{"id":"https://openalex.org/W3092201697","doi":"https://doi.org/10.1109/case48305.2020.9217011","title":"Simulation Optimization for Arterial Coordinated Control: A Parallel Transportation System Method","display_name":"Simulation Optimization for Arterial Coordinated Control: A Parallel Transportation System Method","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3092201697","doi":"https://doi.org/10.1109/case48305.2020.9217011","mag":"3092201697"},"language":"en","primary_location":{"id":"doi:10.1109/case48305.2020.9217011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case48305.2020.9217011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-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/A5035542750","display_name":"Huang-qing Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huangqing Guo","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100352686","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-1401-0168"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210099079","display_name":"Institute of Intelligent Machines","ror":"https://ror.org/00w0qep84","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I2802624667","https://openalex.org/I4210099079"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["Department of Automation, University of Science and Technology of China, Hefei, China","Hefei Institute of Intelligent machinery, Chinese Academy of Sciences, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":"Hefei Institute of Intelligent machinery, Chinese Academy of Sciences, Hefei, China","institution_ids":["https://openalex.org/I4210099079","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5035542750"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1261175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"274","last_page":"279"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9991999864578247,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.6834588646888733},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5391182899475098},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4685315489768982},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.43729308247566223},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.42794620990753174},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.39062565565109253},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3794870972633362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2842971086502075},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1702389121055603}],"concepts":[{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.6834588646888733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5391182899475098},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4685315489768982},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.43729308247566223},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.42794620990753174},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.39062565565109253},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3794870972633362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2842971086502075},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1702389121055603}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case48305.2020.9217011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case48305.2020.9217011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7099999785423279,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W107853361","https://openalex.org/W1533464159","https://openalex.org/W1625956715","https://openalex.org/W1757796397","https://openalex.org/W2119567691","https://openalex.org/W2135635648","https://openalex.org/W2361439446","https://openalex.org/W2498017881","https://openalex.org/W2738419683","https://openalex.org/W2754582354","https://openalex.org/W2801572599","https://openalex.org/W2894849109","https://openalex.org/W2900863070","https://openalex.org/W2903253065","https://openalex.org/W2932967101","https://openalex.org/W2952724561","https://openalex.org/W2962899903","https://openalex.org/W3016648415","https://openalex.org/W4298023569","https://openalex.org/W4298857966","https://openalex.org/W6604355337","https://openalex.org/W6637967152","https://openalex.org/W7004865476","https://openalex.org/W7074104253"],"related_works":["https://openalex.org/W2391251536","https://openalex.org/W2362198218","https://openalex.org/W1982750869","https://openalex.org/W2019521278","https://openalex.org/W1984922432","https://openalex.org/W2113077220","https://openalex.org/W1982014942","https://openalex.org/W2053400739","https://openalex.org/W2375665878","https://openalex.org/W2123876169"],"abstract_inverted_index":{"The":[0,85,153],"urban":[1],"arterial":[2,32,51,70,78,93,136,184],"road":[3,22,79,94],"is":[4,61,104],"the":[5,8,17,21,29,57,77,99,128,131,142,159,182],"aorta":[6],"of":[7,20,31,88,120,130,145,161,179],"city":[9],"and":[10,148,164,175],"plays":[11],"an":[12,42,92],"important":[13],"role":[14],"in":[15,91,140,158],"increasing":[16],"traffic":[18,110,122],"capacity":[19],"network.":[23,102],"Due":[24],"to":[25,45,63,106],"high":[26],"practical":[27],"risk,":[28],"studies":[30],"coordinated":[33,52,71,137,185],"control":[34,48,72,119,138,186],"are":[35,80,95,150],"limited.":[36],"Parallel":[37],"Transportation":[38],"System":[39],"(PTS)":[40],"offers":[41],"effective":[43],"approach":[44],"investigate":[46,126],"optimal":[47,118],"method":[49],"for":[50,109],"control.":[53,112],"In":[54],"this":[55,114],"work,":[56],"deep":[58,100,132],"Q":[59,133],"network":[60,134],"introduced":[62],"PTS":[64],"platform.":[65],"We":[66,124],"proposed":[67],"a":[68,83],"dynamic":[69],"algorithm.":[73],"All":[74],"intersections":[75,90],"on":[76,135],"handled":[81],"as":[82],"whole.":[84],"status":[86],"characteristics":[87],"various":[89],"extracted":[96],"by":[97],"using":[98],"neural":[101],"Q-learning":[103],"used":[105],"accomplish":[107],"decision-making":[108],"signal":[111],"Thus,":[113],"algorithm":[115,168],"can":[116],"realize":[117],"time-variant":[121],"flow.":[123],"further":[125],"experimentally":[127],"effect":[129],"performances,":[139],"which":[141],"different":[143],"number":[144,178],"convolution":[146],"layers":[147],"optimizer":[149],"adopted":[151],"respectively.":[152],"simulation":[154],"results":[155],"show":[156],"that":[157],"condition":[160],"near":[162],"saturation":[163],"initial":[165],"queue,":[166],"our":[167],"has":[169],"much":[170],"lower":[171],"average":[172,177],"vehicle":[173],"delay":[174],"less":[176],"stops":[180],"than":[181],"typical":[183],"method.":[187]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}