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<Article>
<Journal>
				<PublisherName></PublisherName>
				<JournalTitle>Transactions on Machine Intelligence</JournalTitle>
				<Issn>2821-1693</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2018</Year>
					<Month>06</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Single Intersection Control For Urban Traffic Using Model-Based Predictive Control</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>81</FirstPage>
			<LastPage>91</LastPage>
			<ELocationID EIdType="pii">205233</ELocationID>
			
<ELocationID EIdType="doi">10.47176/TMI.2018.81</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>S.</FirstName>
					<LastName>Jafari</LastName>
<Affiliation>Master's Degree in Electrical Engineering with a focus on Control, Faculty of Engineering, University of Qom, Qom, Iran</Affiliation>

</Author>
<Author>
					<FirstName>S.</FirstName>
					<LastName>Mohammad Ali Nejad</LastName>
<Affiliation>Assistant Professor, Electrical and Electronics Engineering Department, University of Qom, Qom, Iran</Affiliation>

</Author>
<Author>
					<FirstName>R.</FirstName>
					<LastName>Ghasemi</LastName>
<Affiliation>Associate Professor, Electrical Engineering, University of Qom, Qom, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2024</Year>
					<Month>03</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, urban road traffic control is presented using model-based predictive control, and the modeling of traffic and state-space parameters at an intersection is extracted. Subsequently, a predictive controller is designed to manage the traffic lights based on the queue length and the number of incoming and outgoing vehicles as inputs to the controller. The cost function is calculated using state-space parameters, and given that the output is predicted according to the model at future moments, optimal control efforts to minimize the cost function are obtained. The stability of the system using predictive control is proven. The advantages of this controller, such as the ability to optimize the current state while considering future states and its design simplicity, have resulted in the predictive controller performing significantly better compared to the fixed-time method. The simulation results also indicate the desirable performance of the controller compared to other control methods, leading to a reduction in queue length.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Traffic Control</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Model-Based Predictive Control</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Single Intersection</Param>
			</Object>
		</ObjectList>
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