{"id":"https://openalex.org/W7117770369","doi":"https://doi.org/10.3390/systems14010047","title":"A Multi-Agent Regional Traffic Signal Control System Integrating Traffic Flow Prediction and Graph Attention Networks","display_name":"A Multi-Agent Regional Traffic Signal Control System Integrating Traffic Flow Prediction and Graph Attention Networks","publication_year":2025,"publication_date":"2025-12-31","ids":{"openalex":"https://openalex.org/W7117770369","doi":"https://doi.org/10.3390/systems14010047"},"language":"en","primary_location":{"id":"doi:10.3390/systems14010047","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010047","pdf_url":"https://www.mdpi.com/2079-8954/14/1/47/pdf?version=1767193072","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-8954/14/1/47/pdf?version=1767193072","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chao Sun","orcid":"https://orcid.org/0000-0002-1543-5790"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Sun","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"],"raw_orcid":"https://orcid.org/0000-0002-1543-5790","affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121642520","display_name":"Yuhao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Yang","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121664993","display_name":"Jiacheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiacheng Li","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121664744","display_name":"Weiyi Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyi Fang","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121651737","display_name":"Peng Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China","institution_ids":["https://openalex.org/I115592961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.7992,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7937272,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"14","issue":"1","first_page":"47","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5167999863624573,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.5167999863624573,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.4025000035762787,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.007300000172108412,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6521999835968018},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5303999781608582},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.49140000343322754},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.48500001430511475},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.4830000102519989},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4740000069141388},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4458000063896179},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.44369998574256897}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.677299976348877},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.48500001430511475},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4740000069141388},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3813000023365021},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C2778391309","wikidata":"https://www.wikidata.org/wiki/Q7832527","display_name":"Traffic simulation","level":3,"score":0.32339999079704285},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30160000920295715},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.29490000009536743},{"id":"https://openalex.org/C2776006172","wikidata":"https://www.wikidata.org/wiki/Q7512741","display_name":"Signal timing","level":3,"score":0.27219998836517334},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.2597000002861023},{"id":"https://openalex.org/C16160715","wikidata":"https://www.wikidata.org/wiki/Q1640676","display_name":"Traffic engineering","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/systems14010047","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010047","pdf_url":"https://www.mdpi.com/2079-8954/14/1/47/pdf?version=1767193072","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ae7b12e278db417b9daa82158510c1bc","is_oa":true,"landing_page_url":"https://doaj.org/article/ae7b12e278db417b9daa82158510c1bc","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Systems, Vol 14, Iss 1, p 47 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/systems14010047","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010047","pdf_url":"https://www.mdpi.com/2079-8954/14/1/47/pdf?version=1767193072","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.49506136775016785,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7117770369.pdf","grobid_xml":"https://content.openalex.org/works/W7117770369.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Adaptive":[0],"traffic":[1,45,52,92,106],"signal":[2,102,152],"control":[3,27],"is":[4],"a":[5,95,140],"critical":[6],"component":[7],"of":[8,50,79,151],"intelligent":[9],"transportation":[10],"systems,":[11],"and":[12,26,43,54,74,112,130,161,167,182,189,194],"multi-agent":[13],"deep":[14],"reinforcement":[15],"learning":[16],"(MARL)":[17],"has":[18],"attracted":[19],"increasing":[20],"interest":[21],"due":[22],"to":[23,65,119,147],"its":[24],"scalability":[25],"efficiency.":[28],"However,":[29],"existing":[30],"methods":[31],"have":[32],"two":[33],"major":[34],"drawbacks:":[35],"(i)":[36],"they":[37],"are":[38,59],"largely":[39],"driven":[40],"by":[41],"current":[42],"historical":[44],"states,":[46],"without":[47],"explicit":[48],"forecasting":[49,107],"upcoming":[51],"conditions,":[53],"(ii)":[55],"their":[56],"coordination":[57],"mechanisms":[58],"often":[60],"weak,":[61],"making":[62],"it":[63],"difficult":[64],"model":[66],"complex":[67],"spatial":[68,134],"dependencies":[69],"in":[70],"large-scale":[71],"road":[72],"networks":[73,163],"thereby":[75],"limiting":[76],"the":[77,116,124,156],"benefits":[78],"coordinated":[80],"control.":[81,103],"To":[82],"address":[83],"these":[84],"issues,":[85],"we":[86,138],"propose":[87],"TG-MADDPG,":[88],"which":[89],"integrates":[90],"short-term":[91],"prediction":[93],"with":[94],"graph":[96],"attention":[97],"network":[98],"(GAT)":[99],"for":[100],"regional":[101],"A":[104],"WT-GWO-CNN-LSTM":[105],"module":[108],"predicts":[109],"near-future":[110],"states":[111],"injects":[113],"them":[114],"into":[115],"MARL":[117],"framework":[118],"support":[120],"anticipatory":[121],"decision-making.":[122],"Meanwhile,":[123],"GAT":[125],"dynamically":[126],"encodes":[127],"road-network":[128],"topology":[129],"adaptively":[131],"captures":[132],"inter-intersection":[133],"correlations.":[135],"In":[136],"addition,":[137],"design":[139],"reward":[141],"based":[142],"on":[143,155],"normalized":[144],"pressure":[145],"difference":[146],"guide":[148],"cooperative":[149],"optimization":[150],"timing.":[153],"Experiments":[154],"SUMO":[157],"simulator":[158],"across":[159],"synthetic":[160],"real-world":[162],"under":[164],"both":[165],"off-peak":[166],"peak":[168],"demands":[169],"show":[170],"that":[171],"TG-MADDPG":[172],"consistently":[173],"achieves":[174],"lower":[175],"average":[176],"waiting":[177],"times,":[178],"shorter":[179],"queue":[180],"lengths,":[181],"higher":[183],"cumulative":[184],"rewards":[185],"than":[186],"IQL,":[187],"MADDPG,":[188],"GMADDPG,":[190],"demonstrating":[191],"strong":[192],"effectiveness":[193],"generalization.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-31T00:00:00"}
