<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Civil Engineering Infrastructures Journal</JournalTitle>
				<Issn>2322-2093</Issn>
				<Volume></Volume>
				<Issue>Articles in Press</Issue>
				<PubDate PubStatus="epublish">
					<Year>2025</Year>
					<Month>10</Month>
					<Day>11</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Unveiling Spatiotemporal Patterns in Public Transportation: A Smart Card Data Analysis</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage></FirstPage>
			<LastPage></LastPage>
			<ELocationID EIdType="pii">104163</ELocationID>
			
<ELocationID EIdType="doi">10.22059/ceij.2025.385897.2189</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Shariat</FirstName>
					<LastName>Radfar</LastName>
<Affiliation>Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Hamidreza</FirstName>
					<LastName>Koosha</LastName>
<Affiliation>Department of Industrial Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Gholami</LastName>
<Affiliation>Department of Civil Engineering, Faculty of Engineering, Golestan University, Gorgan, Iran</Affiliation>
<Identifier Source="ORCID">0000-0001-5888-6420</Identifier>

</Author>
<Author>
					<FirstName>Atefeh</FirstName>
					<LastName>Amindoust</LastName>
<Affiliation>Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2024</Year>
					<Month>11</Month>
					<Day>24</Day>
				</PubDate>
			</History>
		<Abstract>Abstract&lt;br /&gt;Travel patterns in public transportation systems are shaped by a complex interplay of spatial and temporal factors, including passenger location, time of day, and urban infrastructure. Unraveling these patterns is crucial for effective planning and development. This study delves into zonal-based public transport travel behavior in Mashhad, Iran, leveraging smart card data from bus and metro systems. K-means clustering unveils distinct temporal patterns (morning, noon, evening) in passenger trips across 253 traffic zones. Meanwhile, Mean Shift clustering explores the spatial dimension, analyzing population density and built-up areas within each zone. The analysis yields unique clusters for both temporal and spatial aspects, highlighting the intricate relationship between travel patterns, demographics, and land use. Notably, the study confirms correlations between: morning trips and residential areas, midday trips and commercial/educational areas, and the transactions of marginal traffic zones with near outer residential areas. These insights provide valuable knowledge for policymakers and planners in optimizing land-use and transportation strategies.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Smart Card Data (SCD)</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Temporal and Spatial Patterns</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Clustering of Traffic Zones</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">k-means algorithm</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Mean Shift Algorithm</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ceij.ut.ac.ir/article_104163_737291ac3a9755af620fb94cd91243fe.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
