Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks
In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for th...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on control systems technology 2022-01, Vol.30 (1), p.57-70 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 70 |
---|---|
container_issue | 1 |
container_start_page | 57 |
container_title | IEEE transactions on control systems technology |
container_volume | 30 |
creator | Wu, Na Li, Dewei Xi, Yugeng |
description | In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for the cooperative control of mixed urban and freeway traffic networks is developed. First, an integrated traffic model is presented to characterize the interactions between the urban and freeway networks. In addition, a partitioning method is proposed, and then, the mixed traffic network is divided among urban agents and freeway agents for the easy implementation of the distributed control framework. The optimization problem of the whole network can then be decomposed into a number of suboptimization problems based on the partition of the network. In the proposed distributed control strategy, each agent solves its own optimization problem independently with local information and transmitted information from neighboring agents to seek the Nash equilibrium. Finally, the computational efficiency and the effectiveness of the distributed integrated control strategy of mixed traffic networks are evaluated through a numerical example. |
doi_str_mv | 10.1109/TCST.2021.3055071 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TCST_2021_3055071</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9352544</ieee_id><sourcerecordid>2610182581</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-c82da8d2a9e5bfc484417c2449191c71579a4396c9fb2161d5ded3ce9c86d8ab3</originalsourceid><addsrcrecordid>eNo9kM1OwzAQhC0EEqXwAIiLJc4pXv_FPqJAoVKBA6kQJ8txHEgpCTiuSt-eRC2cdrQ7syN9CJ0DmQAQfZVnz_mEEgoTRoQgKRygEQihEqKkOOw1kSyRgsljdNJ1S0KAC5qO0OtN3cVQF-voSzxron8LdpBZ28TQrnBbYYsf6p9-lQdbVbXDjz5u2vCBX-r4jhehsA22TYmnwfuN3f6du1N0VNlV58_2c4wW09s8u0_mT3ez7HqeOKpZTJyipVUltdqLonJccQ6po5xr0OBSEKm2nGnpdFVQkFCK0pfMee2ULJUt2Bhd7v5-hfZ77btolu06NH2loRIIKCoU9C7YuVxouy74ynyF-tOGrQFiBoJmIGgGgmZPsM9c7DK19_7fr5mggnP2C1BEbJY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2610182581</pqid></control><display><type>article</type><title>Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks</title><source>IEEE Electronic Library (IEL)</source><creator>Wu, Na ; Li, Dewei ; Xi, Yugeng</creator><creatorcontrib>Wu, Na ; Li, Dewei ; Xi, Yugeng</creatorcontrib><description>In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for the cooperative control of mixed urban and freeway traffic networks is developed. First, an integrated traffic model is presented to characterize the interactions between the urban and freeway networks. In addition, a partitioning method is proposed, and then, the mixed traffic network is divided among urban agents and freeway agents for the easy implementation of the distributed control framework. The optimization problem of the whole network can then be decomposed into a number of suboptimization problems based on the partition of the network. In the proposed distributed control strategy, each agent solves its own optimization problem independently with local information and transmitted information from neighboring agents to seek the Nash equilibrium. Finally, the computational efficiency and the effectiveness of the distributed integrated control strategy of mixed traffic networks are evaluated through a numerical example.</description><identifier>ISSN: 1063-6536</identifier><identifier>EISSN: 1558-0865</identifier><identifier>DOI: 10.1109/TCST.2021.3055071</identifier><identifier>CODEN: IETTE2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Centralized control ; Computational modeling ; Cooperative control ; Decentralized control ; Distributed control ; Highways ; integrated control ; mixed traffic networks ; Nash equilibrium ; Networks ; Optimization ; Predictive models ; Roads ; Traffic control ; Traffic models ; urban and freeway agents ; Vehicle dynamics</subject><ispartof>IEEE transactions on control systems technology, 2022-01, Vol.30 (1), p.57-70</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-c82da8d2a9e5bfc484417c2449191c71579a4396c9fb2161d5ded3ce9c86d8ab3</citedby><cites>FETCH-LOGICAL-c293t-c82da8d2a9e5bfc484417c2449191c71579a4396c9fb2161d5ded3ce9c86d8ab3</cites><orcidid>0000-0002-0604-7518 ; 0000-0001-8869-5676 ; 0000-0002-9354-3906</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9352544$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9352544$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wu, Na</creatorcontrib><creatorcontrib>Li, Dewei</creatorcontrib><creatorcontrib>Xi, Yugeng</creatorcontrib><title>Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks</title><title>IEEE transactions on control systems technology</title><addtitle>TCST</addtitle><description>In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for the cooperative control of mixed urban and freeway traffic networks is developed. First, an integrated traffic model is presented to characterize the interactions between the urban and freeway networks. In addition, a partitioning method is proposed, and then, the mixed traffic network is divided among urban agents and freeway agents for the easy implementation of the distributed control framework. The optimization problem of the whole network can then be decomposed into a number of suboptimization problems based on the partition of the network. In the proposed distributed control strategy, each agent solves its own optimization problem independently with local information and transmitted information from neighboring agents to seek the Nash equilibrium. Finally, the computational efficiency and the effectiveness of the distributed integrated control strategy of mixed traffic networks are evaluated through a numerical example.</description><subject>Centralized control</subject><subject>Computational modeling</subject><subject>Cooperative control</subject><subject>Decentralized control</subject><subject>Distributed control</subject><subject>Highways</subject><subject>integrated control</subject><subject>mixed traffic networks</subject><subject>Nash equilibrium</subject><subject>Networks</subject><subject>Optimization</subject><subject>Predictive models</subject><subject>Roads</subject><subject>Traffic control</subject><subject>Traffic models</subject><subject>urban and freeway agents</subject><subject>Vehicle dynamics</subject><issn>1063-6536</issn><issn>1558-0865</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1OwzAQhC0EEqXwAIiLJc4pXv_FPqJAoVKBA6kQJ8txHEgpCTiuSt-eRC2cdrQ7syN9CJ0DmQAQfZVnz_mEEgoTRoQgKRygEQihEqKkOOw1kSyRgsljdNJ1S0KAC5qO0OtN3cVQF-voSzxron8LdpBZ28TQrnBbYYsf6p9-lQdbVbXDjz5u2vCBX-r4jhehsA22TYmnwfuN3f6du1N0VNlV58_2c4wW09s8u0_mT3ez7HqeOKpZTJyipVUltdqLonJccQ6po5xr0OBSEKm2nGnpdFVQkFCK0pfMee2ULJUt2Bhd7v5-hfZ77btolu06NH2loRIIKCoU9C7YuVxouy74ynyF-tOGrQFiBoJmIGgGgmZPsM9c7DK19_7fr5mggnP2C1BEbJY</recordid><startdate>202201</startdate><enddate>202201</enddate><creator>Wu, Na</creator><creator>Li, Dewei</creator><creator>Xi, Yugeng</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-0604-7518</orcidid><orcidid>https://orcid.org/0000-0001-8869-5676</orcidid><orcidid>https://orcid.org/0000-0002-9354-3906</orcidid></search><sort><creationdate>202201</creationdate><title>Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks</title><author>Wu, Na ; Li, Dewei ; Xi, Yugeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-c82da8d2a9e5bfc484417c2449191c71579a4396c9fb2161d5ded3ce9c86d8ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Centralized control</topic><topic>Computational modeling</topic><topic>Cooperative control</topic><topic>Decentralized control</topic><topic>Distributed control</topic><topic>Highways</topic><topic>integrated control</topic><topic>mixed traffic networks</topic><topic>Nash equilibrium</topic><topic>Networks</topic><topic>Optimization</topic><topic>Predictive models</topic><topic>Roads</topic><topic>Traffic control</topic><topic>Traffic models</topic><topic>urban and freeway agents</topic><topic>Vehicle dynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Na</creatorcontrib><creatorcontrib>Li, Dewei</creatorcontrib><creatorcontrib>Xi, Yugeng</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on control systems technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wu, Na</au><au>Li, Dewei</au><au>Xi, Yugeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks</atitle><jtitle>IEEE transactions on control systems technology</jtitle><stitle>TCST</stitle><date>2022-01</date><risdate>2022</risdate><volume>30</volume><issue>1</issue><spage>57</spage><epage>70</epage><pages>57-70</pages><issn>1063-6536</issn><eissn>1558-0865</eissn><coden>IETTE2</coden><abstract>In the optimization of mixed urban and freeway networks, most existing control strategies implement centralized controllers that are not appropriate for real-time control in large-scale traffic networks due to the huge computational complexity. In this article, a distributed control framework for the cooperative control of mixed urban and freeway traffic networks is developed. First, an integrated traffic model is presented to characterize the interactions between the urban and freeway networks. In addition, a partitioning method is proposed, and then, the mixed traffic network is divided among urban agents and freeway agents for the easy implementation of the distributed control framework. The optimization problem of the whole network can then be decomposed into a number of suboptimization problems based on the partition of the network. In the proposed distributed control strategy, each agent solves its own optimization problem independently with local information and transmitted information from neighboring agents to seek the Nash equilibrium. Finally, the computational efficiency and the effectiveness of the distributed integrated control strategy of mixed traffic networks are evaluated through a numerical example.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TCST.2021.3055071</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-0604-7518</orcidid><orcidid>https://orcid.org/0000-0001-8869-5676</orcidid><orcidid>https://orcid.org/0000-0002-9354-3906</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1063-6536 |
ispartof | IEEE transactions on control systems technology, 2022-01, Vol.30 (1), p.57-70 |
issn | 1063-6536 1558-0865 |
language | eng |
recordid | cdi_crossref_primary_10_1109_TCST_2021_3055071 |
source | IEEE Electronic Library (IEL) |
subjects | Centralized control Computational modeling Cooperative control Decentralized control Distributed control Highways integrated control mixed traffic networks Nash equilibrium Networks Optimization Predictive models Roads Traffic control Traffic models urban and freeway agents Vehicle dynamics |
title | Distributed Integrated Control of a Mixed Traffic Network With Urban and Freeway Networks |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T00%3A30%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Distributed%20Integrated%20Control%20of%20a%20Mixed%20Traffic%20Network%20With%20Urban%20and%20Freeway%20Networks&rft.jtitle=IEEE%20transactions%20on%20control%20systems%20technology&rft.au=Wu,%20Na&rft.date=2022-01&rft.volume=30&rft.issue=1&rft.spage=57&rft.epage=70&rft.pages=57-70&rft.issn=1063-6536&rft.eissn=1558-0865&rft.coden=IETTE2&rft_id=info:doi/10.1109/TCST.2021.3055071&rft_dat=%3Cproquest_RIE%3E2610182581%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2610182581&rft_id=info:pmid/&rft_ieee_id=9352544&rfr_iscdi=true |