{"id":"https://openalex.org/W4367146630","doi":"https://doi.org/10.1109/tvt.2023.3270356","title":"Anti-Disturbance Self-Supervised Reinforcement Learning for Perturbed Car-Following System","display_name":"Anti-Disturbance Self-Supervised Reinforcement Learning for Perturbed Car-Following System","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367146630","doi":"https://doi.org/10.1109/tvt.2023.3270356"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2023.3270356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3270356","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5027375285","display_name":"Meng Li","orcid":"https://orcid.org/0000-0001-6944-0053"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Li","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6944-0053","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351555","display_name":"Zhibin Li","orcid":"https://orcid.org/0000-0001-7192-6853"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Li","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-7192-6853","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038878659","display_name":"Shunchao Wang","orcid":"https://orcid.org/0000-0002-7826-5880"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shunchao Wang","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7826-5880","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007015385","display_name":"Bingtong Wang","orcid":"https://orcid.org/0000-0002-5747-857X"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingtong Wang","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027375285"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":2.8694,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.90682503,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"72","issue":"9","first_page":"11318","last_page":"11331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9962000250816345,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.9926000237464905,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8088226318359375},{"id":"https://openalex.org/keywords/disturbance","display_name":"Disturbance (geology)","score":0.5931099653244019},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.564099907875061},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5175020694732666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47847363352775574},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.47090578079223633},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4463217258453369},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.4375563859939575},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.4293910562992096},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.41562551259994507},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4142683744430542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38643351197242737},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.34888580441474915},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.16457954049110413},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11973398923873901}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8088226318359375},{"id":"https://openalex.org/C2777601987","wikidata":"https://www.wikidata.org/wiki/Q5283581","display_name":"Disturbance (geology)","level":2,"score":0.5931099653244019},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.564099907875061},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5175020694732666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47847363352775574},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.47090578079223633},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4463217258453369},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.4375563859939575},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4293910562992096},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.41562551259994507},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4142683744430542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38643351197242737},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.34888580441474915},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.16457954049110413},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11973398923873901},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2023.3270356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2023.3270356","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G5180636669","display_name":null,"funder_award_id":"52232012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6891822477","display_name":null,"funder_award_id":"52272331","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1573205248","https://openalex.org/W2046482177","https://openalex.org/W2055514594","https://openalex.org/W2057483198","https://openalex.org/W2101660622","https://openalex.org/W2111876879","https://openalex.org/W2312495449","https://openalex.org/W2337632932","https://openalex.org/W2345459662","https://openalex.org/W2591292776","https://openalex.org/W2591450570","https://openalex.org/W2606206351","https://openalex.org/W2736601468","https://openalex.org/W2744953678","https://openalex.org/W2746553466","https://openalex.org/W2754517384","https://openalex.org/W2794283747","https://openalex.org/W2796582580","https://openalex.org/W2796709586","https://openalex.org/W2885305333","https://openalex.org/W2909696589","https://openalex.org/W2912445127","https://openalex.org/W2945590102","https://openalex.org/W2945843493","https://openalex.org/W2947106284","https://openalex.org/W2947981406","https://openalex.org/W2963277051","https://openalex.org/W2976036462","https://openalex.org/W2988595664","https://openalex.org/W3042395962","https://openalex.org/W3080742113","https://openalex.org/W3089188059","https://openalex.org/W3090027660","https://openalex.org/W3112606159","https://openalex.org/W3139822297","https://openalex.org/W3153676008","https://openalex.org/W3165002413","https://openalex.org/W3169363132","https://openalex.org/W3169375224","https://openalex.org/W3210590548","https://openalex.org/W3211345831","https://openalex.org/W4210404353","https://openalex.org/W4214554111","https://openalex.org/W4214643773","https://openalex.org/W4220865210","https://openalex.org/W4221110788","https://openalex.org/W4226264792","https://openalex.org/W4281972499","https://openalex.org/W4285278949","https://openalex.org/W6718092244","https://openalex.org/W6732837357","https://openalex.org/W6741002519","https://openalex.org/W6796791731"],"related_works":["https://openalex.org/W2341492732","https://openalex.org/W3187193180","https://openalex.org/W106542691","https://openalex.org/W4287027380","https://openalex.org/W1699080303","https://openalex.org/W4297799326","https://openalex.org/W2038604956","https://openalex.org/W2296560746","https://openalex.org/W2338222801","https://openalex.org/W3116064965"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3,41],"anti-disturbance":[4,61,121],"car-following":[5,43,91,111],"strategy":[6],"for":[7],"attenuating":[8],"(i)":[9],"exogenous":[10],"disturbances":[11,19],"from":[12,98],"preceding":[13],"traffic":[14],"oscillations":[15],"and":[16,29,82,129,152],"(ii)":[17],"endogenous":[18],"in":[20,148,156],"vehicular":[21],"control":[22,44,149],"systems":[23],"(e.g.,":[24],"wind":[25],"gust,":[26],"ground":[27],"friction,":[28],"rolling":[30],"resistance).":[31],"Firstly,":[32],"it":[33,47],"employs":[34],"a":[35,127,145,153],"modified":[36],"robust":[37],"controller":[38],"to":[39],"generate":[40],"expert":[42,50],"experience.":[45],"Subsequently,":[46],"imitates":[48],"the":[49,53,60,64,70,95,99,109],"behaviors":[51],"via":[52,87],"behavioral":[54],"cloning":[55],"(BC)":[56],"technique,":[57],"thereby":[58],"developing":[59],"ability.":[62],"Lastly,":[63],"obtained":[65],"policy":[66,117,125],"is":[67],"optimized":[68],"using":[69],"self-supervised":[71,113,122],"reinforcement":[72],"learning":[73],"(RL)":[74],"approach.":[75],"The":[76,119],"simulation":[77],"experiments,":[78],"comprising":[79],"both":[80],"training":[81],"evaluation":[83,136],"phases,":[84],"are":[85,160],"performed":[86],"Python.":[88],"To":[89],"simulate":[90],"scenarios,":[92],"we":[93],"utilize":[94],"ground-truth":[96],"data":[97],"Next":[100],"Generation":[101],"Simulation":[102],"(NGSIM)":[103],"datasets.":[104],"Through":[105],"recursive":[106],"interactions":[107],"with":[108,163],"perturbed":[110],"environment,":[112],"RL":[114,123],"drives":[115],"stable":[116],"improvement.":[118],"proposed":[120],"(ADSSRL)":[124],"presents":[126],"smooth":[128],"almost":[130],"monotonously":[131],"increasing":[132],"reward":[133],"curve.":[134],"Further":[135],"of":[137],"disturbance":[138],"dampening":[139],"performance":[140],"suggests":[141],"that":[142],"at":[143],"least":[144],"44.5%":[146],"reduction":[147,155],"efficiency":[150],"cost":[151,159],"10.1%":[154],"driving":[157],"comfort":[158],"achieved":[161],"compared":[162],"baselines.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
