{"id":"https://openalex.org/W4401414448","doi":"https://doi.org/10.1109/icra57147.2024.10611683","title":"Active Automotive Augmented Reality Displays using Reinforcement Learning","display_name":"Active Automotive Augmented Reality Displays using Reinforcement Learning","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401414448","doi":"https://doi.org/10.1109/icra57147.2024.10611683"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611683","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10611683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","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/A5113325533","display_name":"Ju-Hyeok Ryu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131320","display_name":"LG (South Korea)","ror":"https://ror.org/03ddh2c27","country_code":"KR","type":"company","lineage":["https://openalex.org/I4210131320"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ju-Hyeok Ryu","raw_affiliation_strings":["LG Electronics,Seoul,South Korea,07796"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LG Electronics,Seoul,South Korea,07796","institution_ids":["https://openalex.org/I4210131320"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728732","display_name":"Chan Kim","orcid":"https://orcid.org/0000-0003-1642-6789"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chan Kim","raw_affiliation_strings":["Seoul National University,South Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,South Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101807134","display_name":"Seong-Woo Kim","orcid":"https://orcid.org/0000-0003-1633-573X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Woo Kim","raw_affiliation_strings":["Seoul National University,South Korea,08826"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,South Korea,08826","institution_ids":["https://openalex.org/I139264467"]}]}],"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":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"5134","last_page":"5140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13579","display_name":"Image and Video Stabilization","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T13579","display_name":"Image and Video Stabilization","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T10648","display_name":"Virtual Reality Applications and Impacts","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11687","display_name":"Teleoperation and Haptic Systems","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/automotive-industry","display_name":"Automotive industry","score":0.7572692632675171},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7002870440483093},{"id":"https://openalex.org/keywords/augmented-reality","display_name":"Augmented reality","score":0.6899981498718262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6640056371688843},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5471462607383728},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.4325115978717804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28221264481544495},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23186498880386353},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.054189860820770264}],"concepts":[{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.7572692632675171},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7002870440483093},{"id":"https://openalex.org/C153715457","wikidata":"https://www.wikidata.org/wiki/Q254183","display_name":"Augmented reality","level":2,"score":0.6899981498718262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6640056371688843},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5471462607383728},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.4325115978717804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28221264481544495},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23186498880386353},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.054189860820770264},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611683","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icra57147.2024.10611683","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1571611905","https://openalex.org/W2002156936","https://openalex.org/W2011777324","https://openalex.org/W2036087188","https://openalex.org/W2052594688","https://openalex.org/W2102295697","https://openalex.org/W2105532434","https://openalex.org/W2129373049","https://openalex.org/W2808256842","https://openalex.org/W2889987506","https://openalex.org/W2901966958","https://openalex.org/W2912793672","https://openalex.org/W2980823929","https://openalex.org/W2990054111","https://openalex.org/W3010208358","https://openalex.org/W3128806010","https://openalex.org/W3210735129","https://openalex.org/W4214682575","https://openalex.org/W4285113711","https://openalex.org/W4309445146","https://openalex.org/W4311246402","https://openalex.org/W4323831454","https://openalex.org/W4385767913","https://openalex.org/W6634102128","https://openalex.org/W6747473740","https://openalex.org/W6753526802"],"related_works":["https://openalex.org/W2172197285","https://openalex.org/W2991048842","https://openalex.org/W2750280393","https://openalex.org/W2355696739","https://openalex.org/W3158001554","https://openalex.org/W2771909920","https://openalex.org/W2957704286","https://openalex.org/W2028936041","https://openalex.org/W2179141964","https://openalex.org/W1990434954"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,32,69,84],"enhance":[3],"driving":[4,156],"convenience":[5,157],"and":[6,18,38,64,75,107,117,138,158],"safety,":[7],"automotive":[8,94,146],"Augmented":[9],"Reality":[10],"displays,":[11,14],"e.g.,":[12],"head-up":[13],"have":[15],"garnered":[16],"attention":[17],"are":[19],"gradually":[20],"being":[21],"deployed.":[22],"However,":[23],"when":[24],"vehicles":[25],"encounter":[26],"uneven":[27],"roads,":[28],"vertical":[29,91,136],"vibrations":[30],"lead":[31],"mismatches":[33,92,137],"between":[34],"external":[35],"physical":[36],"objects":[37],"augmented":[39],"reality":[40],"overlay":[41],"images,":[42],"adversely":[43],"affecting":[44],"the":[45,50,56,86,105,110,142],"AR":[46,95,147],"display\u2019s":[47],"visibility.":[48],"Resolving":[49],"problem":[51,89,106],"is":[52,65],"quite":[53],"challenging":[54],"because":[55],"optical":[57],"system":[58],"operates":[59],"on":[60],"a":[61,132],"nanometer":[62],"scale":[63],"highly":[66],"sensitive":[67],"due":[68],"its":[70],"multifunctional":[71],"nature":[72],"involving":[73],"reflection":[74],"refraction":[76],"through":[77,129],"an":[78,139],"intermediate":[79],"medium.":[80],"This":[81],"paper":[82],"aims":[83],"address":[85],"newly":[87],"emerging":[88],"of":[90,112,145],"in":[93,135,141,160],"displays.":[96,148],"To":[97],"tackle":[98],"this":[99],"issue,":[100],"we":[101,125],"begin":[102],"by":[103],"defining":[104],"then":[108],"examine":[109],"effectiveness":[111],"traditional":[113],"control":[114],"methods,":[115],"on-policy":[116],"off-policy":[118],"reinforcement":[119],"learning":[120],"as":[121],"potential":[122],"solutions.":[123],"Finally,":[124],"validate":[126],"our":[127],"approach":[128],"experiments,":[130],"demonstrating":[131],"significant":[133],"reduction":[134],"improvement":[140],"overall":[143],"visibility":[144],"Our":[149],"findings":[150],"provide":[151],"valuable":[152],"insights":[153],"for":[154],"enhancing":[155],"safety":[159],"real-world":[161],"conditions.":[162]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}