{"id":"https://openalex.org/W4408610955","doi":"https://doi.org/10.1109/icaiic64266.2025.10920760","title":"BiLSTM-Based VAE-GAN for Predicting Future Road States in Autonomous Driving","display_name":"BiLSTM-Based VAE-GAN for Predicting Future Road States in Autonomous Driving","publication_year":2025,"publication_date":"2025-02-18","ids":{"openalex":"https://openalex.org/W4408610955","doi":"https://doi.org/10.1109/icaiic64266.2025.10920760"},"language":"en","primary_location":{"id":"doi:10.1109/icaiic64266.2025.10920760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic64266.2025.10920760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","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/A5012176121","display_name":"Dong-Hyun Kim","orcid":"https://orcid.org/0000-0003-4226-8032"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Donghyun Kim","raw_affiliation_strings":["Hanyang University,Division of Electrical Engineering,Ansan,South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Division of Electrical Engineering,Ansan,South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045732610","display_name":"Jaerock Kwon","orcid":"https://orcid.org/0000-0002-5687-6998"},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jaerock Kwon","raw_affiliation_strings":["University of Michigan-Dearborn,Electrical and Computer Engineering,Dearborn,United States of America"],"affiliations":[{"raw_affiliation_string":"University of Michigan-Dearborn,Electrical and Computer Engineering,Dearborn,United States of America","institution_ids":["https://openalex.org/I4210130704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113499996","display_name":"Haewoon Nam","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Haewoon Nam","raw_affiliation_strings":["Hanyang University,Division of Electrical Engineering,Ansan,South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Division of Electrical Engineering,Ansan,South Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012176121"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05714603,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"0905","last_page":"0907"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9682000279426575,"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":0.9682000279426575,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9646000266075134,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9488999843597412,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5170924663543701}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5170924663543701}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaiic64266.2025.10920760","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaiic64266.2025.10920760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2079735306","https://openalex.org/W3015256491","https://openalex.org/W3040099731","https://openalex.org/W6640963894","https://openalex.org/W6687506355","https://openalex.org/W6745935785"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0,37,93,140],"ability":[1,126],"to":[2,31,64,127,149,183],"accurately":[3],"predict":[4],"future":[5,34,113,160],"road":[6,35,88,114,161],"conditions":[7,89],"is":[8],"essential":[9],"for":[10,173],"the":[11,41,49,75,82,105,124,143,146,166,171],"advancement":[12],"of":[13,44,52,107,145],"autonomous":[14,156,179],"driving":[15,71,180,188],"systems.":[16,189],"This":[17],"study":[18],"introduces":[19],"a":[20],"BiLSTM-based":[21,167],"VAE-GAN":[22,168],"framework":[23,148,169],"that":[24],"leverages":[25],"both":[26],"temporal":[27,67],"and":[28,90,101,110,120,136,152,185],"spatial":[29],"information":[30],"generate":[32],"high-quality":[33],"images.":[36,115],"proposed":[38,147],"architecture":[39],"combines":[40],"reconstruction":[42,97,138],"capabilities":[43],"Variational":[45],"Auto-Encoders":[46],"(VAEs)":[47],"with":[48,163],"adversarial":[50,102],"training":[51,94],"Generative":[53],"Adversarial":[54],"Networks":[55],"(GANs),":[56],"while":[57],"incorporating":[58],"Bidirectional":[59],"Long":[60],"Short-Term":[61],"Memory":[62],"(BiLSTM)":[63],"effectively":[65],"capture":[66],"dependencies":[68],"in":[69,155],"sequential":[70],"data.":[72],"To":[73],"train":[74],"model,":[76],"diverse":[77],"datasets":[78],"were":[79],"collected":[80],"from":[81],"CARLA":[83],"simulation":[84],"environment,":[85],"encompassing":[86],"various":[87],"vehicle":[91],"states.":[92],"process":[95],"minimizes":[96],"loss,":[98,103],"KL":[99],"divergence,":[100],"enabling":[104],"generation":[106],"visually":[108],"consistent":[109],"semantically":[111],"accurate":[112],"Quantitative":[116],"evaluations":[117],"using":[118],"PSNR":[119],"MSE":[121],"metrics":[122],"demonstrate":[123],"model's":[125],"outperform":[128],"conventional":[129],"VAE-based":[130],"approaches,":[131],"achieving":[132],"high":[133,164],"structural":[134],"similarity":[135],"low":[137],"errors.":[139],"results":[141],"highlight":[142],"potential":[144],"enhance":[150],"decision-making":[151],"lane-keeping":[153],"performance":[154],"vehicles.":[157],"By":[158],"predicting":[159],"states":[162],"fidelity,":[165],"lays":[170],"groundwork":[172],"integrating":[174],"generative":[175],"models":[176],"into":[177],"real-world":[178],"applications,":[181],"contributing":[182],"safer":[184],"more":[186],"reliable":[187]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
