{"id":"https://openalex.org/W3204848416","doi":"https://doi.org/10.23919/acc53348.2022.9867314","title":"A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways","display_name":"A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways","publication_year":2022,"publication_date":"2022-06-08","ids":{"openalex":"https://openalex.org/W3204848416","doi":"https://doi.org/10.23919/acc53348.2022.9867314","mag":"3204848416"},"language":"en","primary_location":{"id":"doi:10.23919/acc53348.2022.9867314","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867314","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 American Control Conference (ACC)","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/A5014468803","display_name":"Sai Krishna Sumanth Nakka","orcid":null},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sai Krishna Sumanth Nakka","raw_affiliation_strings":["University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716"],"affiliations":[{"raw_affiliation_string":"University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068009319","display_name":"Behdad Chalaki","orcid":"https://orcid.org/0000-0002-3055-1693"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Behdad Chalaki","raw_affiliation_strings":["University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716"],"affiliations":[{"raw_affiliation_string":"University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716","institution_ids":["https://openalex.org/I86501945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076592878","display_name":"Andreas A. Malikopoulos","orcid":"https://orcid.org/0000-0003-4817-0976"},"institutions":[{"id":"https://openalex.org/I86501945","display_name":"University of Delaware","ror":"https://ror.org/01sbq1a82","country_code":"US","type":"education","lineage":["https://openalex.org/I86501945"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas A. Malikopoulos","raw_affiliation_strings":["University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716"],"affiliations":[{"raw_affiliation_string":"University of Delaware,Department of Mechanical Engineering,Newark,USA,DE 19716","institution_ids":["https://openalex.org/I86501945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5014468803"],"corresponding_institution_ids":["https://openalex.org/I86501945"],"apc_list":null,"apc_paid":null,"fwci":7.4291,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.98633852,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3297","last_page":"3302"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9998000264167786,"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":0.9998000264167786,"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/T11942","display_name":"Transportation and Mobility Innovations","score":0.996399998664856,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9923999905586243,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8648505210876465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6720557808876038},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5402753949165344},{"id":"https://openalex.org/keywords/greenhouse-gas","display_name":"Greenhouse gas","score":0.49114033579826355},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4527859091758728},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.43918097019195557},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.43087100982666016},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.4036322832107544},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3399547338485718},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3246329724788666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2902159094810486},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.2756654620170593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20314502716064453},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18118241429328918}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8648505210876465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6720557808876038},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5402753949165344},{"id":"https://openalex.org/C47737302","wikidata":"https://www.wikidata.org/wiki/Q167336","display_name":"Greenhouse gas","level":2,"score":0.49114033579826355},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4527859091758728},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.43918097019195557},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.43087100982666016},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4036322832107544},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3399547338485718},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3246329724788666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2902159094810486},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.2756654620170593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20314502716064453},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18118241429328918},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc53348.2022.9867314","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc53348.2022.9867314","pdf_url":null,"source":{"id":"https://openalex.org/S4363607732","display_name":"2022 American Control Conference (ACC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W78707537","https://openalex.org/W598084924","https://openalex.org/W1547334443","https://openalex.org/W1757796397","https://openalex.org/W1766637835","https://openalex.org/W2003215771","https://openalex.org/W2005318074","https://openalex.org/W2038617280","https://openalex.org/W2062107013","https://openalex.org/W2094652234","https://openalex.org/W2108511252","https://openalex.org/W2173248099","https://openalex.org/W2187751550","https://openalex.org/W2212765426","https://openalex.org/W2508448572","https://openalex.org/W2509583637","https://openalex.org/W2515191420","https://openalex.org/W2734733003","https://openalex.org/W2752236613","https://openalex.org/W2794786585","https://openalex.org/W2797923482","https://openalex.org/W2897650612","https://openalex.org/W2907176255","https://openalex.org/W2947383384","https://openalex.org/W2963407617","https://openalex.org/W2963864421","https://openalex.org/W2983507942","https://openalex.org/W2990945991","https://openalex.org/W3001167148","https://openalex.org/W3003628925","https://openalex.org/W3007251354","https://openalex.org/W3011120880","https://openalex.org/W3014476692","https://openalex.org/W3042379327","https://openalex.org/W3047667548","https://openalex.org/W3054983093","https://openalex.org/W3093448500","https://openalex.org/W3098698879","https://openalex.org/W3101063937","https://openalex.org/W3101875691","https://openalex.org/W3102270594","https://openalex.org/W3102272080","https://openalex.org/W3105820921","https://openalex.org/W3119806386","https://openalex.org/W3149738779","https://openalex.org/W4298857966","https://openalex.org/W4299802797","https://openalex.org/W6637930290","https://openalex.org/W6684921986","https://openalex.org/W6738796088","https://openalex.org/W6775686901","https://openalex.org/W6782010504","https://openalex.org/W6784122241"],"related_works":["https://openalex.org/W2474431918","https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2078072966","https://openalex.org/W4383503214","https://openalex.org/W4390987329","https://openalex.org/W2361581724"],"abstract_inverted_index":{"The":[0],"steady":[1],"increase":[2],"in":[3],"the":[4,10,33,75,88],"number":[5],"of":[6,74,90],"vehicles":[7,30],"operating":[8],"on":[9],"highways":[11],"continues":[12],"to":[13,35,78],"exacerbate":[14],"congestion,":[15],"accidents,":[16],"energy":[17],"consumption,":[18],"and":[19,28,40,45,56,95],"greenhouse":[20],"gas":[21],"emissions.":[22],"Emerging":[23],"mobility":[24],"systems,":[25],"e.g.,":[26],"connected":[27],"automated":[29],"(CAVs),":[31],"have":[32],"potential":[34],"directly":[36],"address":[37],"these":[38],"issues":[39],"improve":[41],"transportation":[42],"network":[43],"efficiency":[44],"safety.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50],"consider":[51],"a":[52,58,71,98],"highway":[53],"merging":[54],"scenario":[55],"propose":[57],"framework":[59],"for":[60],"coordinating":[61],"CAVs":[62,91],"such":[63],"that":[64,97],"stop-and-go":[65,106],"driving":[66],"is":[67,102],"eliminated.":[68],"We":[69,86],"use":[70],"decentralized":[72],"form":[73],"actor-critic":[76],"approach":[77],"deep":[79,82],"reinforcement":[80],"learning\u2014multi-agent":[81],"deterministic":[83],"policy":[84],"gradient.":[85],"demonstrate":[87],"coordination":[89],"through":[92],"numerical":[93],"simulations":[94],"show":[96],"smooth":[99],"traffic":[100],"flow":[101],"achieved":[103],"by":[104],"eliminating":[105],"driving.":[107]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}