A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios
This paper presents a swarm approach to the problem of synchronisation of traffic lights in order to reduce traffic jams in urban scenarios. Other approaches for reducing jams have been proposed. A classical one is to coordinate or synchronise traffic lights so that vehicles can traverse an arterial...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 417 |
---|---|
container_issue | |
container_start_page | 416 |
container_title | |
container_volume | |
creator | de Oliveira, Denise Ferreira, Paulo Roberto Bazzan, Ana L. C. Klügl, Franziska |
description | This paper presents a swarm approach to the problem of synchronisation of traffic lights in order to reduce traffic jams in urban scenarios. Other approaches for reducing jams have been proposed. A classical one is to coordinate or synchronise traffic lights so that vehicles can traverse an arterial in one direction, with a specific speed, without stopping. Coordination here means that if appropriate signal plans are selected to run at the adjacent traffic lights, a “green wave” is built so that drivers do not have to stop at junctions. This approach works fine in traffic networks with defined traffic flow patterns like for instance morning flow towards downtown and its similar afternoon rush hour. However, in cities where these patterns are not clear, that approach may not be effective. This is clearly the case in big cities where the business centres are no longer located exclusively downtown. |
doi_str_mv | 10.1007/978-3-540-28646-2_43 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>pascalfrancis_sprin</sourceid><recordid>TN_cdi_pascalfrancis_primary_16107448</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>16107448</sourcerecordid><originalsourceid>FETCH-LOGICAL-p228t-53e4537cd99256de3abe9b8db14c7a0c7cd6864063da12de49fdb08a4a78b4e33</originalsourceid><addsrcrecordid>eNpFkE1LAzEQhuMXWGr_gYdcPEaTTLrZHKtoFQoKa89hNputq9vskhTEf2_aCs5l4H1eBuYh5FrwW8G5vjO6ZMDmijNZFqpg0io4IbMcQw4PmTwlE1EIwQCUOftnstBSn5MJBy6Z0QouySylT55HcDBaT8hyQatvjFt2j8k3dDGOcUD3Qdsh0sr33u26IdChpVW3CdjTtx5Dol2g61hjoJXzAWM3pCty0WKf_OxvT8n66fH94ZmtXpcvD4sVG6Usd2wOXs1Bu8YYOS8aD1h7U5dNLZTTyF0mRf6IF9CgkI1Xpm1qXqJCXdbKA0zJzfHuiMlh30YMrkt2jN0W44_NFrhWqsw9eeyljMLGR1sPw1eygtu9VZsVWbBZkj0YtHur8AuZnWQp</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios</title><source>Springer Books</source><creator>de Oliveira, Denise ; Ferreira, Paulo Roberto ; Bazzan, Ana L. C. ; Klügl, Franziska</creator><contributor>Gambardella, Luca Maria ; Blum, Christian ; Dorigo, Marco ; Birattari, Mauro ; Stützle, Thomas ; Mondada, Francesco</contributor><creatorcontrib>de Oliveira, Denise ; Ferreira, Paulo Roberto ; Bazzan, Ana L. C. ; Klügl, Franziska ; Gambardella, Luca Maria ; Blum, Christian ; Dorigo, Marco ; Birattari, Mauro ; Stützle, Thomas ; Mondada, Francesco</creatorcontrib><description>This paper presents a swarm approach to the problem of synchronisation of traffic lights in order to reduce traffic jams in urban scenarios. Other approaches for reducing jams have been proposed. A classical one is to coordinate or synchronise traffic lights so that vehicles can traverse an arterial in one direction, with a specific speed, without stopping. Coordination here means that if appropriate signal plans are selected to run at the adjacent traffic lights, a “green wave” is built so that drivers do not have to stop at junctions. This approach works fine in traffic networks with defined traffic flow patterns like for instance morning flow towards downtown and its similar afternoon rush hour. However, in cities where these patterns are not clear, that approach may not be effective. This is clearly the case in big cities where the business centres are no longer located exclusively downtown.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540226727</identifier><identifier>ISBN: 3540226729</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540286462</identifier><identifier>EISBN: 3540286462</identifier><identifier>DOI: 10.1007/978-3-540-28646-2_43</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Learning and adaptive systems ; Response Threshold ; Social Insect ; Street Section ; Task Allocation ; Traffic Light</subject><ispartof>Ant Colony Optimization and Swarm Intelligence, 2004, p.416-417</ispartof><rights>Springer-Verlag Berlin Heidelberg 2004</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/978-3-540-28646-2_43$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-540-28646-2_43$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,779,780,784,789,790,793,4040,4041,27916,38246,41433,42502</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16107448$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Gambardella, Luca Maria</contributor><contributor>Blum, Christian</contributor><contributor>Dorigo, Marco</contributor><contributor>Birattari, Mauro</contributor><contributor>Stützle, Thomas</contributor><contributor>Mondada, Francesco</contributor><creatorcontrib>de Oliveira, Denise</creatorcontrib><creatorcontrib>Ferreira, Paulo Roberto</creatorcontrib><creatorcontrib>Bazzan, Ana L. C.</creatorcontrib><creatorcontrib>Klügl, Franziska</creatorcontrib><title>A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios</title><title>Ant Colony Optimization and Swarm Intelligence</title><description>This paper presents a swarm approach to the problem of synchronisation of traffic lights in order to reduce traffic jams in urban scenarios. Other approaches for reducing jams have been proposed. A classical one is to coordinate or synchronise traffic lights so that vehicles can traverse an arterial in one direction, with a specific speed, without stopping. Coordination here means that if appropriate signal plans are selected to run at the adjacent traffic lights, a “green wave” is built so that drivers do not have to stop at junctions. This approach works fine in traffic networks with defined traffic flow patterns like for instance morning flow towards downtown and its similar afternoon rush hour. However, in cities where these patterns are not clear, that approach may not be effective. This is clearly the case in big cities where the business centres are no longer located exclusively downtown.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><subject>Response Threshold</subject><subject>Social Insect</subject><subject>Street Section</subject><subject>Task Allocation</subject><subject>Traffic Light</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540226727</isbn><isbn>3540226729</isbn><isbn>9783540286462</isbn><isbn>3540286462</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpFkE1LAzEQhuMXWGr_gYdcPEaTTLrZHKtoFQoKa89hNputq9vskhTEf2_aCs5l4H1eBuYh5FrwW8G5vjO6ZMDmijNZFqpg0io4IbMcQw4PmTwlE1EIwQCUOftnstBSn5MJBy6Z0QouySylT55HcDBaT8hyQatvjFt2j8k3dDGOcUD3Qdsh0sr33u26IdChpVW3CdjTtx5Dol2g61hjoJXzAWM3pCty0WKf_OxvT8n66fH94ZmtXpcvD4sVG6Usd2wOXs1Bu8YYOS8aD1h7U5dNLZTTyF0mRf6IF9CgkI1Xpm1qXqJCXdbKA0zJzfHuiMlh30YMrkt2jN0W44_NFrhWqsw9eeyljMLGR1sPw1eygtu9VZsVWbBZkj0YtHur8AuZnWQp</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>de Oliveira, Denise</creator><creator>Ferreira, Paulo Roberto</creator><creator>Bazzan, Ana L. C.</creator><creator>Klügl, Franziska</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios</title><author>de Oliveira, Denise ; Ferreira, Paulo Roberto ; Bazzan, Ana L. C. ; Klügl, Franziska</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p228t-53e4537cd99256de3abe9b8db14c7a0c7cd6864063da12de49fdb08a4a78b4e33</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Learning and adaptive systems</topic><topic>Response Threshold</topic><topic>Social Insect</topic><topic>Street Section</topic><topic>Task Allocation</topic><topic>Traffic Light</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Oliveira, Denise</creatorcontrib><creatorcontrib>Ferreira, Paulo Roberto</creatorcontrib><creatorcontrib>Bazzan, Ana L. C.</creatorcontrib><creatorcontrib>Klügl, Franziska</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Oliveira, Denise</au><au>Ferreira, Paulo Roberto</au><au>Bazzan, Ana L. C.</au><au>Klügl, Franziska</au><au>Gambardella, Luca Maria</au><au>Blum, Christian</au><au>Dorigo, Marco</au><au>Birattari, Mauro</au><au>Stützle, Thomas</au><au>Mondada, Francesco</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios</atitle><btitle>Ant Colony Optimization and Swarm Intelligence</btitle><date>2004</date><risdate>2004</risdate><spage>416</spage><epage>417</epage><pages>416-417</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540226727</isbn><isbn>3540226729</isbn><eisbn>9783540286462</eisbn><eisbn>3540286462</eisbn><abstract>This paper presents a swarm approach to the problem of synchronisation of traffic lights in order to reduce traffic jams in urban scenarios. Other approaches for reducing jams have been proposed. A classical one is to coordinate or synchronise traffic lights so that vehicles can traverse an arterial in one direction, with a specific speed, without stopping. Coordination here means that if appropriate signal plans are selected to run at the adjacent traffic lights, a “green wave” is built so that drivers do not have to stop at junctions. This approach works fine in traffic networks with defined traffic flow patterns like for instance morning flow towards downtown and its similar afternoon rush hour. However, in cities where these patterns are not clear, that approach may not be effective. This is clearly the case in big cities where the business centres are no longer located exclusively downtown.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/978-3-540-28646-2_43</doi><tpages>2</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0302-9743 |
ispartof | Ant Colony Optimization and Swarm Intelligence, 2004, p.416-417 |
issn | 0302-9743 1611-3349 |
language | eng |
recordid | cdi_pascalfrancis_primary_16107448 |
source | Springer Books |
subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Learning and adaptive systems Response Threshold Social Insect Street Section Task Allocation Traffic Light |
title | A Swarm-Based Approach for Selection of Signal Plans in Urban Scenarios |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T05%3A55%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20Swarm-Based%20Approach%20for%20Selection%20of%20Signal%20Plans%20in%20Urban%20Scenarios&rft.btitle=Ant%20Colony%20Optimization%20and%20Swarm%20Intelligence&rft.au=de%20Oliveira,%20Denise&rft.date=2004&rft.spage=416&rft.epage=417&rft.pages=416-417&rft.issn=0302-9743&rft.eissn=1611-3349&rft.isbn=9783540226727&rft.isbn_list=3540226729&rft_id=info:doi/10.1007/978-3-540-28646-2_43&rft_dat=%3Cpascalfrancis_sprin%3E16107448%3C/pascalfrancis_sprin%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783540286462&rft.eisbn_list=3540286462&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |