{"id":"https://openalex.org/W4366381375","doi":"https://doi.org/10.1145/3584376.3584431","title":"Adaptive traffic signal control based on Dueling Deep Q-Learning Network","display_name":"Adaptive traffic signal control based on Dueling Deep Q-Learning Network","publication_year":2022,"publication_date":"2022-12-16","ids":{"openalex":"https://openalex.org/W4366381375","doi":"https://doi.org/10.1145/3584376.3584431"},"language":"en","primary_location":{"id":"doi:10.1145/3584376.3584431","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584376.3584431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","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/A5051767411","display_name":"Zhuohang Xu","orcid":"https://orcid.org/0000-0002-8765-5426"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhuohang Xu","raw_affiliation_strings":["School of Electronic and Control Engineering, Chang45an University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Control Engineering, Chang45an University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338728","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0003-2963-9476"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Wang","raw_affiliation_strings":["School of Electronic and Control Engineering, Chang45an University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Control Engineering, Chang45an University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021050004","display_name":"Libin Zhang","orcid":"https://orcid.org/0000-0001-9785-2127"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Libin Zhang","raw_affiliation_strings":["School of Electronic and Control Engineering, Chang45an University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Control Engineering, Chang45an University, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088515588","display_name":"Fan Qi","orcid":"https://orcid.org/0000-0002-7280-8346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Qi","raw_affiliation_strings":["School of Electronic and Control Engineering, Chang45an University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Control Engineering, Chang45an University, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032665058","display_name":"Guiping Wang","orcid":"https://orcid.org/0000-0003-0042-8501"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guiping Wang","raw_affiliation_strings":["School of Electronic and Control Engineering, Chang45an University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Control Engineering, Chang45an University, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5051767411"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1205,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4608777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"297","last_page":"301"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9972000122070312,"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":0.9639999866485596,"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/intersection","display_name":"Intersection (aeronautics)","score":0.7545043230056763},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7370707392692566},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.7035283446311951},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6076354384422302},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5598341226577759},{"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":0.5420364737510681},{"id":"https://openalex.org/keywords/traffic-optimization","display_name":"Traffic optimization","score":0.48379725217819214},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.474281370639801},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.46120375394821167},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4309297204017639},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4151794910430908},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.3547069728374481},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.35265058279037476},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32525888085365295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31561464071273804},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.31453579664230347},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.16600912809371948},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12779855728149414}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7545043230056763},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7370707392692566},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.7035283446311951},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6076354384422302},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5598341226577759},{"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":0.5420364737510681},{"id":"https://openalex.org/C86266404","wikidata":"https://www.wikidata.org/wiki/Q7832512","display_name":"Traffic optimization","level":4,"score":0.48379725217819214},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.474281370639801},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.46120375394821167},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4309297204017639},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4151794910430908},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.3547069728374481},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.35265058279037476},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32525888085365295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31561464071273804},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.31453579664230347},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.16600912809371948},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12779855728149414},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584376.3584431","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584376.3584431","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2115524942","https://openalex.org/W2130241203","https://openalex.org/W2416799949","https://openalex.org/W2766381093","https://openalex.org/W2914585077","https://openalex.org/W3007754307","https://openalex.org/W3049728571","https://openalex.org/W3216516204","https://openalex.org/W4200308385","https://openalex.org/W4226019605","https://openalex.org/W4281396886"],"related_works":["https://openalex.org/W2314667417","https://openalex.org/W4200341511","https://openalex.org/W2383825462","https://openalex.org/W4226139383","https://openalex.org/W2156725836","https://openalex.org/W3003957176","https://openalex.org/W2108968924","https://openalex.org/W3139957274","https://openalex.org/W3010557371","https://openalex.org/W2274909486"],"abstract_inverted_index":{"The":[0],"intersection":[1,57],"is":[2,23,27,48,86,146],"the":[3,18,34,38,52,56,60,64,71,78,90,100,119,125,140,170,174,189],"place":[4],"where":[5],"traffic":[6,10,19,35,45,53,79,92,101,120,131,171,190],"flow":[7,102,172],"converges":[8],"and":[9,17,32,148,157,179],"accidents":[11],"are":[12],"most":[13],"likely":[14],"to":[15,29,50,88,169],"occur,":[16],"conditions":[20,103],"at":[21],"intersections":[22,105,123],"also":[24],"complex,":[25],"which":[26,185],"easy":[28],"cause":[30],"congestion":[31],"reduce":[33],"efficiency.":[36,191],"With":[37],"development":[39],"of":[40,55,63,74,104,122,127,130,143,153,173],"intelligent":[41],"transportation":[42],"system,":[43],"adaptive":[44,91],"signal":[46,65,93,108],"control":[47,94,109],"proposed":[49],"improve":[51,118,188],"efficiency":[54,121],"by":[58],"adjusting":[59],"phase":[61,155],"sequence":[62],"in":[66,77,95],"real":[67],"time.":[68],"Meanwhile,":[69,160],"with":[70],"extensive":[72],"application":[73],"reinforcement":[75],"learning":[76],"field,":[80],"dueling":[81,114,144,165],"DQN":[82,115,145,158,166],"(Deep":[83],"Q-Learning":[84],"Network)":[85],"introduced":[87],"realize":[89],"this":[96],"paper.":[97],"By":[98],"comparing":[99],"under":[106,124],"different":[107],"methods,":[110],"we":[111,136],"find":[112],"that":[113,139,152,164],"can":[116,137,167,186],"effectively":[117,187],"condition":[126],"random":[128],"change":[129],"flow.":[132],"Through":[133],"experiment":[134],"results,":[135],"conclude":[138],"expected":[141],"reward":[142],"41.1%":[147],"4.8%":[149],"higher":[150,181],"than":[151,183],"fixed":[154],"method":[156],"method.":[159],"simulation":[161],"result":[162],"shows":[163],"react":[168],"road":[175],"network":[176],"more":[177],"timely,":[178],"has":[180],"stability":[182],"DQN,":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}