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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Tarrahan Parseh Transportation Research Institute</PublisherName>
				<JournalTitle>International Journal of Transportation Engineering</JournalTitle>
				<Issn>2322-259X</Issn>
				<Volume>14</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>07</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>In Light of the Automated Fare Collection Data, How Did the Travel Patterns of Transit Riders in Tehran Change following COVID-19?</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>2387</FirstPage>
			<LastPage>2418</LastPage>
			<ELocationID EIdType="pii">181837</ELocationID>
			
<ELocationID EIdType="doi">10.22119/ijte.2023.413809.1649</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mostafa</FirstName>
					<LastName>Shafaati</LastName>
<Affiliation>PHD candidate, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mahmoud</FirstName>
					<LastName>Saffarzadeh</LastName>
<Affiliation>Professor, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-9713-2776</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2023</Year>
					<Month>09</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>&lt;span&gt;The spread of COVID-19 caused some problems in public transportation. The pandemic created new challenges for developing countries like Iran, where public transportation is already plagued by many problems. As a result of COVID-19 concerns, it was speculated that unpredictable travel patterns would result. Based on Automatic Fare Collection data, in which passengers use a smartcard to enter a stop, this study evaluates this speculation. The dataset includes one month of transactions for each of the three COVID-19-related years (2019, 2020, and 2021) in Tehran, the country&#039;s capital. By using time series clustering, it was found that a new pattern of travel has emerged. Before vaccination, most origins were in the eastern part of the city; whereas, in the new era, most of the origins are in the western part of the city. The peak hours have also undergone a significant change. Prior to the pandemic, the peak hour occurred between 7 and 8 o&#039;clock in the morning, and demand reduced until the evening peak hour, but as a result of the new pattern, demand did not decrease significantly after 8:00:00, which resulted in new peak hours. It is anticipated that these changes will have a domino effect on Tehran&#039;s transit system as a whole. The system may not be able to handle the changes in behavior, as it was designed to deal with pre-pandemic behavior patterns. There is a need for rescheduling to resolve the problem. Additionally, the government should develop a long-term plan for restoring public transportation demand to its pre-pandemic level.&lt;/span&gt;</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">public transportation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">COVID-19 vaccination</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Transit Ridership</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Machine Learning</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Time series Clustering</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijte.ir/article_181837_73320454bf49795462956b6c45ea6885.pdf</ArchiveCopySource>
</Article>
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