{"id":"https://openalex.org/W4323338523","doi":"https://doi.org/10.1109/tits.2023.3248649","title":"Deep Koopman Traffic Modeling for Freeway Ramp Metering","display_name":"Deep Koopman Traffic Modeling for Freeway Ramp Metering","publication_year":2023,"publication_date":"2023-03-06","ids":{"openalex":"https://openalex.org/W4323338523","doi":"https://doi.org/10.1109/tits.2023.3248649"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3248649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3248649","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005186365","display_name":"Chuanye Gu","orcid":"https://orcid.org/0000-0002-7076-057X"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuanye Gu","raw_affiliation_strings":["School of Management, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Management, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007742331","display_name":"Tao Zhou","orcid":"https://orcid.org/0000-0003-3456-8983"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tao Zhou","raw_affiliation_strings":["Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Geelong, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045897515","display_name":"Changzhi Wu","orcid":"https://orcid.org/0000-0002-2276-6862"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changzhi Wu","raw_affiliation_strings":["School of Management, Guangzhou University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Management, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5005186365"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":2.8172,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90385416,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"24","issue":"6","first_page":"6001","last_page":"6013"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9968000054359436,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/metering-mode","display_name":"Metering mode","score":0.7711947560310364},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6034693717956543},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5727363228797913},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5538354516029358},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5219292640686035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5141237378120422},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.513237714767456},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.484294593334198},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4734953045845032},{"id":"https://openalex.org/keywords/model-predictive-control","display_name":"Model predictive control","score":0.4470321536064148},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.3934844732284546},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3866349756717682},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.36348074674606323},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.27797573804855347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20782342553138733},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.1756625771522522},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.14133265614509583}],"concepts":[{"id":"https://openalex.org/C30905978","wikidata":"https://www.wikidata.org/wiki/Q815598","display_name":"Metering mode","level":2,"score":0.7711947560310364},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6034693717956543},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5727363228797913},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5538354516029358},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5219292640686035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5141237378120422},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.513237714767456},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.484294593334198},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4734953045845032},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.4470321536064148},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3934844732284546},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3866349756717682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.36348074674606323},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27797573804855347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20782342553138733},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.1756625771522522},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.14133265614509583},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2023.3248649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3248649","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G6157611754","display_name":null,"funder_award_id":"11991020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7742573971","display_name":null,"funder_award_id":"2022A1515011761","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W614362261","https://openalex.org/W790961892","https://openalex.org/W1484203172","https://openalex.org/W1591018827","https://openalex.org/W1967804417","https://openalex.org/W1969563507","https://openalex.org/W1975864868","https://openalex.org/W1977556410","https://openalex.org/W1984568974","https://openalex.org/W1997054581","https://openalex.org/W2004797340","https://openalex.org/W2014356541","https://openalex.org/W2016315007","https://openalex.org/W2032549372","https://openalex.org/W2036271427","https://openalex.org/W2037141248","https://openalex.org/W2060806808","https://openalex.org/W2065672848","https://openalex.org/W2067035505","https://openalex.org/W2076932342","https://openalex.org/W2078898317","https://openalex.org/W2098382127","https://openalex.org/W2114876173","https://openalex.org/W2126999002","https://openalex.org/W2128798488","https://openalex.org/W2139316239","https://openalex.org/W2154271150","https://openalex.org/W2159633185","https://openalex.org/W2164954534","https://openalex.org/W2519706319","https://openalex.org/W2561027863","https://openalex.org/W2591292776","https://openalex.org/W2619723897","https://openalex.org/W2924607344","https://openalex.org/W2939120428","https://openalex.org/W2971232013","https://openalex.org/W2990033500","https://openalex.org/W3031785929","https://openalex.org/W3038118776","https://openalex.org/W3096189530","https://openalex.org/W3096866065","https://openalex.org/W3099803807","https://openalex.org/W3124522123","https://openalex.org/W3165455659","https://openalex.org/W3194366730","https://openalex.org/W3209319237","https://openalex.org/W4210312713","https://openalex.org/W4212811589","https://openalex.org/W4287078811","https://openalex.org/W4304086169","https://openalex.org/W6629034932","https://openalex.org/W6631943919","https://openalex.org/W6742271211","https://openalex.org/W6784537573","https://openalex.org/W6798557224"],"related_works":["https://openalex.org/W2172038067","https://openalex.org/W2124386340","https://openalex.org/W2047787160","https://openalex.org/W2374664215","https://openalex.org/W2365785480","https://openalex.org/W2393509435","https://openalex.org/W1588144310","https://openalex.org/W2004764932","https://openalex.org/W2118920847","https://openalex.org/W2044870794"],"abstract_inverted_index":{"Ramp":[0],"metering":[1,128],"has":[2,53],"been":[3,54],"considered":[4],"as":[5],"one":[6],"of":[7,12,23,32,83,92,125,136,151,163,176],"the":[8,15,19,24,84,89,93,99,114,122,126,130,134,137,143,146,161,164,169,173,177],"most":[9],"effective":[10],"approaches":[11],"dealing":[13],"with":[14,113],"traffic":[16,26,147],"congestion":[17],"on":[18,70,98,129,142,167],"freeways.":[20],"The":[21,158],"modelling":[22,57,67],"freeway":[25],"flow":[27],"dynamics":[28,170],"is":[29,106,119],"challenging":[30],"because":[31],"its":[33],"non-linearity":[34],"and":[35,95,172],"uncertainty.":[36],"Recently,":[37],"Koopman":[38,76,85,117],"operator,":[39],"which":[40],"transfers":[41],"a":[42,46,65,80,101,109],"non-linear":[43],"system":[44,48],"to":[45,78],"linear":[47],"in":[49,145],"an":[50],"infinite-dimensional":[51],"space,":[52],"studied":[55],"for":[56,121],"complex":[58],"dynamics.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63],"propose":[64],"data-driven":[66],"approach":[68,166],"based":[69,141],"neural":[71],"networks,":[72],"denoted":[73],"by":[74],"deep":[75,116],"model,":[77],"learn":[79],"finite-dimensional":[81],"approximation":[82],"operator.":[86],"To":[87,132],"consider":[88],"sequential":[90],"relations":[91],"ramps":[94],"main":[96],"roads":[97],"freeway,":[100],"long":[102],"short-term":[103],"memory":[104],"network":[105],"applied.":[107],"Furthermore,":[108],"model":[110,118],"predictive":[111],"controller":[112],"trained":[115],"proposed":[120,138,165],"real-time":[123,174],"control":[124,175],"ramp":[127,178],"freeway.":[131],"validate":[133],"performance":[135],"approach,":[139],"experiments":[140],"simulation":[144,148],"software":[149],"Simulation":[150],"Urban":[152],"MObility":[153],"(SUMO)":[154],"environment":[155],"are":[156],"conducted.":[157],"results":[159],"demonstrate":[160],"effectiveness":[162],"both":[168],"prediction":[171],"metering.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}