{"id":"https://openalex.org/W4285145842","doi":"https://doi.org/10.1109/tiv.2022.3184729","title":"Autonomous Driving Policy Continual Learning With One-Shot Disengagement Case","display_name":"Autonomous Driving Policy Continual Learning With One-Shot Disengagement Case","publication_year":2022,"publication_date":"2022-06-21","ids":{"openalex":"https://openalex.org/W4285145842","doi":"https://doi.org/10.1109/tiv.2022.3184729"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2022.3184729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3184729","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-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/A5016651437","display_name":"Zhong Cao","orcid":"https://orcid.org/0000-0002-2243-5705"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Cao","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2243-5705","affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631401","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0003-0569-2176"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Qiyuan Lab, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qiyuan Lab, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kun Jiang","orcid":"https://orcid.org/0000-0001-7282-172X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Jiang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7282-172X","affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050020266","display_name":"Weitao Zhou","orcid":"https://orcid.org/0000-0002-1266-3843"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weitao Zhou","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1266-3843","affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455486","display_name":"Xiaoyu Liu","orcid":"https://orcid.org/0000-0001-7854-4866"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Liu","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013415505","display_name":"Nanshan Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanshan Deng","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100735948","display_name":"Diange Yang","orcid":"https://orcid.org/0000-0002-0074-2448"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Diange Yang","raw_affiliation_strings":["School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0074-2448","affiliations":[{"raw_affiliation_string":"School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2868,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.7793838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":"2","first_page":"1380","last_page":"1391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9973999857902527,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9754999876022339,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/disengagement-theory","display_name":"Disengagement theory","score":0.9734269380569458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5207862257957458},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.48773083090782166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.472332626581192},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4643564224243164},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.42575421929359436},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41815200448036194},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4167366027832031},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4050012230873108},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33265796303749084},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.31853795051574707},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24511995911598206}],"concepts":[{"id":"https://openalex.org/C25740722","wikidata":"https://www.wikidata.org/wiki/Q3044915","display_name":"Disengagement theory","level":2,"score":0.9734269380569458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5207862257957458},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.48773083090782166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.472332626581192},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4643564224243164},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.42575421929359436},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41815200448036194},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4167366027832031},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4050012230873108},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33265796303749084},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.31853795051574707},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24511995911598206},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74909509","wikidata":"https://www.wikidata.org/wiki/Q10387","display_name":"Gerontology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2022.3184729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3184729","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G1230750079","display_name":null,"funder_award_id":"52102460","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6988613448","display_name":null,"funder_award_id":"2021M701883","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7458066130","display_name":null,"funder_award_id":"U1864203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W174147238","https://openalex.org/W1965455100","https://openalex.org/W1972060013","https://openalex.org/W1977085960","https://openalex.org/W2056877664","https://openalex.org/W2076290341","https://openalex.org/W2100488636","https://openalex.org/W2107338474","https://openalex.org/W2504001346","https://openalex.org/W2594201198","https://openalex.org/W2621719447","https://openalex.org/W2742058231","https://openalex.org/W2784675945","https://openalex.org/W2884634491","https://openalex.org/W2891526102","https://openalex.org/W2913416895","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2968296999","https://openalex.org/W3000193750","https://openalex.org/W3005458448","https://openalex.org/W3034942609","https://openalex.org/W3113555494","https://openalex.org/W3120197634","https://openalex.org/W3121012756","https://openalex.org/W3148740559","https://openalex.org/W3178012085","https://openalex.org/W3181350748","https://openalex.org/W3207915602","https://openalex.org/W4241567030","https://openalex.org/W6607124794","https://openalex.org/W6637967152","https://openalex.org/W6735944222","https://openalex.org/W6745935785","https://openalex.org/W6746348303","https://openalex.org/W6747473740","https://openalex.org/W6753596642","https://openalex.org/W6757223306"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W4376166922","https://openalex.org/W2490526372","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Disengagement":[0],"cases":[1,52],"during":[2,207],"naturalistic":[3],"driving":[4,61,155,165],"are":[5,18,117],"rare":[6],"or":[7,44],"even":[8],"one-shot,":[9],"but":[10,150],"valuable":[11],"for":[12,31,100,132],"autonomous":[13,16,164,172],"driving.":[14],"The":[15,83,136,174],"vehicles":[17],"necessary":[19],"to":[20,27,48,87,119,128,142,184,199],"continually":[21,70],"learn":[22,183],"from":[23,169],"these":[24,38,50],"disengagement":[25,51,81,148,166,188],"cases,":[26],"improve":[28],"the":[29,42,46,95,111,114,122,129,133,144,147,153,162,178,186,201],"policy":[30,43,96,134],"better":[32],"performance":[33,101],"when":[34],"next":[35],"time":[36],"meeting":[37],"cases.":[39,192],"Manually":[40],"adjusting":[41],"adding":[45],"rules":[47],"fix":[49],"may":[53,58],"cause":[54],"engineering":[55],"burden":[56],"and":[57,92,125,190],"contradict":[59],"other":[60],"functions.":[62],"To":[63],"this":[64,66],"end,":[65],"work":[67,194],"proposes":[68],"a":[69,80,89,196],"learning":[71,108],"agent":[72,180],"which":[73],"can":[74,181],"automatically":[75,182,204],"get":[76,205],"improved":[77],"once":[78],"encountering":[79],"case.":[82,156],"main":[84],"idea":[85],"is":[86,139,159],"establish":[88],"disengagement-imagination":[90],"environment,":[91,113],"then":[93,126],"train":[94],"using":[97],"imagination":[98,105,112,145],"data":[99],"improvement,":[102],"named":[103],"disengagement-case":[104],"augmented":[106],"continual":[107],"(DICL).":[109],"In":[110],"surrounding":[115],"objects":[116],"designed":[118,141],"first":[120],"follow":[121],"recorded":[123],"trajectory,":[124],"switch":[127,137],"interactive":[130],"models":[131],"training.":[135],"point":[138],"carefully":[140],"make":[143,200],"contain":[146],"reasons":[149],"avoid":[151],"overfitting":[152],"collected":[154,168],"This":[157,193],"method":[158],"evaluated":[160],"by":[161],"real":[163],"data,":[167],"an":[170],"open-road-testing":[171],"vehicle.":[173],"results":[175],"show":[176],"that":[177],"DICL":[179],"handle":[185],"emerging":[187],"case":[189],"similar":[191],"provides":[195],"possible":[197],"way":[198],"AV":[202],"agents":[203],"improvement":[206],"road":[208],"testing.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}