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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>Transport Research International Documentation (TRID)</title>
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      <title>Modeling Operating Speed: Synthesis Report. Chapter 5: Deficiencies in Existing Speed Models</title>
      <link>https://trid.trb.org/View/1112894</link>
      <description><![CDATA[This chapter describes the main limitations and deficiencies identified in the existing speed profile models.  The following topics are addressed: issues with data collection; unrealistic assumptions of driver behavior; difficulties in estimating speed changes between geometric elements; lack of uniformity across models; consideration of only passenger cars; limitations of linear regression; and limited applicability of models.]]></description>
      <pubDate>Mon, 15 Aug 2011 15:24:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1112894</guid>
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      <title>Interrelations of Reaction Time, Driver Sensitivity, and Time Headway in Congested Traffic</title>
      <link>https://trid.trb.org/View/1093375</link>
      <description><![CDATA[Reaction time, driver sensitivity, and time headway are traffic parameters that are critical for understanding and modeling traffic stability and wave propagation. Both theoretical and empirical relationships between these three parameters are examined with vehicle trajectory data. A few clear and distinct relationships are identified, and driver reaction time is found to be closely related to time headway, especially in the deceleration phase. Time headway can be accurately predicted when reaction time and the initial time headway are known. In a traffic simulation, a range of values also exists for the product of driver sensitivity and reaction time to avoid unrealistic speed fluctuations and collisions.]]></description>
      <pubDate>Fri, 25 Mar 2011 13:13:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/1093375</guid>
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    <item>
      <title>Effects of Passengers on Bus Driver Celeration Behavior and Incident Prediction</title>
      <link>https://trid.trb.org/View/805505</link>
      <description><![CDATA[Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density cirrcumstances are supposed to yield better estimates of the individual driver component of celeration behavior.  In this study, comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). Results showed that after holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more.  The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.]]></description>
      <pubDate>Fri, 30 Mar 2007 06:59:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/805505</guid>
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    <item>
      <title>Highway Safety when Truck Speed Limits are Increased to 65 MPH in Ohio</title>
      <link>https://trid.trb.org/View/793574</link>
      <description><![CDATA[The objective of this paper is to determine the economic impact associated with raising the maximum truck speed limit in the state of Ohio from 55 mph to 65 mph.  The paper develops a prediction model that will determine the expected number of increased or decreased fatalities if the maximum speed limit in Ohio is raised to 65 mph.  Once the prediction model is developed, the results of the model will then be analyzed to determine if the economic impact of raising the speed limit is equivalent to the expected decrease in safety.]]></description>
      <pubDate>Wed, 15 Nov 2006 16:21:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/793574</guid>
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    <item>
      <title>Speed Choice Versus Celeration Behavior as Traffic Accident Predictor</title>
      <link>https://trid.trb.org/View/781317</link>
      <description><![CDATA[Introduction: The driver celeration behavior theory predicts that this variable is superior to all other variables as a predictor of individual traffic accident involvement, including the ever-important speed parameter. The study was undertaken to test this prediction. Also, it was expected that most variables would associate fairly strongly. Method: The use of speed choice as a predictor of individual traffic accident record was discussed, and four different variants of this variable (maximum, net mean, gross mean, and standard deviation of speed) identified. These variables were then compared to celeration behavior as predictors of accident record of bus drivers in the same set of data. Results: Celeration behavior was found to be slightly superior, in accordance with the prediction made from the driver celeration behavior theory, although the differences were not significant. Furthermore, the predictor variables were found to associate fairly strongly between themselves, with the exception of gross mean speed, and to have fair stability over time, especially when aggregated. Conclusions: These results tentatively confirm some of the predictions made from the driver celeration behavior theory. As the results for accidents were in the expected direction, but not significant, and the maximum speed variable may have suffered from a ceiling effect, the conclusion is provisional. Impact on industry: The correlations found were strong enough to warrant the use of celeration behavior as a predictive variable for transportation companies in their safety work.]]></description>
      <pubDate>Wed, 31 May 2006 09:31:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/781317</guid>
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    <item>
      <title>The Accuracy of Crash Data From Ford Restraint Control Modules Interpreted with Revised Vetronix Software</title>
      <link>https://trid.trb.org/View/761521</link>
      <description><![CDATA[Using Vetronix Crash Data Retrieval software, crash data can be downloaded from the restraint control modules (RCM) on some Ford motor vehicles.  These RCMs are part of the on-board computers that control the vehicle's airbags.  An earlier study used version 2.1 of the Vetronix software to download longitudinal speed change and acceleration data from RCMs on two Ford vehicles.  The accuracy of the data was then evaluated.  The current study reanalyzes the same RCM data using version 2.4 of the Vetronix software.  Unlike version 2.1, version 2.4 did not report duplicate data points.  Results showed that there were differences between the acceleration and speed change data reported by the two versions.  The speed change values reported by the newer version were, on average, more accurate than those of version 2.1 for one of the vehicles, the Ford Windstar.  For the Windstar RCM data, the average underestimate was 0.23 km/h using version 2.4.  However, the speed change values were less accurate for version 2.4 than for version 2.1 for the Ford Crown Victoria.  Using the version 2.4 data, the average underestimate was 0.73 km/h for the Crown Victoria RCM data.  The general underestimate of speed change can be accounted for by the incomplete record of the crash pulse reported by both software versions.]]></description>
      <pubDate>Fri, 21 Oct 2005 07:57:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/761521</guid>
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    <item>
      <title>AN ANALYSIS OF SPEED CHANGES FOR LARGE TRANSPORT TRUCKS</title>
      <link>https://trid.trb.org/View/117059</link>
      <description><![CDATA[RESEARCH WAS CONDUCTED TO DEVELOP A MEANS OF CALCULATING THE SPEED AND ACCELERATION CHARACTERISTICS OF LARGE TRANSPORT TRUCKS ON VARIOUS GRADES AND ACCELERATION LANES. BY MEANS OF A FORCE AND MOMENTUM BALANCE, A METHOD WAS DEVISED FOR CALCULATING THE SPEED VS DISTANCE HISTORY OF LARGE TRUCKS TRAVERSING VARIOUS TYPES OF VERTICAL HIGHWAY CURVES AT WIDE-OPEN THROTTLE. THE EQUATIONS THAT RESULTED WERE SOLVED WITH THE AID OF ELECTRONIC COMPUTING MACHINES OVER VARIOUS RANGES OF VALUES OF VEHICLE AND HIGHWAY PROPERTIES. RESULTS OF THE CALCULATIONS ARE PRESENTED AS CHARTS RELATING VEHICLE SPEED TO DISTANCE ALONG THE VERTICAL HIGHWAY CURVES. A COMPARISON OF CALCULATED AND EXPERIMENTAL VALUES SHOWED SATISFACTORY AGREEMENT. VARIOUS POSSIBLE METHODS OF UTILIZING THE CHARTS FOR HIGHWAY DESIGN OR VEHICLE SELECTION PURPOSES ARE DISCUSSED.]]></description>
      <pubDate>Fri, 13 Aug 2004 18:56:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/117059</guid>
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    <item>
      <title>PROTOTYPE TESTING OF ADVANCED CROSSING DIAMONDS</title>
      <link>https://trid.trb.org/View/539715</link>
      <description><![CDATA[Better performance from high-angle crossing diamonds has been a goal of the railway industry for quite some time.  Crossing diamonds are among the most short-lived, high-cost items in track.  They are also bottlenecks in operations, limiting the capacity of one or both crossing lines.  The Association of American Railroads has been researching methods to improve crossing diamond performance.  The methods, which include the use of improved materials, maintenance procedures and design features, are discussed in this article.]]></description>
      <pubDate>Wed, 14 Oct 1998 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/539715</guid>
    </item>
    <item>
      <title>SPEED CHANGE FROM CURB IMPACTS</title>
      <link>https://trid.trb.org/View/486682</link>
      <description><![CDATA[Tests were conducted to quantify the vehicle speed change during curb impacts for two vehicles.  The vehicles were driven into a curb at varying speeds and two approach angles.  The effect of braking during the curb impact for one the vehicles was investigated.  Test data are also included in which only one wheel of an unbraked vehicle climbed a curb.  The 11 tests were conducted on May 31, 1996, at the T-intersection of East 10th Street and West Grand Boulevard, in the City of North Vancouver, British Columbia.  The roads were traveled asphalt two lane roadways.  In the tests where the vehicle was rolling and not braking at the curb impact, longitudinal speed changes were 1.4 to 2.8 km/h for vehicle 1 and 3.0 to 3.8 km/h for vehicle 2. These data suggest that when a vehicle with freely rolling wheels drives over a curb, the speed loss is not significant. The single wheel curb impact tests are also consistent with this finding.  Further investigation is needed into the role of vehicle size, but initial indications are that the speed change is lower for larger vehicles for a given impact speed.  The braking at curb impact test data indicates that the speed calculated ignoring the curb impact, but accounting for locked wheel braking over the wheelbase, is similar to the speed loss from the front and rear wheels striking the curb and the lowered deceleration between wheel impacts.  Therefore, the curb impact can be ignored in the speed calculation.  Further tests are required to verify this result.]]></description>
      <pubDate>Tue, 16 Jun 1998 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/486682</guid>
    </item>
    <item>
      <title>EVALUATION OF SPEED LIMITS IN KENTUCKY</title>
      <link>https://trid.trb.org/View/473306</link>
      <description><![CDATA[The objectives of this study were to examine current criteria and procedures used for setting speed limits on public roads and to recommend appropriate speed limits for various types of roadways.  The major components of the study were a review of the literature, the collection and analysis of speed data, and the collection and analysis of accident data.  The speed data showed that operating speeds for most types of highways are substantially above the posted speed limit and that speeds of cars are slightly above those of trucks.  Data taken before and after speed limit changes show that operating speeds are changed much less than the change in speed limit.  Speed data taken in construction zones show that, while speeds are lower than typical for the specific type of highway, there is a disregard for lowered speed limits.  A comparison of accident rates at adjacent sections of interstate showed no increase in either total, injury, or fatal injury rates at locations with a 65 mph (104.6 kph) speed limit compared to a 55 mph (88.5 kph) speed limit.  Except where legislatively mandated speed limits apply, the 85th percentile speed should be used to establish speed limits.  Maximum limits are given for various types of roadways. In many instances, the maximum speed limit is slightly higher than the existing limit.  Also, different speed limits for cars and trucks are recommended for some roadways.  An engineering study must be conducted before the speed limit is increased for any specific section of roadway.]]></description>
      <pubDate>Mon, 30 Mar 1998 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/473306</guid>
    </item>
    <item>
      <title>ANALYSIS OF FREEWAY ACCIDENT DETECTION</title>
      <link>https://trid.trb.org/View/474553</link>
      <description><![CDATA[Instrumented traffic management can assist in the detection of freeway incidents and reduce the time required to initiate effective traffic management strategies and emergency response measures.  Although instrumented freeway traffic management is concerned primarily with general incidents, reportable vehicle accidents are the focus of this research.  Reportable accidents account for 20% of all freeway incidents and give rise to much of the nonrecurrent traffic congestion experienced on many freeways.  Explored here is how the use of various accident-detection criteria, such as change in speed, vehicle occupancy, and traffic volume, affects the time to detection for a mix of factors (preaccident traffic characteristics, accident lane-blockage pattern, position and distance of detector with respect to each accident).  A representative sample of Toronto freeway accidents for 1994 was analyzed using analysis of variance.  The results of this analysis suggest ways in which instrumented detection of freeway accidents can be made more efficient by reducing the time to detection.]]></description>
      <pubDate>Fri, 19 Dec 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/474553</guid>
    </item>
    <item>
      <title>OBSTACLE AVOIDANCE TECHNIQUES FOR THE AUTOMATED HIGHWAY SYSTEM</title>
      <link>https://trid.trb.org/View/574770</link>
      <description><![CDATA[One of the more difficult issues in designing the Automated Highway System (AHS) is how to avoid colliding with obstacles. This analysis of obstacle avoidance looks at the effect of increased vehicle cooperation on obstacle avoidance performance under three different obstacle avoidance techniques.  The scenario chosen to evaluate obstacle avoidance strategies has two dedicated AHS lanes with traffic moving in the same direction, operating at near capacity.  An obstacle appears in the roadway some distance ahead of a group of vehicles.  All vehicles are assumed to have obstacle detection sensors, to communicate with other vehicles, and to know the position of nearby vehicles.  A set of three obstacle avoidance strategies is analyzed.  These are: 1) full lane change, a relatively complex strategy requiring a high degree of data exchange and coordination between vehicles; 2) hybrid lane change, a simplified strategy requiring only limited data exchange and coordination between vehicles; and 3) hard braking, which can be done autonomously with no data exchange.  Braking and lane changing protocols were created as part of this analysis.  Each protocol divides the highway into a series of imaginary longitudinal strips, or zones.  At each of three decision times, an action involving longitudinal or lateral acceleration/deceleration (or both lateral and longitudinal) is chosen based on the best estimate of the zone in which the obstacle is located.  When viewed as a whole, the sequence of actions for each obstacle avoidance strategy (lane changing and hard braking) chosen successively at the three times forms a decision tree with ten to twelve branches.  All vehicles in this analysis are light passenger vehicles (car/pickup/van).  The obstacle appearing on the roadway is assumed to be stationary, and to have the size-to-mass characteristics of a granite boulder.  Tracking error estimates are based on the covariance errors for an alpha-beta filter.  The change in speed of a vehicle at the moment of collision is used as the safety metric for this analysis.  Safety performance of the three obstacle avoidance techniques is shown quantitatively as a function of speed, obstacle size, and sensor acquisition distance.  These results show the improvement in safety which is achievable with vehicle-to-vehicle coordination.  Some qualitative conclusions are also drawn about the circumstances under which each of the three obstacle avoidance techniques performs best.]]></description>
      <pubDate>Thu, 06 Nov 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/574770</guid>
    </item>
    <item>
      <title>EXPERIMENTAL AND NUMERICAL STUDIES OF SHEAR LAYERS IN GRANULAR SHEAR CELL</title>
      <link>https://trid.trb.org/View/458230</link>
      <description><![CDATA[The authors study--experimentally and numerically--the stability of a shear layer inside a granular material in a gravity field. A shear cell is constructed of transparent acrylic to visualize the motion of the granular material.  Two concentric cylinders containing layers of uniform spheres in the annular space between the cylinders comprise the shear cell. The shearing motion of the spheres results from the rotating bottom boundary of the cell. Friction of the cylinder walls resists the shear motion, thus producing a single shear layer adjacent to the bottom boundary, while the rest of the layers above move with constant speed as a solid body.  As the rotation speed of the bottom boundary increases, the two layers adjacent to the bottom boundary begin to shear.  This shearing zone rapidly thickens and dilates as the rotational speed increases. The transition of this shear motion from a single to multiple layers of shearing is examined by video recording. The start of the transition is dependent on the material properties and the number of layers overlaying the shear layer.  A one-dimensional numerical model is constructed to better understand this transitional phenomenon.]]></description>
      <pubDate>Sun, 24 Mar 1996 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/458230</guid>
    </item>
    <item>
      <title>SPEEDUP OF SHINKANSEN AND ATLAS PROJECT IN RTRI</title>
      <link>https://trid.trb.org/View/452756</link>
      <description><![CDATA[In an effort to make technological contributions to the Shinkansen speedup project of the JR companies, RTRI is now vigorously at work in R&D of fundamental domains under the ATLAS project envisioning an environment-friendly next generation super high-speed Shinkansen.  This paper outlines the trends in the R&D activities crucial to the speedup of Shinkansen, specifically on adhesion, running stability, current collection as well as external noise and ground vibrations, and comments on other problems, such as riding comfort, high-speed and high transportation density safety system and weight reduction of cars.]]></description>
      <pubDate>Thu, 04 Jan 1996 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/452756</guid>
    </item>
    <item>
      <title>MOBILE SOURCE EMISSION IMPACTS OF HIGH OCCUPANCY VEHICLE FACILITIES</title>
      <link>https://trid.trb.org/View/450896</link>
      <description><![CDATA[This paper appears in a compendium of conference papers and describes research to verify and validate two methods that estimate the potential mobile source emission reduction of high occupancy vehicle (HOV) facilities.  Results obtained from these methods are not consistent with the implementation of HOV facilities; both models failed validation due to their inability to accurately predict observed changes in travel characteristics due to implementation of HOV facilities.  Three recommendations stem from the research:  1) one method has potential for future use, however, it must be modified to account for HOV trips by trip purpose and include a more conservative speed change methodology; 2) traffic characteristic data are best for model validation due to the current state of technology; and 3) more research is needed to determine the validity of methods that assess the potential emission reduction of HOV facilities.  The Clean Air Act Amendments of 1990 mandate the use of transportation control measures, such as HOV facilities, in non-attainment areas.]]></description>
      <pubDate>Sun, 01 Oct 1995 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/450896</guid>
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