{"id":"https://openalex.org/W4392153438","doi":"https://doi.org/10.1109/globecom54140.2023.10437453","title":"Implicit Sensing in Traffic Optimization: Advanced Deep Reinforcement Learning Techniques","display_name":"Implicit Sensing in Traffic Optimization: Advanced Deep Reinforcement Learning Techniques","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4392153438","doi":"https://doi.org/10.1109/globecom54140.2023.10437453"},"language":"en","primary_location":{"id":"doi:10.1109/globecom54140.2023.10437453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5006556760","display_name":"Emanuel Figetakis","orcid":"https://orcid.org/0009-0003-1254-3598"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Emanuel Figetakis","raw_affiliation_strings":["University of Guelph,Guelph,Ontario,Canada","University of Guelph, Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,Guelph,Ontario,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032612595","display_name":"Yahuza Bello","orcid":"https://orcid.org/0000-0002-4518-0653"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yahuza Bello","raw_affiliation_strings":["University of Guelph,Guelph,Ontario,Canada","University of Guelph, Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,Guelph,Ontario,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055738950","display_name":"Ahmed Refaey","orcid":"https://orcid.org/0000-0002-1540-9349"},"institutions":[{"id":"https://openalex.org/I125749732","display_name":"Western University","ror":"https://ror.org/02grkyz14","country_code":"CA","type":"education","lineage":["https://openalex.org/I125749732"]},{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ahmed Refaey","raw_affiliation_strings":["University of Guelph,Guelph,Ontario,Canada","University of Guelph, Guelph, Ontario, Canada","Western University, London, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,Guelph,Ontario,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"Western University, London, Ontario, Canada","institution_ids":["https://openalex.org/I125749732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381347","display_name":"Lei Lei","orcid":"https://orcid.org/0000-0002-2577-6644"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Lei Lei","raw_affiliation_strings":["University of Guelph,Guelph,Ontario,Canada","University of Guelph, Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,Guelph,Ontario,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072374563","display_name":"Medhat Moussa","orcid":"https://orcid.org/0000-0002-5394-043X"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Medhat Moussa","raw_affiliation_strings":["University of Guelph,Guelph,Ontario,Canada","University of Guelph, Guelph, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Guelph,Guelph,Ontario,Canada","institution_ids":["https://openalex.org/I79817857"]},{"raw_affiliation_string":"University of Guelph, Guelph, Ontario, Canada","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1042","last_page":"1047"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9923999905586243,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9916999936103821,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8409565687179565},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230981588363647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4563103914260864},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43415695428848267},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3201233148574829}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8409565687179565},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230981588363647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4563103914260864},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43415695428848267},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3201233148574829}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom54140.2023.10437453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom54140.2023.10437453","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","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":14,"referenced_works":["https://openalex.org/W2606682591","https://openalex.org/W2963240573","https://openalex.org/W2996680849","https://openalex.org/W3015667630","https://openalex.org/W3127561923","https://openalex.org/W3165263791","https://openalex.org/W3199157630","https://openalex.org/W3212593277","https://openalex.org/W4285107713","https://openalex.org/W4285218530","https://openalex.org/W4286580809","https://openalex.org/W4288064502","https://openalex.org/W4297964528","https://openalex.org/W6736512474"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"A":[0,53],"sudden":[1,115],"roadblock":[2],"on":[3,100,183],"highways":[4],"due":[5],"to":[6,46,81,105,141,146,196],"many":[7],"reasons":[8],"such":[9,36],"as":[10,37,129],"road":[11],"maintenance,":[12],"accidents,":[13],"and":[14,40,62,74,95,135,166,193,209],"car":[15],"repair":[16],"is":[17],"a":[18,51,67,112,123,130],"common":[19],"situation":[20],"we":[21,90,110,172],"encounter":[22],"almost":[23],"daily.":[24],"Autonomous":[25],"Vehicles":[26],"(AVs)":[27],"equipped":[28],"with":[29,230],"sensors":[30],"that":[31,216],"can":[32,42],"acquire":[33],"vehicle":[34],"dynamics":[35],"speed,":[38],"acceleration,":[39],"location":[41],"make":[43,147],"intelligent":[44],"decisions":[45],"change":[47,160],"lanes":[48],"before":[49],"reaching":[50],"roadblock.":[52],"number":[54],"of":[55,169,200],"literature":[56],"studies":[57,69],"have":[58],"examined":[59],"car-following":[60,73,94],"models":[61],"lane-changing":[63,75,96],"models.":[64],"However,":[65],"only":[66],"few":[68],"proposed":[70,202],"an":[71,92,174],"integrated":[72,93],"model,":[76],"which":[77],"has":[78],"the":[79,127,137,143,148,156,164,178,188,198,201,217,222,227,231],"potential":[80],"model":[82,126,203],"practical":[83],"driving":[84],"maneuvers.":[85],"Hence,":[86],"in":[87,155],"this":[88,107],"paper,":[89],"present":[91],"decision-control":[97],"system":[98],"based":[99],"Deep":[101],"Reinforcement":[102],"Learning":[103],"(DRL)":[104],"address":[106],"issue.":[108],"Specifically,":[109],"consider":[111],"scenario":[113,128],"where":[114,177],"construction":[116],"work":[117],"will":[118],"be":[119],"carried":[120],"out":[121],"along":[122],"highway.":[124],"We":[125,186],"Markov":[131],"Decision":[132],"Process":[133],"(MDP)":[134],"employ":[136],"well-known":[138],"DQN":[139,218],"algorithm":[140],"train":[142],"RL":[144,179],"agent":[145,219],"appropriate":[149],"decision":[150],"accordingly":[151],"(i.e.,":[152],"either":[153],"stay":[154],"same":[157],"lane":[158],"or":[159],"lanes).":[161],"To":[162],"overcome":[163],"delay":[165],"computational":[167],"requirement":[168],"DRL":[170],"algorithms,":[171],"adopt":[173],"MEC-assisted":[175],"architecture":[176],"agents":[180],"are":[181],"trained":[182,220,229],"MEC":[184],"servers.":[185],"utilize":[187],"highly":[189],"reputable":[190],"SUMO":[191],"simulator":[192],"OPENAI":[194],"GYM":[195],"evaluate":[197],"performance":[199],"under":[204],"two":[205],"policies;":[206],"E-greedy":[207],"policy":[208,224],"Boltzmann":[210,232],"policy.":[211,233],"The":[212],"results":[213],"unequivocally":[214],"demonstrate":[215],"using":[221],"e-greedy":[223],"significantly":[225],"outperforms":[226],"one":[228]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}