<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1665-6423</journal-id>
<journal-title><![CDATA[Journal of applied research and technology]]></journal-title>
<abbrev-journal-title><![CDATA[J. appl. res. technol]]></abbrev-journal-title>
<issn>1665-6423</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1665-64232018000200079</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Characterization of municipalities with high road traffic fatality rates using macro level data and the CART algorithm]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Campos]]></surname>
<given-names><![CDATA[Cintia Isabel de]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Santos]]></surname>
<given-names><![CDATA[Murilo Castanho dos]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pitombo]]></surname>
<given-names><![CDATA[Cira Souza]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,University of Sao Paulo São Carlos School of Engineering Department of Transportation Engineering]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,University of Porto Faculty of Engineering Department of Civil Engineering]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2018</year>
</pub-date>
<volume>16</volume>
<numero>2</numero>
<fpage>79</fpage>
<lpage>94</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1665-64232018000200079&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1665-64232018000200079&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1665-64232018000200079&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Road traffic accidents occur daily caused by different factors leading to varying degrees of injury severity. Considering this, many studies have been developed to identify and understand these factors to implement preventive actions. A Decisión Tree (DT) is one of the techniques that can genérate classifications and predictions by detecting a priori imknown patterns. This study aims to identify the characteristics of municipalities with high and very high fatality rates caused by traffic accidents, using a macro level dataset and a DT algorithm (CART - Classification And Regression Tree). Therefore, macro level data from the municipalities of Sao Paulo state (Brazil) were used, such as demographic and socioeconomic data, fatality rates and other variables related to traffic. The results indicated the Gross Domestic Product (GDP) as the most important variable, and the municipalities were characterized mainly considering the size of the highway network and vehicle ffeet (trucks, minibuses, cars, motorcycles). These characteristics could provide support to the government to plan mitigating actions in municipalities with the highest tendency to high traffic fatality rates.]]></p></abstract>
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<kwd lng="en"><![CDATA[Road Safety]]></kwd>
<kwd lng="en"><![CDATA[Macro Level Data]]></kwd>
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