{"id":"https://openalex.org/W4315630313","doi":"https://doi.org/10.1109/globecom48099.2022.10001396","title":"Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policies","display_name":"Reinforcement Learning for Joint V2I Network Selection and Autonomous Driving Policies","publication_year":2022,"publication_date":"2022-12-04","ids":{"openalex":"https://openalex.org/W4315630313","doi":"https://doi.org/10.1109/globecom48099.2022.10001396"},"language":"en","primary_location":{"id":"doi:10.1109/globecom48099.2022.10001396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10001396","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","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":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","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/A5088546712","display_name":"Zijiang Yan","orcid":"https://orcid.org/0000-0002-7959-8329"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zijiang Yan","raw_affiliation_strings":["York University,Dept. of Electrical Engineering and Computer Science,Canada","Dept. of Electrical Engineering and Computer Science, York University, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"York University,Dept. of Electrical Engineering and Computer Science,Canada","institution_ids":["https://openalex.org/I192455969"]},{"raw_affiliation_string":"Dept. of Electrical Engineering and Computer Science, York University, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039708717","display_name":"Hina Tabassum","orcid":"https://orcid.org/0000-0002-7379-6949"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hina Tabassum","raw_affiliation_strings":["York University,Dept. of Electrical Engineering and Computer Science,Canada","Dept. of Electrical Engineering and Computer Science, York University, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"York University,Dept. of Electrical Engineering and Computer Science,Canada","institution_ids":["https://openalex.org/I192455969"]},{"raw_affiliation_string":"Dept. of Electrical Engineering and Computer Science, York University, Canada","institution_ids":["https://openalex.org/I192455969"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.06,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.98149055,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1241","last_page":"1246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9557999968528748,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.8923709392547607},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7476396560668945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7462356090545654},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5754293203353882},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.5387329459190369},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4829265773296356},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47992974519729614},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.47324830293655396},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47246551513671875},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.4525361657142639},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.44563084840774536},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4305892288684845},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.42136627435684204},{"id":"https://openalex.org/keywords/network-dynamics","display_name":"Network dynamics","score":0.41142675280570984},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3211871385574341},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19060957431793213},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.176262766122818},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17409124970436096},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.09193199872970581}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8923709392547607},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7476396560668945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7462356090545654},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5754293203353882},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.5387329459190369},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4829265773296356},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47992974519729614},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.47324830293655396},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47246551513671875},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4525361657142639},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.44563084840774536},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4305892288684845},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.42136627435684204},{"id":"https://openalex.org/C123757187","wikidata":"https://www.wikidata.org/wiki/Q9195957","display_name":"Network dynamics","level":2,"score":0.41142675280570984},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3211871385574341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19060957431793213},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.176262766122818},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17409124970436096},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.09193199872970581},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom48099.2022.10001396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10001396","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","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":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2487175822","https://openalex.org/W2775482448","https://openalex.org/W2962834855","https://openalex.org/W2963000651","https://openalex.org/W2997499903","https://openalex.org/W3004199239","https://openalex.org/W3035858775","https://openalex.org/W3045764976","https://openalex.org/W3045995653","https://openalex.org/W3118727533","https://openalex.org/W3139539396","https://openalex.org/W3177911636","https://openalex.org/W4205676769","https://openalex.org/W4224215291","https://openalex.org/W4285246415"],"related_works":["https://openalex.org/W2808418668","https://openalex.org/W2357975469","https://openalex.org/W2101748387","https://openalex.org/W3096874164","https://openalex.org/W4281812492","https://openalex.org/W3105579180","https://openalex.org/W2970347269","https://openalex.org/W3167472281","https://openalex.org/W4400868993","https://openalex.org/W2146763310"],"abstract_inverted_index":{"Vehicle-to-Infrastructure":[0],"(V2I)":[1],"communication":[2,52,184,205],"is":[3,30,92,177],"becoming":[4],"critical":[5,32],"for":[6,169],"the":[7,15,18,36,51,97,105,120,129,158,181,196,204],"enhanced":[8],"reliability":[9],"of":[10,187,198],"autonomous":[11,71,114],"vehicles":[12],"(AVs).":[13],"However,":[14],"uncertainties":[16],"in":[17,43,74],"road-traffic":[19],"and":[20,40,70,85,100,111,117,123,133,149,165,183,203],"AVs'":[21,37],"wireless":[22],"connections":[23],"can":[24],"severely":[25],"impair":[26],"timely":[27],"decision-making.":[28],"It":[29],"thus":[31],"to":[33,45,65,94,156,195,213],"simultaneously":[34],"optimize":[35,157],"network":[38,68,78,134],"selection":[39,69,135],"driving":[41,72,115,216],"policies":[42,73,210],"order":[44],"minimize":[46,101,124],"road":[47],"collisions":[48,102],"while":[49],"maximizing":[50],"data":[53,121,206],"rates.":[54],"In":[55],"this":[56,141],"paper,":[57],"we":[58],"develop":[59,150],"a":[60,75,144,151,170],"reinforcement":[61],"learning":[62],"(RL)":[63],"framework":[64,91],"characterize":[66],"efficient":[67],"multi-band":[76],"vehicular":[77],"(VNet)":[79],"operating":[80],"on":[81,180],"conventional":[82],"sub-6GHz":[83],"spectrum":[84],"Terahertz":[86],"(THz)":[87],"frequencies.":[88],"The":[89,174,208],"proposed":[90,209],"designed":[93],"(i)":[95],"maximize":[96,119],"traffic":[98],"flow":[99],"by":[103,126],"controlling":[104,128],"vehicle's":[106,130,199],"motion":[107,131,200],"dynamics":[108,132],"(i.e.,":[109],"speed":[110],"acceleration)":[112],"from":[113,136],"perspective,":[116],"(ii)":[118],"rates":[122],"handoffs":[125],"jointly":[127],"telecommunication":[137],"perspective.":[138],"We":[139],"cast":[140],"problem":[142],"as":[143,161],"Markov":[145],"Decision":[146],"Process":[147],"(MDP)":[148],"deep":[152],"Q-learning":[153],"based":[154,179],"solution":[155],"actions":[159],"such":[160],"acceleration,":[162],"deceleration,":[163],"lane-changes,":[164],"AV-base":[166],"station":[167],"assignments":[168],"given":[171],"AV's":[172,175],"state.":[173],"state":[176],"defined":[178],"velocities":[182],"channel":[185],"states":[186],"AVs.":[188],"Numerical":[189],"results":[190],"demonstrate":[191],"interesting":[192],"insights":[193],"related":[194],"inter-dependency":[197],"dynamics,":[201],"handoffs,":[202],"rate.":[207],"enable":[211],"AVs":[212],"adopt":[214],"safe":[215],"behaviors":[217],"with":[218],"improved":[219],"connectivity.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}