{"id":"https://openalex.org/W4360930864","doi":"https://doi.org/10.1109/mits.2023.3253134","title":"A Comprehensive Regional Traffic Coordination Control Strategy Integrated the Short-Term Traffic Flow Identification and Prediction","display_name":"A Comprehensive Regional Traffic Coordination Control Strategy Integrated the Short-Term Traffic Flow Identification and Prediction","publication_year":2023,"publication_date":"2023-03-24","ids":{"openalex":"https://openalex.org/W4360930864","doi":"https://doi.org/10.1109/mits.2023.3253134"},"language":"en","primary_location":{"id":"doi:10.1109/mits.2023.3253134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3253134","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"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 Intelligent Transportation Systems Magazine","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/A5008788676","display_name":"Xiaoping Ma","orcid":"https://orcid.org/0000-0002-4266-0854"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoping Ma","raw_affiliation_strings":["State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4266-0854","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067401714","display_name":"Sibo Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sibo Lu","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102487396","display_name":"Honglan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honglan Huang","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089020716","display_name":"Yanpiao Chen","orcid":"https://orcid.org/0009-0000-6092-2232"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanpiao Chen","raw_affiliation_strings":["State Key Laboratory of Network Switching and Control, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Network Switching and Control, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2041,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75782225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"15","issue":"4","first_page":"137","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T10370","display_name":"Traffic and Road Safety","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.7036916613578796},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.616473913192749},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6155095100402832},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.5898093581199646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5882390141487122},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.5267816781997681},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5113129615783691},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5090627074241638},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4546010196208954},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.44212013483047485},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.4299919009208679},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4282754361629486},{"id":"https://openalex.org/keywords/traffic-optimization","display_name":"Traffic optimization","score":0.42324477434158325},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.412826269865036},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.32312101125717163},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2944643795490265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21198847889900208},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.16344258189201355}],"concepts":[{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.7036916613578796},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.616473913192749},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6155095100402832},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.5898093581199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5882390141487122},{"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":0.5267816781997681},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5113129615783691},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5090627074241638},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4546010196208954},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.44212013483047485},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.4299919009208679},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4282754361629486},{"id":"https://openalex.org/C86266404","wikidata":"https://www.wikidata.org/wiki/Q7832512","display_name":"Traffic optimization","level":4,"score":0.42324477434158325},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.412826269865036},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.32312101125717163},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2944643795490265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21198847889900208},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.16344258189201355},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mits.2023.3253134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3253134","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"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 Intelligent Transportation Systems Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1518198452","display_name":null,"funder_award_id":"2022JBXT009","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G1682896328","display_name":null,"funder_award_id":"RCS2022ZZ002","funder_id":"https://openalex.org/F4320323067","funder_display_name":"State Key Laboratory of Rail Traffic Control and Safety"},{"id":"https://openalex.org/G2482190385","display_name":null,"funder_award_id":"2021YFB2501001","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"}],"funders":[{"id":"https://openalex.org/F4320323067","display_name":"State Key Laboratory of Rail Traffic Control and Safety","ror":"https://ror.org/01yj56c84"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1610291649","https://openalex.org/W2015948277","https://openalex.org/W2053546515","https://openalex.org/W2253429366","https://openalex.org/W2367939631","https://openalex.org/W2498017881","https://openalex.org/W2759352291","https://openalex.org/W2799109291","https://openalex.org/W2807129134","https://openalex.org/W2808448224","https://openalex.org/W2891280833","https://openalex.org/W2911369830","https://openalex.org/W2916664939","https://openalex.org/W2921767676","https://openalex.org/W2939251941","https://openalex.org/W2954616501","https://openalex.org/W3000580204","https://openalex.org/W3020398622","https://openalex.org/W3020515607","https://openalex.org/W3033337169","https://openalex.org/W3034294191","https://openalex.org/W3087451749","https://openalex.org/W3098339705","https://openalex.org/W3124050193","https://openalex.org/W3130729047","https://openalex.org/W3133129631","https://openalex.org/W3144678276","https://openalex.org/W3171265245","https://openalex.org/W3212930182","https://openalex.org/W4285238123"],"related_works":["https://openalex.org/W2587362999","https://openalex.org/W2009112536","https://openalex.org/W2410941711","https://openalex.org/W2361775397","https://openalex.org/W1550043390","https://openalex.org/W4256033520","https://openalex.org/W2064543875","https://openalex.org/W2161957991","https://openalex.org/W2288817554","https://openalex.org/W2621233240"],"abstract_inverted_index":{"Traffic":[0],"congestion":[1,133],"caused":[2],"by":[3],"the":[4,25,40,81,93,112,118,124,139,142,147,160,164,168,177],"rapid":[5],"growth":[6],"of":[7,35,45,123,141,167],"vehicles":[8],"and":[9,21,42,55,75,87,96,107,120,130,152,173],"unadaptable":[10],"signal":[11],"control":[12,57,158],"has":[13],"become":[14],"a":[15,32,49,97,153],"major":[16],"constraint":[17],"on":[18,31],"traffic":[19,36,46,65,77,85,105,132],"efficiency":[20],"travel":[22],"experience.":[23],"However,":[24],"existing":[26,148],"studies":[27,127],"have":[28],"primarily":[29],"focused":[30],"particular":[33],"aspect":[34],"behaviors,":[37],"without":[38],"considering":[39],"systemic":[41],"interconnected":[43],"nature":[44],"congestion.":[47],"Hence,":[48],"comprehensive":[50],"strategy":[51,170],"integrating":[52],"monitoring,":[53],"prediction,":[54],"coordinated":[56],"at":[58],"regional":[59],"intersections":[60,82],"is":[61,71,101,114,171],"proposed":[62,102,143,169],"to":[63,73,103,117,137,176],"improve":[64,104],"efficiency.":[66],"First,":[67],"an":[68],"intelligent":[69],"algorithm":[70],"designed":[72,136],"identify":[74],"predict":[76],"condition":[78],"information.":[79],"Then,":[80],"with":[83,146],"similar":[84],"behaviors":[86],"higher":[88],"relevancy":[89],"are":[90,135],"divided":[91],"into":[92],"same":[94],"subzone,":[95],"multiobjective":[98],"optimization":[99],"model":[100],"capacity":[106],"green":[108],"time":[109],"utilization.":[110],"Furthermore,":[111],"timing":[113,150],"modified":[115],"according":[116],"temporal":[119],"spatial":[121],"characteristics":[122],"oversaturation.":[125],"Simulation":[126],"in":[128],"long-term":[129],"short-term":[131],"scenarios":[134],"verify":[138],"performance":[140],"strategy.":[144],"Compared":[145],"multitime":[149],"method":[151],"newly":[154],"formed":[155],"reinforcement":[156],"learning":[157],"method,":[159],"results":[161],"show":[162],"that":[163],"average":[165],"delay":[166],"4.945%":[172],"6.737%":[174],"inferior":[175],"outstanding":[178],"strategies.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
