{"id":"https://openalex.org/W4403182429","doi":"https://doi.org/10.1109/tits.2024.3467269","title":"The Intelligent Traffic Flow Control System Based on 6G and Optimized Genetic Algorithm","display_name":"The Intelligent Traffic Flow Control System Based on 6G and Optimized Genetic Algorithm","publication_year":2024,"publication_date":"2024-10-07","ids":{"openalex":"https://openalex.org/W4403182429","doi":"https://doi.org/10.1109/tits.2024.3467269"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3467269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3467269","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/A5066094987","display_name":"Caichang Ding","orcid":"https://orcid.org/0000-0002-2214-0050"},"institutions":[{"id":"https://openalex.org/I4210154338","display_name":"Hubei Engineering University","ror":"https://ror.org/05amnwk22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154338"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caichang Ding","raw_affiliation_strings":["School of Computer and Information Science, Hubei Engineering University, Xiaogan, China"],"raw_orcid":"https://orcid.org/0000-0002-2214-0050","affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Hubei Engineering University, Xiaogan, China","institution_ids":["https://openalex.org/I4210154338"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Zhu","orcid":"https://orcid.org/0009-0004-4366-5034"},"institutions":[{"id":"https://openalex.org/I10011244","display_name":"Huanggang Normal University","ror":"https://ror.org/007gf6e19","country_code":"CN","type":"education","lineage":["https://openalex.org/I10011244"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhu","raw_affiliation_strings":["Basic Course Department, Huanggang Normal University, Huanggang, China"],"raw_orcid":"https://orcid.org/0009-0004-4366-5034","affiliations":[{"raw_affiliation_string":"Basic Course Department, Huanggang Normal University, Huanggang, China","institution_ids":["https://openalex.org/I10011244"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102545351","display_name":"Ling Shen","orcid":"https://orcid.org/0000-0002-6376-8485"},"institutions":[{"id":"https://openalex.org/I4210128608","display_name":"Hubei Polytechnic Institute","ror":"https://ror.org/0353dhs61","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210128608"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Shen","raw_affiliation_strings":["School of Intelligent Engineering, Hubei Industry Polytechnic, Shiyan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Engineering, Hubei Industry Polytechnic, Shiyan, China","institution_ids":["https://openalex.org/I4210128608"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004466992","display_name":"Zhimin Li","orcid":"https://orcid.org/0000-0001-5407-1662"},"institutions":[{"id":"https://openalex.org/I4210154338","display_name":"Hubei Engineering University","ror":"https://ror.org/05amnwk22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154338"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimin Li","raw_affiliation_strings":["Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China","institution_ids":["https://openalex.org/I4210154338"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000368871","display_name":"Youfeng Li","orcid":"https://orcid.org/0009-0000-1741-4785"},"institutions":[{"id":"https://openalex.org/I4210154338","display_name":"Hubei Engineering University","ror":"https://ror.org/05amnwk22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154338"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youfeng Li","raw_affiliation_strings":["Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China","institution_ids":["https://openalex.org/I4210154338"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112985147","display_name":"Qiyang Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154338","display_name":"Hubei Engineering University","ror":"https://ror.org/05amnwk22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154338"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiyang Liang","raw_affiliation_strings":["Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for AI Industrial Technology Research, Hubei Engineering University, Xiaogan, China","institution_ids":["https://openalex.org/I4210154338"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.0681,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.98929872,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"26","issue":"10","first_page":"17403","last_page":"17416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13535","display_name":"Wireless Sensor Networks and IoT","score":0.7516000270843506,"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/T13535","display_name":"Wireless Sensor Networks and IoT","score":0.7516000270843506,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.64313805103302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5935595631599426},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.48773202300071716},{"id":"https://openalex.org/keywords/power-flow","display_name":"Power flow","score":0.4746951460838318},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.45182982087135315},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43526917695999146},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.27040213346481323},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1903703808784485},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.16461282968521118},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.1469244658946991},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.13518473505973816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11912843585014343},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07519859075546265}],"concepts":[{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.64313805103302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5935595631599426},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.48773202300071716},{"id":"https://openalex.org/C2986056383","wikidata":"https://www.wikidata.org/wiki/Q556030","display_name":"Power flow","level":4,"score":0.4746951460838318},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.45182982087135315},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43526917695999146},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27040213346481323},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1903703808784485},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.16461282968521118},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.1469244658946991},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.13518473505973816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11912843585014343},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07519859075546265},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3467269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3467269","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":[],"awards":[{"id":"https://openalex.org/G4564370521","display_name":null,"funder_award_id":"XGKJ2023010060","funder_id":"https://openalex.org/F4320334342","funder_display_name":"Natural Science Foundation of Xiaogan City"},{"id":"https://openalex.org/G6926929500","display_name":null,"funder_award_id":"2024AFC066","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"}],"funders":[{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320334342","display_name":"Natural Science Foundation of Xiaogan City","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1990771923","https://openalex.org/W2085352492","https://openalex.org/W2413688291","https://openalex.org/W2792111260","https://openalex.org/W2802574842","https://openalex.org/W2804329282","https://openalex.org/W2809133492","https://openalex.org/W2914743011","https://openalex.org/W2945192711","https://openalex.org/W3070374663","https://openalex.org/W3096604274","https://openalex.org/W3106977783","https://openalex.org/W3110411590","https://openalex.org/W3139957274","https://openalex.org/W3152335886","https://openalex.org/W3155305895","https://openalex.org/W3174176721","https://openalex.org/W3193804826","https://openalex.org/W3198283894","https://openalex.org/W3201960826","https://openalex.org/W3210716582","https://openalex.org/W4206341558","https://openalex.org/W4210554801","https://openalex.org/W4210562960","https://openalex.org/W4220899555","https://openalex.org/W4225157025","https://openalex.org/W4282013727","https://openalex.org/W4288078078","https://openalex.org/W4290065450","https://openalex.org/W4308741682","https://openalex.org/W4310177439","https://openalex.org/W4311168005","https://openalex.org/W4313855663","https://openalex.org/W4317934073","https://openalex.org/W4383535232","https://openalex.org/W4386415976","https://openalex.org/W4388232550","https://openalex.org/W4392375077","https://openalex.org/W4392457584","https://openalex.org/W4393079684"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2989452537","https://openalex.org/W2052122378","https://openalex.org/W2544423928","https://openalex.org/W2062023542"],"abstract_inverted_index":{"With":[0],"the":[1,5,97,105,109,116,120,160,180,192,214,224,237,242],"acceleration":[2],"of":[3,7,38,66,90,119,163,229,245],"urbanization,":[4],"problem":[6],"urban":[8,50],"traffic":[9,22,39,51,60,84,106,111,121,136,140,164,182,189,217,230],"congestion":[10],"has":[11,197,205],"become":[12],"increasingly":[13],"serious.":[14],"This":[15,55],"study":[16,56],"aims":[17],"to":[18,32,82,103,130],"develop":[19],"an":[20,58],"intelligent":[21,59,216],"flow":[23,61,165,218],"control":[24,62,177,219],"system":[25,63,74,220],"based":[26],"on":[27],"sixth-generation":[28],"(6G)":[29],"communication":[30,94],"technology":[31,78],"achieve":[33],"real-time":[34,88],"prediction":[35,166],"and":[36,44,53,70,79,86,114,132,138,150,175,202,226,240],"management":[37,141,190],"flow,":[40,107,137],"optimize":[41,104,232],"signal":[42,176,233],"control,":[43,234],"reduce":[45,236],"accident":[46,195,238],"rates,":[47],"thereby":[48],"improving":[49],"efficiency":[52,118],"safety.":[54],"constructs":[57],"framework":[64],"consisting":[65],"network,":[67],"platform,":[68],"perception,":[69],"application":[71],"layers.":[72],"The":[73,123,143,156],"utilizes":[75],"vehicle":[76],"networking":[77],"various":[80],"sensors":[81],"collect":[83],"data":[85,91],"ensures":[87],"transmission":[89],"through":[92,148],"6G":[93],"technology.":[95],"Meantime,":[96],"optimized":[98],"genetic":[99],"algorithm":[100],"is":[101,146,170],"used":[102],"solve":[108],"complex":[110],"optimization":[112,178],"problems,":[113],"improve":[115,241],"overall":[117,243],"system.":[122],"platform":[124],"layer":[125],"employs":[126],"machine":[127],"learning":[128],"algorithms":[129],"analyze":[131],"process":[133],"data,":[134],"predict":[135],"formulate":[139],"strategies.":[142],"system\u2019s":[144],"effectiveness":[145],"verified":[147],"experiments":[149],"comparative":[151],"analysis":[152],"with":[153],"actual":[154],"data.":[155],"results":[157],"show":[158],"that":[159,213],"error":[161],"rate":[162,196],"during":[167],"peak":[168],"hours":[169],"as":[171,173],"low":[172],"0.81%,":[174],"reduces":[179],"average":[181,193],"delay":[183],"by":[184,199,207],"15%.":[185],"By":[186],"implementing":[187],"improved":[188],"measures,":[191],"annual":[194],"decreased":[198],"over":[200],"40%,":[201],"user":[203],"satisfaction":[204,244],"increased":[206],"30%.":[208],"It":[209],"can":[210,221],"be":[211],"found":[212],"6G-based":[215],"effectively":[222],"enhance":[223],"accuracy":[225],"response":[227],"speed":[228],"prediction,":[231],"remarkably":[235],"rate,":[239],"users.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":39},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}