{"id":"https://openalex.org/W3210769222","doi":"https://doi.org/10.1109/itsc48978.2021.9564664","title":"Adaptive Coordinated Traffic Control for Arterial Intersections based on Reinforcement Learning","display_name":"Adaptive Coordinated Traffic Control for Arterial Intersections based on Reinforcement Learning","publication_year":2021,"publication_date":"2021-09-19","ids":{"openalex":"https://openalex.org/W3210769222","doi":"https://doi.org/10.1109/itsc48978.2021.9564664","mag":"3210769222"},"language":"en","primary_location":{"id":"doi:10.1109/itsc48978.2021.9564664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","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/A5070278647","display_name":"Zian Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zian Ma","raw_affiliation_strings":["SenseTime Group Limited and Shanghai AI lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited and Shanghai AI lab, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072820659","display_name":"Chengcheng Xu","orcid":"https://orcid.org/0000-0003-3028-0034"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengcheng Xu","raw_affiliation_strings":["SenseTime Group Limited and Shanghai AI lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited and Shanghai AI lab, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077820835","display_name":"Yuheng Kan","orcid":"https://orcid.org/0000-0003-0756-8478"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuheng Kan","raw_affiliation_strings":["SenseTime Group Limited and Shanghai AI lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited and Shanghai AI lab, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025157753","display_name":"Maonan Wang","orcid":"https://orcid.org/0000-0001-5407-0416"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maonan Wang","raw_affiliation_strings":["SenseTime Group Limited and Shanghai AI lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited and Shanghai AI lab, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100741922","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0001-8582-1876"},"institutions":[{"id":"https://openalex.org/I4391012619","display_name":"Shanghai Artificial Intelligence Laboratory","ror":"https://ror.org/03wkvpx79","country_code":null,"type":"facility","lineage":["https://openalex.org/I4391012619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["SenseTime Group Limited and Shanghai AI lab, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited and Shanghai AI lab, Shanghai, China","institution_ids":["https://openalex.org/I4391012619"]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070278647"],"corresponding_institution_ids":["https://openalex.org/I4391012619"],"apc_list":null,"apc_paid":null,"fwci":0.9613,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75452646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2562","last_page":"2567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9980000257492065,"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":0.9980000257492065,"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/T14011","display_name":"Elevator Systems and Control","score":0.9961000084877014,"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":0.9876999855041504,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8212460875511169},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6320599317550659},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5188361406326294},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.4806336462497711},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3657146096229553}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8212460875511169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6320599317550659},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5188361406326294},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.4806336462497711},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3657146096229553}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc48978.2021.9564664","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564664","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W920737085","https://openalex.org/W1506701843","https://openalex.org/W1549969567","https://openalex.org/W1869778509","https://openalex.org/W1974937264","https://openalex.org/W1985458300","https://openalex.org/W2021415726","https://openalex.org/W2061928772","https://openalex.org/W2082310090","https://openalex.org/W2082371193","https://openalex.org/W2139728973","https://openalex.org/W2149012699","https://openalex.org/W2155968351","https://openalex.org/W2201581102","https://openalex.org/W2287027336","https://openalex.org/W2505920244","https://openalex.org/W2746553466","https://openalex.org/W2766381093","https://openalex.org/W2794621419","https://openalex.org/W2801572599","https://openalex.org/W2904906709","https://openalex.org/W2915117209","https://openalex.org/W2945442007","https://openalex.org/W2963477884","https://openalex.org/W2966130848","https://openalex.org/W2984165296","https://openalex.org/W2989874518","https://openalex.org/W2991602722","https://openalex.org/W2991611854","https://openalex.org/W3032398409","https://openalex.org/W3044015199","https://openalex.org/W3047152140","https://openalex.org/W3090940203","https://openalex.org/W3093228258","https://openalex.org/W4238995758","https://openalex.org/W4292167352","https://openalex.org/W4293797479","https://openalex.org/W6630332285","https://openalex.org/W6639086533"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4306904969","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2138720691","https://openalex.org/W2376932109","https://openalex.org/W4362501864","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Coordinated":[0],"control":[1,20,59],"of":[2,12,28,68,82,95,110,153,178],"arterial":[3,61,70],"roads":[4],"is":[5,21],"widely":[6],"used":[7],"to":[8,23,54,79],"increase":[9],"the":[10,13,17,26,29,33,37,49,69,80,83,90,96,101,111,126,133,139,170,176,179],"efficiency":[11],"main":[14,34],"road.":[15],"However,":[16],"traditional":[18],"fixed-time":[19,148],"difficult":[22],"simultaneously":[24],"tackle":[25],"fluctuation":[27],"initial":[30],"queuing":[31],"on":[32],"road":[35],"and":[36,65,93,104,108,128,155,160,166],"flow":[38],"in":[39,120,142,169],"all":[40],"directions.":[41],"To":[42],"fill":[43],"this":[44,46,143],"gap,":[45],"research":[47,87],"employs":[48],"reinforcement":[50],"learning":[51],"(RL)":[52],"method":[53],"design":[55],"adaptive":[56],"coordinated":[57],"traffic":[58,84,116],"for":[60,125,132],"intersections.":[62],"Specifically,":[63],"offsets":[64],"green":[66],"splits":[67],"intersections":[71],"are":[72,118,124,131,162],"adaptively":[73],"controlled":[74],"by":[75,164],"RL":[76,112],"agent":[77],"according":[78],"perception":[81],"dynamics.":[85],"This":[86],"deeply":[88],"analyzes":[89],"boundaries,":[91],"features":[92],"objectives":[94],"problem":[97],"and,":[98],"accordingly,":[99],"determines":[100],"training":[102,127],"environment":[103],"state,":[105],"reward,":[106],"action,":[107],"timeline":[109],"agent.":[113],"200":[114],"random":[115],"scenes":[117],"built,":[119],"which":[121,174],"50":[122,129],"percent":[123,130],"test.":[134],"The":[135,157],"results":[136],"show":[137],"that":[138],"algorithm":[140],"proposed":[141,180],"study":[144],"can":[145],"significantly":[146],"outperform":[147],"signal":[149],"scheme":[150],"with":[151],"optimization":[152],"offset":[154],"green-split.":[156],"stop":[158],"number":[159],"delay":[161],"decreased":[163],"-11&#x0025;":[165],"-":[167],"4&#x0025;":[168],"large-scale":[171],"test":[172],"set,":[173],"verifies":[175],"effectiveness":[177],"model.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
