{"id":"https://openalex.org/W7135193001","doi":"https://doi.org/10.48550/arxiv.2603.12096","title":"A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control","display_name":"A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135193001","doi":"https://doi.org/10.48550/arxiv.2603.12096"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.12096","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12096","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.12096","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5124017084","display_name":"Sheng-You Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Sheng-You","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123910268","display_name":"Hsiao-Chuan Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Hsiao-Chuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123885723","display_name":"Yen-Chi Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yen-Chi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129047960","display_name":"Ting-Han Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Ting-Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128965378","display_name":"I-Hau Yeh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeh, I-Hau","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093192059","display_name":"Sheng-Yao Kuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuan, Sheng-Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129091064","display_name":"Chien-Yao Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Chien-Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037009054","display_name":"Hsuan-Han Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Hsuan-Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124027890","display_name":"I-Chen Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, I-Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9124000072479248,"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"}},"topics":[{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9124000072479248,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.049800001084804535,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.006099999882280827,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7904999852180481},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6000000238418579},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5644000172615051},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5192999839782715},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/vissim","display_name":"VisSim","score":0.4162999987602234},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4142000079154968},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.40459999442100525},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.37709999084472656}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7904999852180481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6757000088691711},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6000000238418579},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5644000172615051},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5192999839782715},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C2775988433","wikidata":"https://www.wikidata.org/wiki/Q369244","display_name":"VisSim","level":3,"score":0.4162999987602234},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3840000033378601},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.37709999084472656},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C2778047078","wikidata":"https://www.wikidata.org/wiki/Q82299449","display_name":"Tardiness","level":4,"score":0.335099995136261},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30070000886917114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30070000886917114},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C31531917","wikidata":"https://www.wikidata.org/wiki/Q915157","display_name":"Robust control","level":3,"score":0.266400009393692},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26350000500679016},{"id":"https://openalex.org/C3018134525","wikidata":"https://www.wikidata.org/wiki/Q2501541","display_name":"Control signal","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.2596000134944916},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.12096","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12096","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.12096","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.12096","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0,43],"Learning":[1,44],"(RL)":[2],"in":[3,11,48,154],"Traffic":[4],"Signal":[5],"Control":[6],"(TSC)":[7],"faces":[8],"significant":[9],"hurdles":[10],"real-world":[12],"deployment":[13],"due":[14],"to":[15,18,68,72],"limited":[16],"generalization":[17,153],"dynamic":[19,69],"traffic":[20,51,156],"flow":[21],"variations.":[22],"Existing":[23],"approaches":[24],"often":[25],"overfit":[26],"static":[27],"patterns":[28],"and":[29,90,97,158],"use":[30],"action":[31,85],"spaces":[32],"incompatible":[33],"with":[34,107,110],"driver":[35],"expectations.":[36],"This":[37],"paper":[38],"proposes":[39],"a":[40,62,79,99,164],"robust":[41],"Multi-Agent":[42],"(MARL)":[45],"framework":[46,54,136],"validated":[47],"the":[49,104,121],"Vissim":[50],"simulator.":[52],"The":[53,148],"integrates":[55],"three":[56],"mechanisms:":[57],"(1)":[58],"Turning":[59],"Ratio":[60],"Randomization,":[61],"training":[63],"strategy":[64],"that":[65,134],"exposes":[66],"agents":[67],"turning":[70],"probabilities":[71],"enhance":[73],"robustness":[74],"against":[75],"unseen":[76,155],"scenarios;":[77],"(2)":[78],"stability-oriented":[80],"Exponential":[81],"Phase":[82],"Duration":[83],"Adjustment":[84],"space,":[86],"which":[87],"balances":[88],"responsiveness":[89],"precision":[91],"through":[92],"cyclical,":[93],"exponential":[94],"phase":[95],"adjustments;":[96],"(3)":[98],"Neighbor-Based":[100],"Observation":[101],"scheme":[102],"utilizing":[103],"MAPPO":[105],"algorithm":[106],"Centralized":[108],"Training":[109],"Decentralized":[111],"Execution":[112],"(CTDE).":[113],"By":[114],"leveraging":[115],"centralized":[116],"updates,":[117],"this":[118],"approach":[119],"approximates":[120],"efficacy":[122],"of":[123],"global":[124],"observations":[125],"while":[126],"maintaining":[127],"scalable":[128],"local":[129],"communication.":[130],"Experimental":[131],"results":[132],"demonstrate":[133],"our":[135],"outperforms":[137],"standard":[138],"RL":[139],"baselines,":[140],"reducing":[141],"average":[142],"waiting":[143],"time":[144],"by":[145],"over":[146],"10%.":[147],"proposed":[149],"model":[150],"exhibits":[151],"superior":[152],"scenarios":[157],"maintains":[159],"high":[160],"control":[161],"stability,":[162],"offering":[163],"practical":[165],"solution":[166],"for":[167],"adaptive":[168],"signal":[169],"control.":[170]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-14T00:00:00"}