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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Pedestrian Tracking Using Online Boosted Random Ferns Learning in Far-Infrared Imagery for Safe Driving at Night</title>
      <link>https://trid.trb.org/View/1441016</link>
      <description><![CDATA[Pedestrian-vehicle accidents that occur at night are a major social problem worldwide. Advanced driver assistance systems that are equipped with cameras have been designed to automatically prevent such accidents. Among the various types of cameras used in such systems, far-infrared (FIR) cameras are favorable because they are invariant to illumination changes. Therefore, this paper focuses on a pedestrian nighttime tracking system with an FIR camera that is able to discern thermal energy and is mounted on the forward roof part of a vehicle. Since the temperature difference between the pedestrian and background depends on the season and the weather, the authors therefore propose two models to detect pedestrians according to the season and the weather, which are determined using Weber–Fechner's law. For tracking pedestrians, the authors perform real-time online learning to track pedestrians using boosted random ferns and update the trackers at each frame. In particular, the authors  link detection responses to trajectories based on similarities in position, size, and appearance. There is no standard data set for evaluating the tracking performance using an FIR camera; thus, the authors created the Keimyung University tracking data set (KMUTD) by combining the KMU sudden pedestrian crossing (SPC) data set [21] for summer nights with additional tracking data for winter nights. The KMUTD contains video sequences involving a moving camera, moving pedestrians, sudden shape deformations, unexpected motion changes, and partial or full occlusions between pedestrians at night. The proposed algorithm is successfully applied to various pedestrian video sequences of the KMUTD; specifically, the proposed algorithm yields more accurate tracking performance than other existing methods.]]></description>
      <pubDate>Wed, 15 Feb 2017 17:03:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1441016</guid>
    </item>
    <item>
      <title>Night watch</title>
      <link>https://trid.trb.org/View/1363187</link>
      <description><![CDATA[Night vision systems play a crucial role in the safety of driving in the dark; drivers can be alerted to people and animals ahead of them with passive far infrared technology. Night vision systems generate an alert well in advance of a collision and help the driver to completely avoid a dangerous situation. The two types of night vision technology are active near infrared (ANI) and passive far infrared (PFI). ANI systems feature an infrared light source that is integrated into the headlights. However, current ANI systems can have difficulty distinguishing between objects, people and animals. PFI systems detect thermal radiation emitted by objects in the field of view and are not affected by glare from oncoming traffic. A discussion of the technology is presented in this article. The Japan New Car Assessment Program (NCAP) and Euro NCAP have started taking these systems into consideration.]]></description>
      <pubDate>Tue, 28 Jul 2015 15:50:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1363187</guid>
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    <item>
      <title>Night-time pedestrian classification with histograms of oriented gradients-local binary patterns vectors</title>
      <link>https://trid.trb.org/View/1342056</link>
      <description><![CDATA[The use of night vision systems in vehicles is becoming increasingly common, not just in luxury cars but also in the more cost sensitive sectors. Numerous approaches using infrared sensors have been proposed in the literature to detect and classify pedestrians in low visibility situations. However, the performance of these systems is limited by the capability of the classifier. This paper presents a novel method of classifying pedestrians in far-infrared automotive imagery. Regions of interest are segmented from the infrared frame using seeded region growing. A novel method of filtering the region growing results based on the location and size of the bounding box within the frame is described. This results in a smaller number of regions of interest for classification, leading to a reduced false positive rate. Histograms of oriented gradient features and local binary pattern features are extracted from the regions of interest and concatenated to form a feature for classification. Pedestrians are tracked with a Kalman filter to increase detection rates and system robustness. Detection rates of 98%, and false positive rates of 1% have been achieved on a database of 2000 images and streams of video; this is a 3% improvement on previously reported detection rates.]]></description>
      <pubDate>Mon, 09 Feb 2015 10:44:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1342056</guid>
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    <item>
      <title>Enhanced Night Visibility Series, Volume XIV: Phase III—Study 2: Comparison of Near Infrared, Far Infrared, and Halogen Headlamps on Object Detection in Nighttime Rain</title>
      <link>https://trid.trb.org/View/782630</link>
      <description><![CDATA[Enhanced Night Visibility Series Phase III, Study 2 (rainy weather) was performed following the same procedures used for Phase III, Study 1 (clear weather).  Study 2 served to expand the knowledge of how current vision enhancement systems can affect detection and recognition of different types of objects while driving during adverse weather, specifically during rainy conditions.  The empirical testing for this study was performed on the Virginia Smart Road; the rain was controlled by weather-making equipment.  Fifteen participants were involved in the study.  A 4 by 8 by 3 mixed factorial design was used to investigate the effects of different types of vision enhancement systems, different types of objects on the roadway, and driver's age on detection and recognition distances; subjective evaluations also were obtained for the different vision enhancement systems.  The results of the empirical testing suggest that well-designed infrared (IR) systems are consistently associated with often significantly longer detection distances for most types of pedestrian objects during rainy conditions.  In particular, the use of the near IR (NIR) systems resulted in earlier detection of nearly all tested pedestrian types than did the use of either far IR (FIR) or baseline halogen (HLB) systems.  The exception to this finding is the case in which the pedestrian is on the right side of a right [1,250-m (4,101-ft) radius] curve.  In this case, the NIR system was associated with similar or shorter (though not significantly so) detection distances than the FIR and HLB systems.  Drivers in this study detected the nonpedestrian object (tire tread) at similar distances regardless of the headlamp system in use (NIR, FIR, or HLB).  This indicates that there is no significant loss in detection distance for small, low-contrast objects (such as tire treads) among the types of headlamps tested in this study.  All of these findings appear to be applicable regardless of driver age.  Subjective comments by the drivers in this study tend to be consistent with the objective results discussed above.]]></description>
      <pubDate>Thu, 01 Jun 2006 00:11:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/782630</guid>
    </item>
    <item>
      <title>Enhanced Night Visibility Series, Volume XIII: Phase III—Study 1: Comparison of Near Infrared, Far Infrared, High Intensity Discharge, and Halogen Headlamps on Object Detection in Nighttime Clear Weather</title>
      <link>https://trid.trb.org/View/782628</link>
      <description><![CDATA[Phase III—Study 1 was performed to further explore findings on far infrared (FIR) systems from Phase II, to investigate near infrared (NIR) and high intensity discharge (HID) technologies, and to investigate detection and recognition of retroreflective infrastructure components.  The empirical testing for this study was performed at the Virginia Smart Road testing facility during clear weather conditions.  A total of 18 participants were involved in the study.  A 6 by 3 by 17 mixed-factorial design was used to investigate the effects of 6 different types of vision enhancement systems, 3 age groups, and 17 object presentations on detection and recognition distances; subjective evaluations were obtained for the different systems as well.  The results of the empirical testing suggest that infrared (IR) systems, when designed correctly, can provide pedestrian detection benefit in clear weather, particularly for pedestrians in dark clothing and veiled in the glare of oncoming headlamps.  A wider field of view display appears to facilitate detection in curves of 1,250-m radius.  Retroreflective objects may be detected earlier in an NIR display, but require direct visual observation to recognize the object or read signage.  HID systems did not provide detection benefit over the baseline halogen headlamps tested.]]></description>
      <pubDate>Thu, 01 Jun 2006 00:11:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/782628</guid>
    </item>
    <item>
      <title>Pedestrian Detection with Night Vision Systems Enhanced by Automatic Warnings</title>
      <link>https://trid.trb.org/View/767803</link>
      <description><![CDATA[This experiment compared pedestrian detection using far-infrared (FIR) and near-infrared (NIR) night vision systems, combined with automatic warnings at one of two distances or no warning at all.  Sixteen subjects (eight younger than 30 years and eight older than 60 years) pressed a button as soon as they saw a pedestrian on a night vision system in the center console of a vehicle simulator.  In addition, they performed a concurrent simulated steering task that required almost continuous viewing of the forward scene, similar to real driving.  As in a previous experiment (Tsimhoni, Bargman, Minoda, and Flannagan, 2004), detection distances with FIR systems were substantially greater than with NIR systems.  Detection distances with both systems were shorter than in the previous experiment by about 20 m, probably because of the addition of simulated steering in the present experiment.  The automatic visual warning was a blue rectangle that zoomed in on the pedestrian in the video display.  In the long-distance condition, it was presented when the pedestrian was 150 m away.  Detection distance and accuracy for both night vision systems increased, but the effects were more prominent for the NIR system.  Automatic warnings at 75 m improved performance with NIR but worsened performance with FIR, perhaps because in some trials subjects waited for the automatic warning before responding.  Subjective ratings of mental workload and of effort were higher for NIR than for FIR, but the addition of automatic warnings did not decrease perceived workload significantly.  Overall, automatic visual warnings based on image processing were effective in increasing accuracy and detection distance for pedestrians except when short-distance warnings were used with the FIR system.]]></description>
      <pubDate>Thu, 22 Dec 2005 09:25:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/767803</guid>
    </item>
    <item>
      <title>PEDESTRIAN DETECTION WITH NEAR AND FAR INFRARED NIGHT VISION ENHANCEMENT</title>
      <link>https://trid.trb.org/View/753548</link>
      <description><![CDATA[Current headlighting and road lighting are only partly effective in reducing the risk of driving at night.  Various forms of night vision enhancement systems, using a variety of sensing technologies, are being developed to further reduce this risk. Two major sensing technologies are receiving particular development interest and are both currently available on new vehicles:  far infrared (FIR) systems, which generate images by passively detecting thermal emissions from objects and surfaces in the road scene, and near infrared (NIR) systems, which actively illuminate the scene in the near infrared spectrum and capture the reflected radiation.  The images generated by these systems, and the ways they are used by drivers, are expected to differ.  There is evidence that the major safety problem caused by darkness is increased risk of pedestrian collisions.  Because pedestrians are usually prominent among far infrared sources in roadway scenes, their detection may be especially enhanced in FIR views.  To compare pedestrian detection in NIR and FIR views, a test vehicle equipped with each type of system was driven at night on several roads with pedestrians standing along the route.  Video clips, recorded from both systems simultaneously, were later shown in a laboratory setting to 16 subjects (eight younger than 30 years and eight older than 60 years).  Subjects pressed a button as soon as they saw each pedestrian.  Detection distances with FIR were significantly greater than with NIR.  Younger subjects had greater detection distances than did older subjects, and both age groups had greater detection distances with FIR.  The effectiveness of NIR and FIR systems can be expected to depend on the details of implementation as well as any inherent advantages of either technology.  To the extent that the two systems used in this experiment reasonably represent the respective technologies, the results support the expected enhancement of pedestrian detection in FIR systems.]]></description>
      <pubDate>Tue, 08 Mar 2005 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/753548</guid>
    </item>
    <item>
      <title>INVESTIGATIONS INTO AUTOMATIC INTERPRETATIONS OF TERRAIN FEATURES</title>
      <link>https://trid.trb.org/View/119083</link>
      <description><![CDATA[INVESTIGATIONS INTO METHODS TO QUANTIFY AND AUTOMATICALLY IDENTIFY THE ELEMENTS OF TONE AND TEXTURE IN THE IDENTIFICATION OF TERRAIN FEATURES ARE DESCRIBED. MEASUREMENTS OF THE ELEMENT OF TONE AND TEXTURE WERE PERFORMED WITH A DENSITOMETER ADAPTED TO OBTAIN CONTINUOUS SCANS. MEASUREMENTS WERE PERFORMED ON ULTRAVIOLET THROUGH FAR INFRARED IMAGERY AND SPECTRAL RESPONSE SIGNATURES WERE DEVELOPED FOR VARIOUS TARGET MATERIALS. FACTORS INVESTIGATED INCLUDED: (1) EFFECTIVE FILM TYPES AND FILTERS, (2) SEASONAL EFFECTS, (3) APERTURE SIZE, AND (4) SCALE. A TECHNIQUE WAS DEVELOPED FOR THE PREPARATION OF ISOCHROMAL MAPS FROM DENSITOMETRIC SCANS ON COLOR PHOTOGRAPHY. EFFORTS TO DEVELOP DIAGNOSTIC PATTERNS FOR VARIOUS TERRAIN FEATURES FROM MEASUREMENTS ON A SINGLE FILM TYPE WERE NOT SUCCESSFUL. ANALYSIS OF SPECTRAL RESPONSE CURVES DEVELOPED FROM MULTICHANNEL IMAGERY INDICATE THAT THIS APPROACH OFFERS THE GREATEST POTENTIAL FOR DELINEATING TERRAIN FEATURES. THE TECHNIQUE DEVELOPED FOR ISOCHROMAL MAPPING OFFERS A METHOD FOR AUTOMATICALLY MAPPING VARIOUS TONAL PATTERNS PRESENT ON COLOR PHOTOGRAPHY.]]></description>
      <pubDate>Sun, 15 Aug 2004 02:11:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/119083</guid>
    </item>
    <item>
      <title>NIGHT VISION ENHANCEMENT SYSTEMS: WHAT SHOULD THEY DO AND WHAT MORE DO WE NEED TO KNOW?</title>
      <link>https://trid.trb.org/View/725562</link>
      <description><![CDATA[Night vision enhancement systems (NVES), which use infrared (IR) cameras, are designed to supplement the visibility provided by standard headlamps.  There are two main NVES systems: active, near infrared (NIR) systems, which require an IR source but give a complete picture of the scene in front of the driver; and passive, far infrared (FIR) systems, which do not need an IR source but only enhance relatively warm objects (such as people and animals).  There are three main display alternatives: a contact analog display with the camera view superimposed on the direct view of the road by means of a head-up display (HUD), a separate HUD on the top of the dashboard, and a head-down display (HDD) in the dashboard.  This report analyzes what a NVES should do to improve night visibility based on night crash statistics, driver vision and visibility conditions in night driving, driver tasks and behavior, technological approaches, costs, and regulations.  Potential problems with using NVES are also discussed.  Finally, issues requiring future research are presented.  The six main questions that need to be answered concerning NVES are: What kind of information should be presented? To whom should the information be presented? Which technological approach should be used? When should the information be presented? How should the information be presented? Where should the information be presented?]]></description>
      <pubDate>Fri, 19 Dec 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/725562</guid>
    </item>
    <item>
      <title>ICE SYMPOSIUM</title>
      <link>https://trid.trb.org/View/96089</link>
      <description><![CDATA[CONTENTS: THE WATER-ICE INTERFACE AS SEEN FROM THE LIQUID SIDE, WALTER DROST-HANSEN THE FAR INFRARED SPRECTRUM AND LONG-RANGE FORCES IN ICE, E. WALLEY, J. E. BERTIE PHASE TRANSITIONS OF WATER ADSORBED IN POROUS SOLIDS, G. LITVAN ON THE MOBILITY OF WATER MOLECULES IN THE TRANSITIONAL LAYER BETWEEN ICE AND A SOLID SURFACE, PIETER HOEKSTRA, R. D. MILLER THE INTERFACE BETWEEN ICE AND SILICATE SURFACES, DUWAYNE M. ANDERSON LIQUID-LIKE (TRANSITION) LAYER ON ICE, H. H. G. JELLINEK PHYSICAL ADSORPTION OF VAPORS ON ICE AND ON WATER, ARTHUR W. ADAMSON, L. M. DORMANT, MICHAEL OREM SOME SURFACE PHENOMENA OF ICE, K. ITAGAKI SURFACE DIFFUSION AT THE ICE-AIR INTERFACE, P. W. HOBBS, W. D. SCOTT STUDIES OF ICE ADHESION I. ADHESION OF ICE TO PLASTICS, MILTON LANDY, ARNOLD FREIBERGER TRANSITION FROM PLANAR TO NONPLANAR SOLID/LIQUID INTERFACE FOR THE SYSTEMS WATER-AMMONIUM FLUORIDE AND WATER-AIR, D. W. JAMES SINTERING OF POWDERED ICE, H. H. G. JELLINEK, S. H. IBRAHIM THE FREEZING OF WATER ON SOLID SURFACE, PAUL R. CAMP SURFACE FEATURES OBSERVED DURING THERMAL ETCHING OF ICE, A. S. KRAUSZ, L. W. GOLD DENDRITIC AND PLANAR ICE GROWTH, G. KVAJIC, E. R. POUNDER FREEZING POTENTIALS AND THE ICE-SOLUTION AND ICE-METAL INTERFACES, VERNON LE FERRE ION DISTRIBUTION AND PHASE-BOUNDARY POTENTIALS DURING THE FREEZING OF VERY DILUTE IONIC SOLUTIONS AT UNIFORM RATES, GERARDO WOLFGANG GROSS ICE MORPHOLOGY AT THE FREEZING INTERFACE, J. D. HARRISON WATER-ICE-AIR INTERSECTION ANGLE, CHARLES A. KNIGHT SOME RELATIONS BETWEEN THE STRUCTURE OF THE ICE-SOLUTION INTERFACE AND THE FREE GROWTH RATE OF ICE CRYSTALS IN SUPERCOOLED AQUEOUS SOLUTION, H. R. PRUPPACHER.]]></description>
      <pubDate>Mon, 17 Feb 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/96089</guid>
    </item>
    <item>
      <title>THE FAR INFRARED SPECTRUM OF VULCANIZED NATURAL RUBBER</title>
      <link>https://trid.trb.org/View/110161</link>
      <description><![CDATA[EARLIER STUDIES OF THE INFRARED SPECTRA OF NATURAL RUBBER AND SOME VULCANIZATES OF RUBBER HAVE BEEN EXTENDED INTO THE 650 TO 33 CM FAR INFRARED REGION. SOME OF THE ABSORPTION BANDS ORIGINATING IN THE CRYSTALLINE PORTION OF UNVULCANIZED RUBBER HAVE BEEN STUDIED BY USING POLARIZED RADIATION AND SAMPLES ORIENTED BY STRETCHING. VULCANIZATION OF RUBBER WITH SULFUR ALONE PRODUCES A GENERAL WEAKENING OF ALL ABSORPTION BANDS AND NO NEW ABSORPTIONS. VULCANIZATION WITH SULFUR AND AN ACCELERATOR ALSO RESLUTS IN A REDUCTION IN INTENSITY OF THE RUBBER ABSORPTIONS, BUT IS ACCOMPANIED BY THE APPEARANCE OF NEW BANDS. WHEN THE ACCELERATOR IS TETRAMETHYLTHIURAM DISULFIDE (TMTD) THE NEW BANDS ARE PROBABLY INDICATIVE OF A THIOCARBAMATE STRUCTURE. WHEN ZINC DIBUTYLDITHIOCARBAMATE IS USED AS AN ACCELERATOR A BAND PROBABLY DUE TO ZINC SULFIDE OCCURS. VULCANIZATION WITH TMTD ALONE PRODUCES ONLY SLIGHT CHANGES IN THE FAR INFRARED SPECTRUM. HOWEVER, WHEN TMTD IS USED IN THE PRESENCE OF ZINC OXIDE A REACTION OCCURS IN WHICH ZINC DIMETHYLDITHIOCARBAMATE (ZNDMDC) IS FORMED. AFTER VULCANIZATION FOR A SHORT PERIOD OF TIME STRONG TMTD BANDS REMAIN, BUT AFTER LONG VULCANIZATION THE TMTD BANDS ARE REPLACED BY ZNDMDC BANDS. /AUTHOR/]]></description>
      <pubDate>Fri, 03 Jun 1994 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/110161</guid>
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