{"id":"https://openalex.org/W4380628798","doi":"https://doi.org/10.1145/3585542.3585552","title":"A DQN Algorithm for Traffic Signal Control Based on Meta-learning Training","display_name":"A DQN Algorithm for Traffic Signal Control Based on Meta-learning Training","publication_year":2023,"publication_date":"2023-02-17","ids":{"openalex":"https://openalex.org/W4380628798","doi":"https://doi.org/10.1145/3585542.3585552"},"language":"en","primary_location":{"id":"doi:10.1145/3585542.3585552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3585542.3585552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Digital Signal Processing","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/A5024067904","display_name":"Ke Li","orcid":"https://orcid.org/0009-0009-3023-5883"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Li","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, China"],"raw_orcid":"https://orcid.org/0009-0009-3023-5883","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076976848","display_name":"Zhandong Liu","orcid":"https://orcid.org/0000-0002-6073-4618"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhandong Liu","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, China"],"raw_orcid":"https://orcid.org/0000-0002-6073-4618","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081413477","display_name":"Nan Ding","orcid":"https://orcid.org/0000-0002-9958-8224"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Ding","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, China"],"raw_orcid":"https://orcid.org/0000-0002-9958-8224","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049174911","display_name":"Ronghua Jiang","orcid":"https://orcid.org/0009-0000-1362-120X"},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghua Jiang","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang Normal University, China"],"raw_orcid":"https://orcid.org/0009-0000-1362-120X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang Normal University, China","institution_ids":["https://openalex.org/I1334729051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024067904"],"corresponding_institution_ids":["https://openalex.org/I1334729051"],"apc_list":null,"apc_paid":null,"fwci":0.4524,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6035428,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9835000038146973,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9505000114440918,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/computer-science","display_name":"Computer science","score":0.7520442008972168},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6910707354545593},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.6470497846603394},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5786776542663574},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4567192792892456},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4183367192745209},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4118344187736511},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40694528818130493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3100479245185852}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7520442008972168},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6910707354545593},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.6470497846603394},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5786776542663574},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4567192792892456},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4183367192745209},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4118344187736511},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40694528818130493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3100479245185852},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"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/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3585542.3585552","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3585542.3585552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 7th International Conference on Digital Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5199999809265137,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2519882289","https://openalex.org/W2809148419","https://openalex.org/W2910646677","https://openalex.org/W2963351448","https://openalex.org/W3012066402","https://openalex.org/W4286696412","https://openalex.org/W6600281463","https://openalex.org/W6604103938"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4366179611","https://openalex.org/W2996078371"],"abstract_inverted_index":{"With":[0],"the":[1,13,52,58,65,79,82,86,95,101,107,129],"rapid":[2],"development":[3],"of":[4,31,55,81,85,131],"our":[5,132],"society":[6],"and":[7,89],"economy,":[8],"traffic":[9,41,53],"congestion":[10],"caused":[11],"by":[12,124],"increase":[14],"in":[15,40,94],"vehicles":[16,56],"is":[17],"an":[18,28,91],"important":[19],"challenge":[20],"we":[21,69,105],"are":[22],"facing":[23],"today.":[24],"Traffic":[25],"control,":[26],"as":[27],"integral":[29],"part":[30],"intelligent":[32],"transport":[33],"systems":[34],"(ITS),":[35],"plays":[36],"a":[37,71,112],"huge":[38],"role":[39],"control":[42,47],"areas.":[43],"A":[44],"good":[45],"signal":[46,119],"method":[48],"can":[49],"greatly":[50],"improve":[51],"capacity":[54],"on":[57,64,75],"road.":[59],"In":[60],"this":[61],"paper,":[62],"based":[63,74],"traditional":[66],"DQN":[67,87,115],"algorithm,":[68],"propose":[70],"gradient":[72],"algorithm":[73,88,116],"meta-learning":[76],"to":[77,99,110],"promote":[78],"adjustment":[80],"training":[83],"parameters":[84],"add":[90],"attention":[92],"mechanism":[93],"depth":[96],"neural":[97],"network":[98],"aggregate":[100],"effective":[102,114],"features.":[103],"Finally,":[104],"adjust":[106],"loss":[108],"function":[109],"obtain":[111],"more":[113],"for":[117],"road":[118],"control.":[120],"Simulation":[121],"experiments":[122],"conducted":[123],"SUMO":[125],"simulation":[126],"software":[127],"prove":[128],"effectiveness":[130],"method.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
