{"id":"https://openalex.org/W4414646817","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174648","title":"Joint Trajectory and Spectrum Optimization in Advanced Air Mobility via Multi-Agent Deep Reinforcement Learning","display_name":"Joint Trajectory and Spectrum Optimization in Advanced Air Mobility via Multi-Agent Deep Reinforcement Learning","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4414646817","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174648"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2025-spring65109.2025.11174648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174648","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","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/A5008990445","display_name":"Qingyang Li","orcid":"https://orcid.org/0000-0003-2602-9250"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qingyang Li","raw_affiliation_strings":["University of Louisville,Louisville,KY,USA"],"affiliations":[{"raw_affiliation_string":"University of Louisville,Louisville,KY,USA","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781436","display_name":"Hongxiang Li","orcid":"https://orcid.org/0000-0002-5444-2168"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongxiang Li","raw_affiliation_strings":["University of Louisville,Louisville,KY,USA"],"affiliations":[{"raw_affiliation_string":"University of Louisville,Louisville,KY,USA","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060568983","display_name":"Eric J. Knoblock","orcid":"https://orcid.org/0000-0003-4898-2704"},"institutions":[{"id":"https://openalex.org/I2799786008","display_name":"Glenn Research Center","ror":"https://ror.org/059fqnc42","country_code":"US","type":"facility","lineage":["https://openalex.org/I2799786008","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric J. Knoblock","raw_affiliation_strings":["NASA Glenn Research Center,Cleveland,OH,USA"],"affiliations":[{"raw_affiliation_string":"NASA Glenn Research Center,Cleveland,OH,USA","institution_ids":["https://openalex.org/I2799786008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008990445"],"corresponding_institution_ids":["https://openalex.org/I142740786"],"apc_list":null,"apc_paid":null,"fwci":5.2163,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.95729189,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11489","display_name":"Air Traffic Management and Optimization","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11489","display_name":"Air Traffic Management and Optimization","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10698","display_name":"Transportation Planning and Optimization","score":0.9855999946594238,"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"}},{"id":"https://openalex.org/T11599","display_name":"Aviation Industry Analysis and Trends","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2000","display_name":"General Economics, Econometrics and Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7462000250816345},{"id":"https://openalex.org/keywords/aviation","display_name":"Aviation","score":0.6069999933242798},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5928999781608582},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5464000105857849},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.49720001220703125},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4959999918937683},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.48910000920295715},{"id":"https://openalex.org/keywords/air-traffic-control","display_name":"Air traffic control","score":0.4047999978065491},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4020000100135803}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7462000250816345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380000114440918},{"id":"https://openalex.org/C74448152","wikidata":"https://www.wikidata.org/wiki/Q765633","display_name":"Aviation","level":2,"score":0.6069999933242798},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5928999781608582},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5464000105857849},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.49720001220703125},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.49459999799728394},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.48910000920295715},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40619999170303345},{"id":"https://openalex.org/C166961238","wikidata":"https://www.wikidata.org/wiki/Q221395","display_name":"Air traffic control","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4020000100135803},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C2776777543","wikidata":"https://www.wikidata.org/wiki/Q1361182","display_name":"Air traffic management","level":3,"score":0.3874000012874603},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.35830000042915344},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.34290000796318054},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3366999924182892},{"id":"https://openalex.org/C512918668","wikidata":"https://www.wikidata.org/wiki/Q206814","display_name":"Civil aviation","level":3,"score":0.3328000009059906},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.28060001134872437},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2776637919","wikidata":"https://www.wikidata.org/wiki/Q624380","display_name":"Descent (aeronautics)","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.2565999925136566}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2025-spring65109.2025.11174648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174648","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2145339207","https://openalex.org/W2914296650","https://openalex.org/W2979979796","https://openalex.org/W3000653182","https://openalex.org/W3047199803","https://openalex.org/W3092163236","https://openalex.org/W3105695615","https://openalex.org/W3167181515","https://openalex.org/W3170320971","https://openalex.org/W4280627398","https://openalex.org/W4324116494"],"related_works":[],"abstract_inverted_index":{"Urban":[0,12],"air":[1,50,58],"transportation":[2,59],"is":[3,25,40,99,144],"undergoing":[4],"a":[5,126,173],"revolutionary":[6],"transformation":[7],"through":[8],"the":[9,34,78,80,102,110,122,131,186],"integration":[10],"of":[11,84],"Air":[13,18],"Mobility":[14,19],"(UAM)":[15],"and":[16,113,157,189],"Advanced":[17],"(AAM)":[20],"systems.":[21],"One":[22],"big":[23],"challenge":[24],"that":[26,180],"new":[27],"aerial":[28],"vehicles":[29],"(AV)":[30],"will":[31],"quickly":[32],"saturate":[33],"already":[35],"crowded":[36],"aviation":[37],"spectrum,":[38],"which":[39],"an":[41,57,163],"essential":[42],"resource":[43,158],"to":[44,67,75,93,100,146],"ensure":[45,94],"reliable":[46],"communications":[47],"for":[48,116,153],"safe":[49],"operations.":[51],"In":[52],"this":[53],"paper,":[54],"we":[55,161],"consider":[56],"system":[60],"where":[61,130],"multiple":[62,165],"AV":[63,118,151],"s":[64,152],"are":[65,134],"operated":[66],"transport":[68],"passengers":[69],"or":[70],"cargo":[71],"from":[72],"different":[73,196],"sources":[74],"destinations.":[76],"During":[77],"flight,":[79],"minimum":[81],"communication":[82],"Quality":[83],"Service":[85],"(QoS)":[86],"must":[87],"be":[88],"achieved":[89],"at":[90],"all":[91,117],"times":[92],"flight":[95],"safety.":[96],"Our":[97],"objective":[98],"minimize":[101],"total":[103],"mission":[104],"completion":[105],"time":[106],"by":[107],"jointly":[108],"optimizing":[109],"trajectories,":[111],"velocities,":[112],"spectrum":[114],"allocation":[115],"s.":[119],"We":[120],"formulate":[121],"optimization":[123,132],"problem":[124],"as":[125,172],"multi-stage":[127],"Markov":[128],"game":[129],"variables":[133],"coupled":[135],"together.":[136],"A":[137,169],"multi-agent":[138],"deep":[139],"Reinforcement":[140],"learning":[141,149],"VD3QN":[142],"algorithm":[143,171],"proposed":[145],"enable":[147],"cooperative":[148],"among":[150],"both":[154,185],"trajectory":[155],"planning":[156],"optimization.":[159],"Additionally,":[160],"propose":[162],"orthogonal":[164],"access":[166],"with":[167],"Space-Time":[168],"*":[170],"non-learning-based":[174,187],"solution.":[175],"Extensive":[176],"simulation":[177],"results":[178],"show":[179],"our":[181],"learning-based":[182,191],"solution":[183,188],"outperforms":[184],"other":[190],"approaches":[192],"like":[193],"Qmix":[194],"under":[195],"parameters.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}