{"id":"https://openalex.org/W3198999478","doi":"https://doi.org/10.1109/tnnls.2021.3109284","title":"Deductive Reinforcement Learning for Visual Autonomous Urban Driving Navigation","display_name":"Deductive Reinforcement Learning for Visual Autonomous Urban Driving Navigation","publication_year":2021,"publication_date":"2021-09-14","ids":{"openalex":"https://openalex.org/W3198999478","doi":"https://doi.org/10.1109/tnnls.2021.3109284","mag":"3198999478","pmid":"https://pubmed.ncbi.nlm.nih.gov/34520367"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3109284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3109284","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5046865333","display_name":"Changxin Huang","orcid":"https://orcid.org/0000-0002-9588-064X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changxin Huang","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9588-064X","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029387407","display_name":"Ronghui Zhang","orcid":"https://orcid.org/0000-0001-6107-4044"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghui Zhang","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084732104","display_name":"Meizi Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meizi Ouyang","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041227759","display_name":"Pengxu Wei","orcid":"https://orcid.org/0000-0002-2190-0767"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengxu Wei","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2190-0767","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007186226","display_name":"Junfan Lin","orcid":"https://orcid.org/0000-0002-0099-6886"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfan Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102792444","display_name":"Jiang Su","orcid":"https://orcid.org/0000-0003-4020-9151"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang Su","raw_affiliation_strings":["DMAI Great China, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DMAI Great China, Guangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100412937","display_name":"Liang Lin","orcid":"https://orcid.org/0000-0003-2248-3755"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Lin","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2248-3755","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5046865333"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":4.8982,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.95902762,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"32","issue":"12","first_page":"5379","last_page":"5391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9991000294685364,"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":0.9815000295639038,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8788345456123352},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7712366580963135},{"id":"https://openalex.org/keywords/semantic-reasoner","display_name":"Semantic reasoner","score":0.6512710452079773},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5665240287780762},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5509620308876038},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5459396839141846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5014619827270508},{"id":"https://openalex.org/keywords/damages","display_name":"Damages","score":0.47017329931259155},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.44614025950431824},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4214051067829132},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41708576679229736}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8788345456123352},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7712366580963135},{"id":"https://openalex.org/C9616225","wikidata":"https://www.wikidata.org/wiki/Q3929429","display_name":"Semantic reasoner","level":2,"score":0.6512710452079773},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5665240287780762},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5509620308876038},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5459396839141846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5014619827270508},{"id":"https://openalex.org/C2777381055","wikidata":"https://www.wikidata.org/wiki/Q308922","display_name":"Damages","level":2,"score":0.47017329931259155},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.44614025950431824},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4214051067829132},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41708576679229736},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3109284","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3109284","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34520367","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34520367","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1295000622","display_name":null,"funder_award_id":"61836012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3577923441","display_name":null,"funder_award_id":"U1811463","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4227929592","display_name":null,"funder_award_id":"62006253","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G517407545","display_name":null,"funder_award_id":"61976233","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7164151747","display_name":null,"funder_award_id":"U181146","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8558289817","display_name":null,"funder_award_id":"61876224","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8879444097","display_name":null,"funder_award_id":"2020AAA0109700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":101,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1845972764","https://openalex.org/W1959608418","https://openalex.org/W1977655452","https://openalex.org/W2032924574","https://openalex.org/W2092235585","https://openalex.org/W2096630263","https://openalex.org/W2119112357","https://openalex.org/W2121863487","https://openalex.org/W2140135625","https://openalex.org/W2144172034","https://openalex.org/W2150468603","https://openalex.org/W2151361137","https://openalex.org/W2156547346","https://openalex.org/W2165150801","https://openalex.org/W2167224731","https://openalex.org/W2173248099","https://openalex.org/W2187089797","https://openalex.org/W2270657321","https://openalex.org/W2334782222","https://openalex.org/W2340897893","https://openalex.org/W2396217537","https://openalex.org/W2530849036","https://openalex.org/W2550936442","https://openalex.org/W2559767995","https://openalex.org/W2560609797","https://openalex.org/W2563338958","https://openalex.org/W2583993537","https://openalex.org/W2606047872","https://openalex.org/W2621150162","https://openalex.org/W2727840223","https://openalex.org/W2736601468","https://openalex.org/W2738669288","https://openalex.org/W2766614170","https://openalex.org/W2770884134","https://openalex.org/W2785389871","https://openalex.org/W2794284562","https://openalex.org/W2837605352","https://openalex.org/W2886616503","https://openalex.org/W2890208753","https://openalex.org/W2905173465","https://openalex.org/W2920362155","https://openalex.org/W2950989657","https://openalex.org/W2962867954","https://openalex.org/W2962872206","https://openalex.org/W2962894046","https://openalex.org/W2962977206","https://openalex.org/W2963219401","https://openalex.org/W2963328631","https://openalex.org/W2963402657","https://openalex.org/W2963846044","https://openalex.org/W2963864421","https://openalex.org/W2963872524","https://openalex.org/W2963960193","https://openalex.org/W2964036701","https://openalex.org/W2964043796","https://openalex.org/W2964198579","https://openalex.org/W2964220198","https://openalex.org/W2964309882","https://openalex.org/W2968983352","https://openalex.org/W2972127687","https://openalex.org/W3009593063","https://openalex.org/W3034431214","https://openalex.org/W3100944043","https://openalex.org/W3103780890","https://openalex.org/W3104842437","https://openalex.org/W3107575247","https://openalex.org/W3209092760","https://openalex.org/W4293396018","https://openalex.org/W4294555834","https://openalex.org/W4295719664","https://openalex.org/W4297789121","https://openalex.org/W4298206671","https://openalex.org/W4301501993","https://openalex.org/W4302570325","https://openalex.org/W6640963894","https://openalex.org/W6680657880","https://openalex.org/W6681239517","https://openalex.org/W6684205842","https://openalex.org/W6684338915","https://openalex.org/W6684921986","https://openalex.org/W6692846177","https://openalex.org/W6712453370","https://openalex.org/W6712884540","https://openalex.org/W6729572786","https://openalex.org/W6736482081","https://openalex.org/W6736803224","https://openalex.org/W6738483526","https://openalex.org/W6740836278","https://openalex.org/W6741002519","https://openalex.org/W6745935785","https://openalex.org/W6746462176","https://openalex.org/W6748012927","https://openalex.org/W6748481559","https://openalex.org/W6748519856","https://openalex.org/W6751494529","https://openalex.org/W6753882966","https://openalex.org/W6754184789","https://openalex.org/W6756871163","https://openalex.org/W6760405395","https://openalex.org/W6782130551"],"related_works":["https://openalex.org/W335786557","https://openalex.org/W1964760324","https://openalex.org/W4205240985","https://openalex.org/W2043069798","https://openalex.org/W1525578575","https://openalex.org/W2106246118","https://openalex.org/W2314597598","https://openalex.org/W1527183021","https://openalex.org/W3125296675","https://openalex.org/W4235320026"],"abstract_inverted_index":{"Existing":[0],"deep":[1],"reinforcement":[2],"learning":[3],"(RL)":[4],"are":[5],"devoted":[6],"to":[7,52,66,76,82,87,110,132,144,167],"research":[8],"applications":[9],"on":[10,162,176],"video":[11],"games,":[12],"e.g.,":[13],"The":[14],"Open":[15],"Racing":[16],"Car":[17],"Simulator":[18],"(TORCS)":[19],"and":[20,44,86,171,179],"Atari":[21],"games.":[22],"However,":[23],"it":[24],"remains":[25],"under-explored":[26],"for":[27,182],"vision-based":[28],"autonomous":[29],"urban":[30],"driving":[31,135,180],"navigation":[32],"(VB-AUDN).":[33],"VB-AUDN":[34],"requires":[35],"a":[36,62,98,119,125,173],"sophisticated":[37],"agent":[38,79],"working":[39],"safely":[40],"in":[41,118],"structured,":[42],"changing,":[43],"unpredictable":[45],"environments;":[46],"otherwise,":[47],"inappropriate":[48],"operations":[49],"may":[50],"lead":[51],"irreversible":[53],"or":[54],"catastrophic":[55],"damages.":[56],"In":[57],"this":[58,68],"work,":[59],"we":[60],"propose":[61],"deductive":[63],"RL":[64,160],"(DeRL)":[65],"address":[67],"challenge.":[69],"A":[70],"deduction":[71],"reasoner":[72],"(DR)":[73],"is":[74,130,142],"introduced":[75],"endow":[77],"the":[78,84,107,112,138,145,148,157,163],"with":[80],"ability":[81],"foresee":[83],"future":[85,95],"promote":[88],"policy":[89,116],"learning.":[90],"Specifically,":[91],"DR":[92,103],"first":[93],"predicts":[94],"transitions":[96],"through":[97],"parameterized":[99],"environment":[100],"model.":[101],"Then,":[102],"conducts":[104],"self-assessment":[105],"at":[106],"predicted":[108],"trajectory":[109],"perceive":[111],"consequences":[113],"of":[114,147],"current":[115],"resulting":[117],"more":[120],"reliable":[121],"decision-making":[122],"process.":[123],"Additionally,":[124],"semantic":[126],"encoder":[127],"module":[128],"(SEM)":[129],"designed":[131],"extract":[133],"compact":[134],"representation":[136],"from":[137],"raw":[139],"images,":[140],"which":[141],"robust":[143],"changes":[146],"environment.":[149],"Extensive":[150],"experimental":[151],"results":[152],"demonstrate":[153],"that":[154],"DeRL":[155],"outperforms":[156],"state-of-the-art":[158],"model-free":[159],"approaches":[161],"public":[164],"CAR":[165],"Learning":[166],"Act":[168],"(CARLA)":[169],"benchmark":[170],"presents":[172],"superior":[174],"performance":[175],"success":[177],"rate":[178],"safety":[181],"goal-directed":[183],"navigation.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-30T09:04:40.226872","created_date":"2025-10-10T00:00:00"}
