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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>Evaluation of the Minimum Number of Local Driving Cycles Required to Represent the Traffic of Distinct Cities: A Case Study of Two Brazilian Metropolises</title>
      <link>https://trid.trb.org/View/2219093</link>
      <description><![CDATA[This study aimed to determine whether a single local driving cycle (LDC) can effectively represent different cities in the same country, in both urban and highway routes, and for cars and motorcycles. To achieve this, experienced drivers drove different monitored vehicles (five cars and three motorcycles) on seven selected routes in two Brazilian states (Pernambuco and São Paulo State), collecting 170?h of speed data in urban and highway routes during peak and off-peak hours. Using the micro-trip and Markov chain methods, LDCs were then developed based on the collected real-world data. The kinematic and energy parameters of different route groupings were compared, revealing that two LDCs, one for cars and one for motorcycles, could be used to represent all urban routes. However, each highway route required a unique LDC. When compared with standard driving cycles adopted in Brazil, the created LDCs presented a coefficient of variation of 13%–46% in kinematic characteristic parameters, highlighting the need for developing LDCs to better represent Brazilian traffic.]]></description>
      <pubDate>Wed, 26 Jul 2023 10:57:03 GMT</pubDate>
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      <title>Analysis of the Applicability of USCS, TRB and MCT Classification Systems to the Tropical Soils of Pernambuco, Brazil, for Use in Road Paving</title>
      <link>https://trid.trb.org/View/2113043</link>
      <description><![CDATA[The purpose of this article is to analyze the applicability of USCS, TRB and MCT soil classification systems in tropical soils for use in road paving. Two soils from the State of Pernambuco (Brazil) were chosen for analysis. The grading composition indicated essentially fine soils, classified as follows: USCS—ML and TRB—A-4 and A-7–6 and CBR ≅ 15% and expansion ≅ 0%. Considering these results and the Brazilian criteria for acceptance of soils for paving use, it is found that the soils in question would be summarily discarded. On the other hand, the characteristic curves showed soils with high suction values, and the EDS and XRD tests revealed the presence of kaolinite and iron and aluminum hydroxides/oxides, evidencing the lateritic nature of the soils and corroborating with MCT classification findings. The USCS and TRB systems are shown to be important for analyzing the fraction controlling the soil’s behavior, since the MCT classification proved helpful to identify the lateritic character of the soils (LA′ and LG′—lateritic sandy and clayey soils), based on responses to compaction and total immersion in water, which are the closest conditions to the site reality. Furthermore, it was found that the soils can be used as embankment material and subgrade reinforcement and have potential use in the main layers of paving (base course and sub-base). It was found to be necessary to incorporate more modern parameters, such as resilient modulus and permanent deformation (the next stage in this study), in order to provide a complete classification.]]></description>
      <pubDate>Wed, 14 Jun 2023 17:09:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2113043</guid>
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      <title>Traffic accident prediction model for rural highways in Pernambuco</title>
      <link>https://trid.trb.org/View/1902455</link>
      <description><![CDATA[Due to the need to update the current guidelines for highway design to focus on safety, this study sought to build an accident prediction model using a Geographic Information System (GIS) for single-lane rural highways, with a minimum of statistically significant variables, adequate to the Brazilian reality, and improve accident prediction for places with similar characteristics. This analysis was conducted on 215 km of single-lane road segments of highway BR-232 in the State of Pernambuco. The development of a database made it possible to associate accident records for the period 2007 to 2016 from Federal Highway Police (PRF) data with the geometric parameters of the highway, obtained through geometric reconstruction of the vector data available at the National Department of Transportation Infrastructure (DNIT) and the semi-automatic extraction of highways from satellite imagery. The homogeneous segments were analyzed and classified by the Spatial method (Kernel-KDE density). A Generalized Estimating Equation (GEE) model was estimated to model the frequency and severity of accidents. The results indicate that increase in the slope and the radius impact the increase in the frequency of accidents and the reduction of the severity of accidents in curves.]]></description>
      <pubDate>Wed, 26 Jan 2022 14:16:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1902455</guid>
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      <title>A multidimensional and multi-period analysis of safety on roads</title>
      <link>https://trid.trb.org/View/1881477</link>
      <description><![CDATA[This paper proposes a multidimensional and multi-period analysis of safety on roads. It aggregates different road safety performance indicators observed over different periods for which multicriteria and multi-period approaches are used. The criticality of a road depends on the interaction of various factors, such as human factors, causes of accidents and their severity levels, and the characteristics/states of the roads. Therefore, there is a need for a multidimensional view of risk and its consequences concerning traffic accidents. Furthermore, using the Multiple Criteria Decision Making/Aid methods (MCDM/A) allows the performance of roads in the multiple criteria to be considered according to the decision maker's preferences. On the other hand, the temporal approach reflects the performance of roads and their accidents in different periods, enabling the information on the temporal behavior of accidents to be aggregated to the result. Given that Brazil has a vast road network, there is thus the problem of prioritizing road segments to allocate resources for traffic accident prevention and mitigation actions, especially as these resources are usually limited and scarce. For that, a case study is developed in the state of Pernambuco in Brazil. Eleven road segments are analyzed. The strategic objective of the decision-maker is to have a broader view, initially, of the criticality of these road segments in terms of safety so that strategically he can allocate resources to prevent and mitigate the risks of traffic accidents. For this, the decision-maker considered eleven criteria. These represent the different dimensions that can influence traffic accidents, such as the damage (impacts) to human beings or other consequences resulting from traffic accidents and issues related to the characteristics/state of the road and its traffic. Five periods of time were considered to incorporate the temporal influence of these dimensions (2015 to 2019). As a result, it is seen that, for a more comprehensive assessment, it is essential to consider a multidimensional view of risk and a multi-period evaluation, thus incorporating more information into the decision model and thereby making its results more assertive.]]></description>
      <pubDate>Tue, 12 Oct 2021 16:52:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/1881477</guid>
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      <title>Alcohol and Risky Behavior in Traffic Among Motorcyclists Involved in Accidents in a City in Northeastern Brazil</title>
      <link>https://trid.trb.org/View/1623190</link>
      <description><![CDATA[The objective of this study was to analyze the association between consumption of alcoholic drinks and adoption of other risky forms of behavior in traffic among motorcyclists involved in accidents.  This was an exploratory cross-sectional study among injured motorcyclists who were hospitalized in the traumatology department of the “Governador Paulo Guerra” Restoration Hospital (Hospital da Restauração Governador Paulo Guerra), Recife, Pernambuco, Brazil. A questionnaire containing items relating to sociodemographic, occupational, and behavioral factors and aspects of the accident and road conditions was applied. Descriptive and bivariate analyses were performed and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The significance level was set at 5%.  One hundred seventy individuals were investigated. Consumption of alcohol prior to the accident was reported by 32.9% of motorcyclists. This behavior was positively associated with the following risky forms of behavior in traffic: speeding (OR = 4.08; 95% CI, 1.15–9.48); failure to use a helmet (OR = 2.41; 95% CI, 1.15–5.02); and not having a motorcycle driver’s license (OR = 2.68; 95% CI, 1.31–5.45).  This study showed that, in the population studied, riding a motorcycle under the effects of alcoholic drinks was associated with other risky forms of behavior in traffic: speeding, not using a helmet, and not having a motorcycle driver’s license. The authors believe that the interaction between these behaviors may lead to greater occurrence and greater severity of accidents.]]></description>
      <pubDate>Fri, 26 Jul 2019 11:52:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1623190</guid>
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