified in SWITRS. The geocoding match rate was 99.8% for postmile-coded collisions and 86% for intersection-coded collisions. The overall match rate was 91%.  The authors conclude with a discussion of the practical uses of this geocoded collision data, including studies of collision clustering on the highway system, which is the associations between collision occurrence and a variety of variables on environmental and social characteristics, including housing and personal demographics, alcohol outlets, schools, and parks.]]></description>
      <pubDate>Thu, 26 Aug 2010 08:22:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/925043</guid>
    </item>
    <item>
      <title>Geospatial Analysis of Rural Motor Vehicle Traffic Fatalities</title>
      <link>https://trid.trb.org/View/908469</link>
      <description><![CDATA[In recent years, on average about 44 percent of traffic fatalities occurred in urban areas. The National Highway Traffic Safety Administration's Fatality Analysis Reporting System (FARS) codes the functional classification of land use by a binary indicator, i.e., if the location is a rural or urban area, as defined by the United States Census Bureau. However, this information is not enough to determine the spatial spread of the fatalities in the rural areas, i.e., are the fatalities occurring in suburban, exurban, or the outlying rural areas. The focus of this report is to determine the extent of fatalities that occur in rural areas that are close to urban areas. Some of these communities in rural areas that are close to urban areas have significant commuting ties with these urban areas. It would be of interest to law enforcement and highway safety planners involved in rural highway safety initiatives to quantify how many traffic fatalities occur in rural areas that are close to urban areas. FARS has begun reporting latitude and longitude information recently that facilitates the type of geospatial analysis required to quantify fatalities that occur near urban areas as a function of distance from the urban boundaries. The distances (buffer distances) used in this spatial analysis are 2.5, 5.0, 7.5, and 10.0 miles. While 44 percent of all traffic fatalities occur in urban areas, the percentage increases to 63 percent in an area that also includes the rural area within 2.5 miles of the urban boundary. The percentage increases to 73 percent 5.0 miles out, 81 percent 7.5 miles out, and 86 percent 10 miles out. In summary, about three-quarters of all traffic fatalities in the Nation occurred in an area that includes all the urban areas along with the rural areas that are within 5 miles of the urban boundaries.]]></description>
      <pubDate>Tue, 12 Jan 2010 16:44:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/908469</guid>
    </item>
    <item>
      <title>ANALYSIS OF TRAVEL ROUTE DATA FROM A SYSTEM EFFICIENCY PERSPECTIVE</title>
      <link>https://trid.trb.org/View/754915</link>
      <description><![CDATA[Traveler route choice behavior is the cornerstone of numerous advanced traffic management technologies.  Yet, few datasets of actual travel routes have been collected and analyzed.  There are two specific objectives of the analysis work conducted in this NEUTC research project (the data collection was only partially funded by this project).  The first was to advance the methodological aspects of using GPS to collect route data, including constructing the spatial model that automatically identifies trip ends in the large-scale continuous GPS data stream.  This work makes use of 10-days of in-vehicle travel routes collected from 256 households using Global Positioning System (GPS) receivers from 2002 to 2003 in Lexington, Kentucky (population 250,000). Information for each vehicle, such as speed, latitude, longitude, and heading was recorded every second or every five seconds (depending on the power feature in the particular vehicle and the corresponding settings of GPS devices).  This dataset was used for the second project objective: to estimate routing efficiency and selection patterns by determining if route choice is influenced by attitudes, travel habits, roadway characteristics, congestion, or a combination of a few or all of these elements.  Surveys were collected from 524 drivers in the 256 households.  This study has demonstrated the importance of validating GPS trip dividing methods against known trip start and end locations in order to defensibly measure the accuracy of algorithms.  The relatively small range of parameters tested here resulted in a significant variation in accuracy and error results, indicating that trip division is highly sensitive to the parameters used.  Some recent studies have found GPS dramatically increases the number of trips reported by travelers. However, it is possible that the method or combination of parameters used to divide the GPS data stream into individual trips significantly affected these trip rate estimates. Therefore, caution should be exercised in interpreting GPS travel data.  The analysis of the route choice data in the follow-up surveys indicates that a wide variety of data types influence route consistency: travel habit variables, attitudinal variables, route characteristic variables, and demographic variables. Demographic and route characteristic variables have less influence in some route models suggesting that attitudinal data may be valuable for predicting specific routes.]]></description>
      <pubDate>Wed, 27 Apr 2005 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/754915</guid>
    </item>
    <item>
      <title>COMPUTER PROGRAM FOR POINT LOCATION AND CALCULATION OF ERROR (PLACER)</title>
      <link>https://trid.trb.org/View/725538</link>
      <description><![CDATA[A program designed for point location and calculation of error (PLACER) was developed as part of the Quality Assurance Program of the Federal Highway Administration/U.S. Geological Survey (USGS) National Data and Methodology Synthesis (NDAMS) review process. The program provides a standard method to derive study-site locations from site maps in highway-runoff, urban-runoff, and other research reports. This report provides a guide for using PLACER, documents methods used to estimate study-site locations, documents the NDAMS Study-Site Locator Form, and documents the FORTRAN code used to implement the method. PLACER is a simple program that calculates the latitude and longitude coordinates of one or more study sites plotted on a published map and estimates the uncertainty of these calculated coordinates. PLACER calculates the latitude and longitude of each study site by interpolating between the coordinates of known features and the locations of study sites using any consistent, linear, user-defined coordinate system. This program will read data entered from the computer keyboard and (or) from a formatted text file, and will write the results to the computer screen and to a text file. PLACER is readily transferable to different computers and operating systems with few (if any) modifications because it is written in standard FORTRAN. PLACER can be used to calculate study site locations in latitude and longitude, using known map coordinates or features that are identifiable in geographic information data bases such as USGS Geographic Names Information System, which is available on the World Wide Web.]]></description>
      <pubDate>Sat, 13 Dec 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/725538</guid>
    </item>
    <item>
      <title>STAND ALONE MULTIPLE UNIT TRACKING SYSTEM; PATENT</title>
      <link>https://trid.trb.org/View/406000</link>
      <description><![CDATA[A stand alone multiple unit tracking system which utilizes a packet radio link to periodically transmit information identifying the geographic position of ships, aircraft and other land mobile vehicles.  The stand alone multiple unit tracking system comprises a base station, relay stations and a plurality of remote stations placed on board ships, aircraft or the like. The remote stations transmit latitude and longitude position information to the base station through relay stations, if required, using packet radio techniques.]]></description>
      <pubDate>Mon, 03 Oct 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/406000</guid>
    </item>
    <item>
      <title>A CALCULATOR PROGRAM FOR MIXING MERCATOR AND GREAT CIRCLE SAILINGS</title>
      <link>https://trid.trb.org/View/155761</link>
      <description><![CDATA[The Navigation Department, Defense Mapping Agency Hydrographic/Topographic Center (DMAHTC) has developed a calculator program, self-contained on one magnetic card, which automatically determines course, distance, and total run in Mercator and Great Circle Sailings. This program will list Great Circle positions every 10 deg of longitude and then print course and distance for each leg. Labels designating latitudes and longitudes, and program sections are also shown. The entire program is controlled by six label keys and can be shifted between Mercator and Great Circle at will. It is prepared on a programmable TI-59 with Marine Navigation Module software and printer capability. The program is in use at DMAHTC for compiling distance tables, and navigational publications and answering public inquiries. The following data are incorporated in this article: General Information, Mercator Computation, Great Circle Computation, Great Circle Positions, Great Circle Course Computation, Program Data, and Special Considerations. (Author)]]></description>
      <pubDate>Mon, 27 Oct 1980 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/155761</guid>
    </item>
    <item>
      <title>DEVELOPMENT OF ANALYTICAL AND EMPIRICAL SYSTEMS FOR PARAMETRIC STUDIES OF DESIGN AND FABRICATION OF WELDED STRUCTURES</title>
      <link>https://trid.trb.org/View/69878</link>
      <description><![CDATA[Part I of the report covers the development of a monograph entitled 'Analysis of Design and Fabrication of Welded Structures.' The monograph deals with the prediction of stresses, strains and other effects produced by welding. Part II covers the development of analytical means for predicting and controlling weld distortion in welded aluminum structures. Distortion in welded structures is caused by three fundamental dimensional changes, namely transverse shrinkage, longitudinal shrinkage and angular change. During the fabrication of actual structures, such as ships, airplanes and buildings which have various types of joints, these dimensional changes are combined. Therefore, shrinkage distortion that occurs in structures can be extremely complex. After a brief introduction, Section 2.2 discusses thermal stresses during welding, residual stresses and distortion in a general manner. The subsequent sections up to Section 2. 6 discuss the analytical and experimental investigations carried out at M.I.T. on the prediction of various fundamental types of distortion. Finally, Section 2. 7 deals with methods of distortion reduction, as they were tested by various investigators at M.I.T. (Author)]]></description>
      <pubDate>Wed, 28 Jun 1978 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/69878</guid>
    </item>
    <item>
      <title>PROCEDURE FOR LOCATING 10 KM UTM GRID ON ALABAMA COUNTY GENERAL HIGHWAY MAPS</title>
      <link>https://trid.trb.org/View/30458</link>
      <description><![CDATA[Each county highway map has a geographic grid of degrees and tens of minutes in both longitude and latitude in the margins and within the map as intersection crosses. These will be used to locate the universal transverse mercator (UTM) grid at 10 km intervals. Since the maps used may have stretched or shrunk in height and/or width, interpolation should be done between the 10 min intersections when possible. A table of UTM coordinates of 10 min intersections is required and included. In Alabama, all eastings are referred to a false easting of 500,000 m at 87 deg W longitude (central meridian, CM). (Author)]]></description>
      <pubDate>Wed, 04 Feb 1976 00:00:00 GMT</pubDate>
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