{"id":"https://openalex.org/W4414539401","doi":"https://doi.org/10.1109/icc52391.2025.11162119","title":"Hybrid Deep Learning Optimization for Accurate Trajectory Prediction in Vehicular Networks","display_name":"Hybrid Deep Learning Optimization for Accurate Trajectory Prediction in Vehicular Networks","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539401","doi":"https://doi.org/10.1109/icc52391.2025.11162119"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11162119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5094199347","display_name":"Abdel Razak Hamadou Adamou","orcid":"https://orcid.org/0009-0009-1909-8304"},"institutions":[{"id":"https://openalex.org/I197681013","display_name":"Universit\u00e9 Paris-Est Cr\u00e9teil","ror":"https://ror.org/05ggc9x40","country_code":"FR","type":"education","lineage":["https://openalex.org/I197681013"]},{"id":"https://openalex.org/I2800365227","display_name":"Paris-Est Sup","ror":"https://ror.org/0268ecp52","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800365227"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Abdel Razak Hamadou Adamou","raw_affiliation_strings":["Univ. Paris Est Creteil,LACL,Creteil,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Paris Est Creteil,LACL,Creteil,France","institution_ids":["https://openalex.org/I197681013","https://openalex.org/I2800365227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061965262","display_name":"Lynda Mokdad","orcid":"https://orcid.org/0000-0002-6182-4869"},"institutions":[{"id":"https://openalex.org/I197681013","display_name":"Universit\u00e9 Paris-Est Cr\u00e9teil","ror":"https://ror.org/05ggc9x40","country_code":"FR","type":"education","lineage":["https://openalex.org/I197681013"]},{"id":"https://openalex.org/I2800365227","display_name":"Paris-Est Sup","ror":"https://ror.org/0268ecp52","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800365227"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lynda Mokdad","raw_affiliation_strings":["Univ. Paris Est Creteil,LACL,Creteil,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Paris Est Creteil,LACL,Creteil,France","institution_ids":["https://openalex.org/I197681013","https://openalex.org/I2800365227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085749623","display_name":"Jalel Ben\u2010Othman","orcid":"https://orcid.org/0000-0001-6942-5435"},"institutions":[{"id":"https://openalex.org/I197681013","display_name":"Universit\u00e9 Paris-Est Cr\u00e9teil","ror":"https://ror.org/05ggc9x40","country_code":"FR","type":"education","lineage":["https://openalex.org/I197681013"]},{"id":"https://openalex.org/I2800365227","display_name":"Paris-Est Sup","ror":"https://ror.org/0268ecp52","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800365227"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jalel Ben Othman","raw_affiliation_strings":["Univ. Paris Est Creteil,LISSI,Creteil,France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Paris Est Creteil,LISSI,Creteil,France","institution_ids":["https://openalex.org/I197681013","https://openalex.org/I2800365227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028077425","display_name":"Ali Benzerbadj","orcid":"https://orcid.org/0000-0003-2576-5504"},"institutions":[{"id":"https://openalex.org/I4210163438","display_name":"Universit\u00e9 de ain T\u00e9mouchent","ror":"https://ror.org/05ckyqt97","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210163438"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Ali Benzerbadj","raw_affiliation_strings":["Univ. Ain Temouchent, Univ. Oran1,RIIR Laboratory,Ain Temouchent,Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. Ain Temouchent, Univ. Oran1,RIIR Laboratory,Ain Temouchent,Algeria","institution_ids":["https://openalex.org/I4210163438"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4197","last_page":"4202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955000281333923,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9614999890327454,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9591000080108643,"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/trajectory","display_name":"Trajectory","score":0.7372999787330627},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7138000130653381},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6403999924659729},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5428000092506409},{"id":"https://openalex.org/keywords/vehicular-ad-hoc-network","display_name":"Vehicular ad hoc network","score":0.5303000211715698},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5078999996185303},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4749999940395355}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7372999787330627},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7138000130653381},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6704999804496765},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6403999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6062999963760376},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C192448918","wikidata":"https://www.wikidata.org/wiki/Q682677","display_name":"Vehicular ad hoc network","level":4,"score":0.5303000211715698},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4749999940395355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3677000105381012},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36039999127388},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3433000147342682},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C30095986","wikidata":"https://www.wikidata.org/wiki/Q1035238","display_name":"Vehicular communication systems","level":5,"score":0.2685999870300293},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11162119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11162119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2808425487","https://openalex.org/W2963906196","https://openalex.org/W2963914175","https://openalex.org/W3083789190","https://openalex.org/W3127304128","https://openalex.org/W4283264004","https://openalex.org/W4284898377","https://openalex.org/W4388901841","https://openalex.org/W4408325908"],"related_works":[],"abstract_inverted_index":{"Vehicular":[0],"Ad-Hoc":[1],"Networks":[2,44],"(VANETs)":[3],"are":[4],"essential":[5],"for":[6,82],"enhancing":[7],"traffic":[8,30],"management":[9],"and":[10,16,46,67,75],"road":[11],"safety":[12],"through":[13],"vehicle-to-vehicle":[14],"(V2V)":[15],"vehicle-to-infrastructure":[17],"(V2I)":[18],"communication.":[19],"Accurately":[20],"predicting":[21],"vehicle":[22],"trajectories":[23],"is":[24],"critical":[25],"yet":[26],"challenging":[27],"in":[28,68,84],"dynamic":[29],"conditions.":[31],"The":[32],"paper":[33],"proposes":[34],"an":[35],"optimized":[36],"hybrid":[37],"deep":[38],"learning":[39],"model":[40,79],"combining":[41],"Convolutional":[42],"Neural":[43],"(CNNs)":[45],"Long":[47],"Short-Term":[48],"Memory":[49],"(LSTM)":[50],"networks":[51],"to":[52],"improve":[53],"trajectory":[54],"prediction.":[55],"Simulation":[56],"results":[57],"on":[58,65],"real-world":[59],"datasets":[60],"(GPS":[61],"tracks":[62],"of":[63],"vehicles":[64],"highways":[66],"urban":[69],"areas)":[70],"demonstrate":[71],"higher":[72],"prediction":[73],"accuracy":[74],"efficiency,":[76],"making":[77],"the":[78],"highly":[80],"effective":[81],"deployment":[83],"real-time":[85],"smart":[86],"city":[87],"systems.":[88]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}