<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-08T22:31:42Z</responseDate><request verb="GetRecord" identifier="oai:riubu.ubu.es:10259/7037" metadataPrefix="marc">https://riubu.ubu.es/oai/request</request><GetRecord><record><header><identifier>oai:riubu.ubu.es:10259/7037</identifier><datestamp>2024-05-17T09:39:04Z</datestamp><setSpec>com_10259_3847</setSpec><setSpec>com_10259_5086</setSpec><setSpec>com_10259_2604</setSpec><setSpec>com_10259_6193</setSpec><setSpec>com_10259_4147</setSpec><setSpec>com_10259.4_106</setSpec><setSpec>com_10259.4_104</setSpec><setSpec>com_10259_7070</setSpec><setSpec>com_10259_6189</setSpec><setSpec>col_10259_7109</setSpec><setSpec>col_10259_7108</setSpec><setSpec>col_10259_6848</setSpec><setSpec>col_10259_7071</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">dc</subfield>
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<datafield tag="720" ind1=" " ind2=" ">
<subfield code="a">Cogollos Adrián, Héctor</subfield>
<subfield code="e">author</subfield>
</datafield>
<datafield tag="720" ind1=" " ind2=" ">
<subfield code="a">Porras Alfonso, Santiago</subfield>
<subfield code="e">author</subfield>
</datafield>
<datafield tag="720" ind1=" " ind2=" ">
<subfield code="a">Baruque Zanón, Bruno</subfield>
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<datafield tag="260" ind1=" " ind2=" ">
<subfield code="c">2021-07</subfield>
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<subfield code="a">The density of traffic within urban areas depends on multiple factors, and among those; one&#xd;
that has major impact is the weather. This paper presents a study that empirically analyzes&#xd;
the traffic flow velocity depending on the atmospherically conditions and the day schedule.&#xd;
The objective is to assess systematically to which extent there is a correlation between the&#xd;
vehicle velocity on an urban environment and the weather, depending on the time of day.&#xd;
The presented case of study uses a set of real data, specifically the trips made by taxis in the&#xd;
city of Porto (Portugal). First, the vehicle GPS routes are analyzed to identify departure and&#xd;
arrival points and estimate the route average velocity and adding weather and time&#xd;
conditions. The data is processed with different regressive techniques to obtain the influence&#xd;
of the variables on the velocity. The results show differences between days of the day and&#xd;
weekends, as well as differences in speeds with a favorable climate for driving compared to&#xd;
other more adverse ones.</subfield>
</datafield>
<datafield tag="024" ind2=" " ind1="8">
<subfield code="a">978-84-18465-12-3</subfield>
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<subfield code="a">http://hdl.handle.net/10259/7037</subfield>
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<datafield tag="024" ind2=" " ind1="8">
<subfield code="a">10.36443/10259/7037</subfield>
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<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Seguridad vial</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Tráfico</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Road safety</subfield>
</datafield>
<datafield ind1=" " ind2=" " tag="653">
<subfield code="a">Traffic</subfield>
</datafield>
<datafield tag="245" ind1="0" ind2="0">
<subfield code="a">Analysis of traffic velocity under different weather and temporary conditions</subfield>
</datafield>
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