{"id":"https://openalex.org/W3090893985","doi":"https://doi.org/10.1109/icpr48806.2021.9412200","title":"A Bayesian Approach to Reinforcement Learning of Vision-Based Vehicular Control","display_name":"A Bayesian Approach to Reinforcement Learning of Vision-Based Vehicular Control","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3090893985","doi":"https://doi.org/10.1109/icpr48806.2021.9412200","mag":"3090893985"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5017564607","display_name":"Zahra Gharaee","orcid":"https://orcid.org/0000-0003-0140-0025"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Zahra Gharaee","raw_affiliation_strings":["Department of Electrical Engineering, Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044139676","display_name":"Karl Holmquist","orcid":"https://orcid.org/0000-0002-8677-8715"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Karl Holmquist","raw_affiliation_strings":["Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden"],"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011425038","display_name":"Linbo He","orcid":null},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Linbo He","raw_affiliation_strings":["Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden"],"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042087981","display_name":"Michael Felsberg","orcid":"https://orcid.org/0000-0002-6096-3648"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Michael Felsberg","raw_affiliation_strings":["Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden"],"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory (CVL), University of Link\u00f6ping, Link\u00f6ping, Sweden","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5017564607"],"corresponding_institution_ids":["https://openalex.org/I102134673"],"apc_list":null,"apc_paid":null,"fwci":0.4079,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66277133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"135","issue":null,"first_page":"3947","last_page":"3954"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9908000230789185,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9853000044822693,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8097334504127502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7124701738357544},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6023818850517273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5829557180404663},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.46417757868766785},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46141016483306885},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35759469866752625}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8097334504127502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7124701738357544},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6023818850517273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5829557180404663},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.46417757868766785},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46141016483306885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35759469866752625}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1515851193","https://openalex.org/W1700665419","https://openalex.org/W1757796397","https://openalex.org/W1971331236","https://openalex.org/W2006681603","https://openalex.org/W2040908214","https://openalex.org/W2089674328","https://openalex.org/W2107525266","https://openalex.org/W2124695578","https://openalex.org/W2257979135","https://openalex.org/W2534269850","https://openalex.org/W2554120691","https://openalex.org/W2575705757","https://openalex.org/W2606508169","https://openalex.org/W2737258237","https://openalex.org/W2740067745","https://openalex.org/W2781726626","https://openalex.org/W2799017078","https://openalex.org/W2883090707","https://openalex.org/W2891315523","https://openalex.org/W2904246096","https://openalex.org/W2952542181","https://openalex.org/W2952629144","https://openalex.org/W2962696750","https://openalex.org/W2962867954","https://openalex.org/W2962894046","https://openalex.org/W2962977206","https://openalex.org/W2963170229","https://openalex.org/W2963946945","https://openalex.org/W2964043796","https://openalex.org/W2965140792","https://openalex.org/W3009593063","https://openalex.org/W3026050828","https://openalex.org/W3045414474","https://openalex.org/W3158154771","https://openalex.org/W4295719664","https://openalex.org/W4298857966","https://openalex.org/W4400608488","https://openalex.org/W6637656884","https://openalex.org/W6692846177","https://openalex.org/W6728925229","https://openalex.org/W6745935785","https://openalex.org/W6747473740","https://openalex.org/W6750106230","https://openalex.org/W6753287391"],"related_works":["https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4380318855","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W3049728571","https://openalex.org/W20361778","https://openalex.org/W2024136090","https://openalex.org/W2964765435"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,73],"present":[4],"a":[5,20,38,68,110,123],"state-of-the-art":[6],"reinforcement":[7],"learning":[8,18],"method":[9],"for":[10,101,127],"autonomous":[11],"driving.":[12],"Our":[13],"approach":[14],"employs":[15],"temporal":[16],"difference":[17],"in":[19,109],"Bayesian":[21],"framework":[22],"to":[23,35,45,85,129,143,153],"learn":[24],"vehicle":[25],"control":[26],"signals":[27],"from":[28,37,67],"sensor":[29],"data.":[30],"The":[31,103,119,134],"agent":[32],"has":[33],"access":[34],"images":[36],"forward":[39],"facing":[40],"camera,":[41],"which":[42],"are":[43],"preprocessed":[44],"generate":[46],"semantic":[47,60],"segmentation":[48,61],"maps.":[49],"We":[50],"trained":[51,106],"our":[52,65],"system":[53,78,91,104,140],"using":[54,115],"both":[55],"ground":[56,80],"truth":[57,81],"and":[58,107,132,146],"estimated":[59,93,97],"input.":[62],"Based":[63],"on":[64,79,92,149],"observations":[66],"large":[69],"set":[70],"of":[71,138],"experiments,":[72],"conclude":[74],"that":[75,125],"training":[76,89,136],"the":[77,90,116,139,147,150],"input":[82,94,98],"data":[83],"leads":[84],"better":[86],"performance":[87,148],"than":[88],"even":[95],"if":[96],"is":[99,105,141],"used":[100],"evaluation.":[102],"evaluated":[108],"realistic":[111],"simulated":[112],"urban":[113],"environment":[114],"CARLA":[117],"simulator.":[118],"simulator":[120],"also":[121],"contains":[122],"benchmark":[124,151],"allows":[126],"comparing":[128],"other":[130],"systems":[131],"methods.":[133],"required":[135],"time":[137],"shown":[142],"be":[144],"lower":[145],"superior":[152],"competing":[154],"approaches.":[155]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
