<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <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>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
    </image>
    <item>
      <title>Estimating the Effects of Environmental Conditions, Built Environment and Traffic Behavioral Factors on Pedestrian and Bicyclist Safety in Washington, DC</title>
      <link>https://trid.trb.org/View/1496606</link>
      <description><![CDATA[Cycling and walking as modes of transportation are on the rise in many major cities. Similarly, pedestrian and bicyclist collisions with motorized vehicles are also on the rise. This calls for the need to identify the factors that may cause collisions, both to improve bicyclist and pedestrian safety and to encourage more individuals to use active modes of transportation. Using a structural equation model, this paper estimates the impact of environmental conditions, road characteristics, and zonal traffic behavior on bicyclist and pedestrian collisions in Washington, DC. The zonal traffic behavior component was captured by using the Vision Zero Safety App, an online platform that allows users to report on a number of transportation safety issues. For pedestrian safety, results showed that traffic signals, intersections, bus stops and bike lanes decrease safety. For bicyclists, bike lanes improve safety whereas major arterial roads decrease it. For both bicyclists and pedestrians, adverse weather conditions and zones with high reporting on safety issues (as a surrogate performance measure of such zones) were associated with an increase in safety.]]></description>
      <pubDate>Wed, 24 Jan 2018 09:25:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1496606</guid>
    </item>
    <item>
      <title>Microscopic Analysis of Traffic Flow in Inclement Weather--Part 2</title>
      <link>https://trid.trb.org/View/1105170</link>
      <description><![CDATA[This report documents the second part of the Federal Highway Administration (FHWA) research study involving analysis of the microscopic impacts of adverse weather on traffic flow, but is a third phase of the research effort on the impacts of weather on traffic flow. The first phase of FHWA research involved macroscopic analysis, which focused on the impacts of adverse weather on aggregate traffic flow. The second phase of research analyzed the impacts of adverse weather on microscopic traffic behavior. This report documents the results of three research efforts (1) The impacts of icy roadway conditions on driver behavior at a microscopic level, using field-measured car-following data,; (2) An investigation of the influence of weather precipitation and roadway surface condition on left-turn gap-acceptance behavior using traffic and weather data collected during the winter of 2009-2010 at a signalized intersection in Blacksburg, Virginia; and (3) The development and demonstration of methodologies for the use of weather-related adjustment factors in microsimulation models, including general approaches to construct simulation models accounting for the impact of precipitation. For the third effort, the general approach was applied to the calibration of the VISSIM and INTEGRATION simulation software.]]></description>
      <pubDate>Thu, 30 Jun 2011 07:11:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1105170</guid>
    </item>
    <item>
      <title>Maintenance Services and Surface Weather</title>
      <link>https://trid.trb.org/View/1083722</link>
      <description><![CDATA[This issue contains 19 papers concerned with maintenance services and surface weather.  Specific topics discussed include the following:  variable speed limit systems in work zones; the safety of mobile lane closures; temporary rumble strips for short-term work zones; the joint merge in construction zones; real-time measurement of travel time delay in work zones; short-term speed limit devices in work zones; simulation models for assessing the impacts of highway work zone strategies; estimating operational impacts of freeway work zones on extended facilities; alternative displays for speed limits in work zones; assessment of pavement marking visibility; repeatability of retroreflectometer measurements of pavement markings; impact of cold temperature and snowfall on traffic volume; diagnosing road weather conditions with vehicle probe data; improving road weather hazard products with vehicle probe data; integrating the impact of rain into traffic management; the impact of adverse weather on freeway free-flow speed; structural control measures to mitigate avalanche hazards; a small unmanned aircraft for avalanche control; and costs and benefits of tools to maintain winter roads.]]></description>
      <pubDate>Mon, 13 Dec 2010 15:21:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1083722</guid>
    </item>
    <item>
      <title>Aging and the Detection of Collision Events in Fog</title>
      <link>https://trid.trb.org/View/918376</link>
      <description><![CDATA[The current study investigated age-related differences in the detection of collision events in fog. Observers were presented with displays simulating an object moving towards a driver at a constant speed and linear trajectory. The observers’ task was to detect whether the object would collide with them. Fog and display duration of the object were manipulated. We found that performance decreased when fog was simulated for older but not for younger observers. An age-related decrement was also found with shorter display durations. These results suggest that under poor weather conditions with reduced   visibility, such as fog, older drivers may have increased accident risk due to decreased ability to detect impending collision events.]]></description>
      <pubDate>Sun, 30 May 2010 07:44:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/918376</guid>
    </item>
    <item>
      <title>Winter Highway Maintenance Operational Performance Management and Performance Targets</title>
      <link>https://trid.trb.org/View/882463</link>
      <description><![CDATA[The purpose of this study is to develop an applicable performance measurement system that enables winter maintenance agencies to evaluate how well operations have been conducted to meet specified maintenance goals using routinely monitored speed and volume data. The research database includes 1876 adverse weather events, with a total 22420 hourly records. CHAID analysis was first applied to explore the structure of associations between speed and volume reductions and various predicators. Chi-squared Automatic Interaction Detector (CHAID) was also used to identify good segmentations for statistical modeling. The results of CHAID analysis indicate that maintenance level of service (LOS), Annual Average Daily Traffic (AADT), road class, urban settings all have considerable influence on speed and volume reductions, and their influence are moderated by time of the day and different maintenance operational stages. The authors found that in general the roads receives the higher level of maintenance service have the lower speed reduction compare to it for the other types. The municipal highways have much less volume reduction than the rural highways. Based on the analysis, the authors recommend appropriate targets for maintenance agencies that accommodate the difference in maintenance outcomes because of a variety of weather conditions, the specifications of road system and various traffic conditions.]]></description>
      <pubDate>Fri, 13 Mar 2009 06:36:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/882463</guid>
    </item>
    <item>
      <title>Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply</title>
      <link>https://trid.trb.org/View/874744</link>
      <description><![CDATA[This paper proposes a novel traffic assignment model considering uncertainties in both demand and supply sides of a road network. These uncertainties are mainly due to adverse weather conditions with different rainfall intensities on the road network. A generalized link travel time function is proposed to capture these effects. The proposed model allows the risk-averse travelers to consider both an average and uncertainty of the random travel time on each path in their path choice decisions, together with the impacts of weather forecasts. Elastic travel demand is considered explicitly in the model responding to random traffic condition in the network. In addition, the model also considers travelers' perception errors using a logit-based stochastic user equilibrium framework formulated as a fixed point problem. A heuristic solution algorithm is proposed for solving the fixed point problem. Numerical examples are presented to illustrate the applications of the proposed model and efficiency of the solution algorithm.]]></description>
      <pubDate>Tue, 25 Nov 2008 07:32:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/874744</guid>
    </item>
    <item>
      <title>High Performance Concrete Bridge Decks in Minnesota</title>
      <link>https://trid.trb.org/View/870498</link>
      <description><![CDATA[This paper describes how bridges in Minnesota experience harsh conditions with wide temperature extremes, fairly long snow and ice seasons, and many applications of deicing chemicals. The standard bridge deck protection system of the Minnesota Department of Transportation (Mn/DOT) includes epoxy-coated reinforcement, a 7-in. (175-mm) thick conventional concrete structural slab, and a 2-in. (50-mm) thick low-slump concrete overlay. This system has worked extremely well since the mid 1970s and is specified on most bridges. High performance concrete (HPC) bridge decks offer potential benefits to the state including decreased construction time, lower permeability, and cost savings of 5 percent or more compared to decks with low-slump overlays.]]></description>
      <pubDate>Wed, 24 Sep 2008 10:39:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/870498</guid>
    </item>
    <item>
      <title>Effects of Adverse Weather on Traffic Crashes: Systematic Review and Meta-Analysis</title>
      <link>https://trid.trb.org/View/848487</link>
      <description><![CDATA[Adverse weather obviously has an impact on vehicle crash rates on roads and highways. However, it would be valuable to quantify the extent to which weather conditions affect the crash rate. To do that, a meta-analysis has been conducted to generalize research findings on this subject and attempt to quantify the impact of weather on traffic crashes. Studies between 1967 and 2005 that examined the interaction of weather and traffic safety were reviewed. Thirty-four papers and 78 records that meet the predetermined criteria were included in the analysis. Crash rates from each study were normalized with respect to effect size for meta-analysis generalization. Results indicate that the crash rate usually increases during precipitation. Snow has a greater effect than rain does on crash occurrence: snow can increase the crash rate by 84% and the injury rate by 75%. Further results also suggest that variations in study results can be explained by study design, date of the study, and region or countries included in the study.]]></description>
      <pubDate>Mon, 25 Feb 2008 14:33:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/848487</guid>
    </item>
    <item>
      <title>Modeling the Causal Relationships between Winter Highway Maintenance, Adverse Weather and Mobility</title>
      <link>https://trid.trb.org/View/848925</link>
      <description><![CDATA[This paper explored the direct and indirect causal effects of adverse weather and winter maintenance actions on mobility as measured by traveling speed and traffic volume. Using Structural Equation Modeling (SEM) with the particular Categorical Variable Methodology (CVM), the paper analyzed the weather, maintenance and traffic data from 2001 to 2004 in the State of Iowa. Separate structure models were fit simultaneously to subgroups, which are disaggregated by road classification, Annual Average Daily Traffic (AADT) and speed limit. The analysis results suggest that despite winter maintenance operations that might slow down traffic during the hour when they are performed, winter maintenance operations have significant positive effects on improving speed, and the positive effects have been fully mediated through road surface conditions. Compared to the effects of plowing and applying chemicals, sanding is the least influential operational method to improve speed. Also the analyses suggest that the influences are different across road classifications, speed limits and different levels of AADT.]]></description>
      <pubDate>Mon, 25 Feb 2008 14:33:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/848925</guid>
    </item>
    <item>
      <title>Accident Reduction Potential of Advanced Adverse Weather Warning Systems</title>
      <link>https://trid.trb.org/View/840178</link>
      <description><![CDATA[This paper presents the main results of a research project that was conducted at Madrid Polytechnic University to assess the potential of effectively reducing accident rates in adverse conditions by deploying Intelligent Transportation Systems (ITS). Traffic accidents that had occurred in the Spanish National System in adverse weather conditions during a 5-year period were studied to identify road sections with an accident record that justified the implementation of specific countermeasures. American and European experience in applying Road Weather Information Systems (RWIS) and Advanced Adverse Weather Motorist Warning Systems (AAWWS) were analyzed prior to the development of three pilot tests for the deployment of AAWWS at three Spanish network sites. These tests where complemented with an in-depth study of a sample of 259 adverse conditions injury crashes. The results were used to provide an estimation of the crash reduction attainable by the deployment of these systems in Spain. The research showed that the annual savings in social costs of traffic crashes would exceed the total investment needed to deploy the systems.]]></description>
      <pubDate>Mon, 26 Nov 2007 09:54:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/840178</guid>
    </item>
    <item>
      <title>Freeway Section Capacity for Different Metrological Conditions Using Neural Networks. Volume 2: Modelling Transport Systems</title>
      <link>https://trid.trb.org/View/839153</link>
      <description><![CDATA[Meteorological features (such as rain, fog low clearance, etc.) cause a capacity reduction of a road section and this reduction is usually computed using the method of the superimposition of effects. This chapter proposed the setting-up of an artificial neural network that in real time is able to estimate and forecast a freeway road section capacity in the function of both meteorological conditions and traffic composition by using a layered feed forward network.]]></description>
      <pubDate>Tue, 23 Oct 2007 09:16:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/839153</guid>
    </item>
    <item>
      <title>Evaluation of Snowplowable Raised Pavement Markers</title>
      <link>https://trid.trb.org/View/836674</link>
      <description><![CDATA[In 1992, the Iowa DOT installed 6200 snowplowable Raised Pavement Markers (RPM) in six areas around the state. They were evaluated at six-month intervals until the replacement of the reflective lenses in 1995. During this time, the RPM performed well. The Iowa Department of Transportation uses deicers and sand during the winter to control snow and ice on the pavement. The sand and the chemicals reduced the reflectivity of the reflectors. With minimum or no maintenance the visibility of the RPM is low. Although the RPM appear to present a problem during snow plowing, they are an excellent device for lane delineation at night in adverse weather. Lane delineation during adverse weather is a problem, especially at night. Some raised marking devices have been tried for lane delineation, but they did not withstand the snowplows during snow removal operations. Painted pavement markings are not visible during rainy conditions.]]></description>
      <pubDate>Mon, 22 Oct 2007 09:58:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/836674</guid>
    </item>
    <item>
      <title>Development of Expert System for Forecasting Frost on Bridges and Roads in Iowa</title>
      <link>https://trid.trb.org/View/836673</link>
      <description><![CDATA[An expert system has been developed that provides 24 hour forecasts of roadway and bridge frost for locations in Iowa. The system is based on analysis of frost observations taken by highway maintenance personnel, analysis of conditions leading to frost as obtained from meteorologists with experience in forecasting bridge and roadway frost, and from fundamental physical principles of frost processes. The expert system requires the forecaster to enter information on recent maximum and minimum temperatures and forecasts of maximum and minimum air temperatures, dew point temperatures, precipitation, cloudiness, and wind speed. The system has been used operationally for the last two frost seasons by Freese-Notis Associates, who have been under contract with the Iowa DOT to supply frost forecasts. The operational meteorologists give the system their strong endorsement. They always consult the system before making a frost forecast unless conditions clearly indicate frost is not likely. In operational use, the system is run several times with different input values to test the sensitivity of frost formation on a particular day to various meteorological parameters. The users comment. that the system helps them to consider all the factors relevant to frost formation and is regarded as an office companion for making frost forecasts.]]></description>
      <pubDate>Mon, 22 Oct 2007 09:58:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/836673</guid>
    </item>
    <item>
      <title>Machine Learning in Modeling Expressway Winter Maintenance Performance</title>
      <link>https://trid.trb.org/View/836681</link>
      <description><![CDATA[This paper presents a machine learning approach to modeling the performance of winter maintenance operations on Western New York’s expressways. A second objective of the paper is to identify any discrepancy in the performances between expressway segments which are directly linked but maintained by two different agencies, namely the New York Department of Transportation and the New York Thruway Authority. The study uses speed reduction converted from actual travel time on the two agencies’ connected expressway segments as the index of level of service. The traffic data is obtained from a traffic surveillance system based on automatic vehicle identification technology, while the meteorological data is provided by the National Weather Service weather surveillance radar system. First, multiple regression analysis is conducted to model hourly speed reduction during snow storms over an entire winter season. However, non-linear relationships are found to exist in the model. Therefore, the M5 machine learning algorithm is applied to induce a model tree, at each leave of which is a linear regression model for a particular input space. The result shows that there is an evident gap in the level of service between the two agencies only during the early stage of storm events. Implications for the seamless operations of the regional expressway system are discussed.]]></description>
      <pubDate>Mon, 22 Oct 2007 09:57:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/836681</guid>
    </item>
    <item>
      <title>Weather-Responsive Transportation Management</title>
      <link>https://trid.trb.org/View/793032</link>
      <description><![CDATA[This paper describes how nearly twenty five percent of non-recurring delays and congestion on freeways are because of adverse weather conditions. The Federal Highway Administration (FHWA) Road Weather Management Program has been focusing its efforts to better understand the impacts of weather on traffic flow and for developing tools to alleviate those impacts.  Information about weather and its impacts on the transportation system are currently not well integrated into the operational framework of most transportation agencies. This paper describes three efforts by the FHWA Road Weather Management program to advance the state-of-the practice in weather-responsive transportation management. The first is a prototype weather response system (WRS) for transportation management that was developed in partnership with the Missouri Department of Transportation. The WRS takes advantage of weather data and products from the National Weather Service (NWS) and other sources to support the application of traffic management, maintenance, and operations activities within the agency. The paper also describes how the system can be deployed in statewide Transportation Management Centers (TMCs), Traffic Operations Centers, and District Maintenance Facilities. The second effort consisted of a study on the integration of weather into TMCs. This paper summarizes how weather information is being integrated into the TMC operations of several agencies in the country. The third effort involves an empirical study on weather and traffic data to model traffic flow under varying weather conditions. Such information is vital for accurate traffic flow analysis and modeling, and determination of appropriate traffic management strategies to mitigate the impacts of weather.]]></description>
      <pubDate>Wed, 15 Nov 2006 16:21:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/793032</guid>
    </item>
  </channel>
</rss>