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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SSR</journal-id><journal-title-group><journal-title>Scientific and Social Research</journal-title></journal-title-group><issn>2661-4332</issn><eissn>2981-9946</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/ssr.v5i10.5443</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Intelligent Transportation Planning and  Construction in the Era of Big Data</title><url>https://artdesignp.com/journal/SSR/5/10/10.26689/ssr.v5i10.5443</url><author>ChenCan</author><pub-date pub-type="publication-year"><year>2023</year></pub-date><volume>5</volume><issue>10</issue><history><date date-type="pub"><published-time>2023-10-30</published-time></date></history><abstract>Intelligent transportation planning has become increasingly important in the era of big data. By utilizing big data technology, traffic flow can be measured and managed more effectively. This leads to transportation planning that is more scientific and provides people with more convenient travel options. 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