{"id":"https://openalex.org/W3116315211","doi":"https://doi.org/10.1109/itsc45102.2020.9294194","title":"Proactive Car-Following Using Deep-Reinforcement Learning","display_name":"Proactive Car-Following Using Deep-Reinforcement Learning","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3116315211","doi":"https://doi.org/10.1109/itsc45102.2020.9294194","mag":"3116315211"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294194","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5050883049","display_name":"Yi-Tung Yen","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I3141939062","display_name":"Institute for Information Industry","ror":"https://ror.org/01d8kr740","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I3141939062"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yi-Tung Yen","raw_affiliation_strings":["Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University","institution_ids":["https://openalex.org/I16733864","https://openalex.org/I3141939062"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021619572","display_name":"Jyun\u2010Jhe Chou","orcid":"https://orcid.org/0000-0001-5845-4214"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I3141939062","display_name":"Institute for Information Industry","ror":"https://ror.org/01d8kr740","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I3141939062"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jyun-Jhe Chou","raw_affiliation_strings":["Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University","institution_ids":["https://openalex.org/I16733864","https://openalex.org/I3141939062"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057633046","display_name":"Chi\u2010Sheng Shih","orcid":"https://orcid.org/0000-0001-8936-8255"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]},{"id":"https://openalex.org/I3141939062","display_name":"Institute for Information Industry","ror":"https://ror.org/01d8kr740","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I3141939062"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chi-Sheng Shih","raw_affiliation_strings":["Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Embedded Systems and Wireless Networking Lab, Graduate Institute of Networking and Multimedia and National Taiwan University","institution_ids":["https://openalex.org/I16733864","https://openalex.org/I3141939062"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631774","display_name":"Chih\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-9640-3503"},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Wei Chen","raw_affiliation_strings":["MediaTek Inc., HsinChu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MediaTek Inc., HsinChu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018848938","display_name":"Pei-Kuei Tsung","orcid":"https://orcid.org/0009-0008-8592-3758"},"institutions":[{"id":"https://openalex.org/I4210148979","display_name":"MediaTek (Taiwan)","ror":"https://ror.org/05g9jck81","country_code":"TW","type":"company","lineage":["https://openalex.org/I4210148979"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pei-Kuei Tsung","raw_affiliation_strings":["MediaTek Inc., HsinChu, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MediaTek Inc., HsinChu, Taiwan","institution_ids":["https://openalex.org/I4210148979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.7654,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.9788925,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9998000264167786,"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":0.9998000264167786,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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":0.9950000047683716,"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/headway","display_name":"Headway","score":0.7628185153007507},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7558609247207642},{"id":"https://openalex.org/keywords/jerk","display_name":"Jerk","score":0.7441157698631287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6474093198776245},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5674153566360474},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5381252765655518},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.4832059144973755},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3823096752166748},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2973938286304474},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.28487882018089294},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.23475581407546997}],"concepts":[{"id":"https://openalex.org/C2779240695","wikidata":"https://www.wikidata.org/wiki/Q4383682","display_name":"Headway","level":2,"score":0.7628185153007507},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7558609247207642},{"id":"https://openalex.org/C181605269","wikidata":"https://www.wikidata.org/wiki/Q497332","display_name":"Jerk","level":3,"score":0.7441157698631287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474093198776245},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5674153566360474},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5381252765655518},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.4832059144973755},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3823096752166748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2973938286304474},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28487882018089294},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.23475581407546997},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294194","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322410","display_name":"MediaTek","ror":"https://ror.org/05g9jck81"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W56473762","https://openalex.org/W1600681312","https://openalex.org/W1955305638","https://openalex.org/W2077679034","https://openalex.org/W2084952317","https://openalex.org/W2129660761","https://openalex.org/W2173248099","https://openalex.org/W2724763165","https://openalex.org/W2741850495","https://openalex.org/W2753477162","https://openalex.org/W2768952159","https://openalex.org/W2792763193","https://openalex.org/W2896642734","https://openalex.org/W2900522770","https://openalex.org/W2903709398","https://openalex.org/W2912445127","https://openalex.org/W2963864421","https://openalex.org/W2967052728","https://openalex.org/W2971510799","https://openalex.org/W4394661925","https://openalex.org/W6756414644"],"related_works":["https://openalex.org/W2497204748","https://openalex.org/W4281395624","https://openalex.org/W2351684991","https://openalex.org/W1561345858","https://openalex.org/W2539932329","https://openalex.org/W1983113136","https://openalex.org/W2392989031","https://openalex.org/W4293226006","https://openalex.org/W2578626244","https://openalex.org/W2033852829"],"abstract_inverted_index":{"Car-following":[0],"is":[1,122],"a":[2,63],"fundamental":[3],"operation":[4],"for":[5,8,154],"vehicle":[6],"control":[7,16],"both":[9],"ADAS":[10],"on":[11,17],"modern":[12],"vehicles":[13,31,140],"and":[14,44,53,61,74,95,118,149],"vehilce":[15],"autonomous":[18],"vehicles.":[19],"Most":[20],"existing":[21],"car":[22],"following":[23],"mechanisms":[24,47],"react":[25],"to":[26,49,67,105,131,141],"the":[27,85,91,101,119,127,134,143,151],"observations":[28],"of":[29,36,38,93],"nearby":[30],"in":[32,114],"real-time.":[33],"Unfortunately,":[34],"lack":[35],"capability":[37],"taking":[39],"into":[40,69],"account":[41,70],"multiple":[42],"constraints":[43],"objectives,":[45],"these":[46],"lead":[48],"poor":[50],"efficiency,":[51,73],"discomfort,":[52],"unsafe":[54,96],"operations.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59],"design":[60],"implement":[62],"proactive":[64,86],"car-following":[65],"model":[66,87,109,136,147],"take":[68],"safety":[71],"regulation,":[72],"comfort":[75],"using":[76],"deep":[77],"reinforcement":[78],"learning.":[79],"The":[80,108],"evaluation":[81],"results":[82],"show":[83],"that":[84],"not":[88],"only":[89,123],"reduces":[90],"number":[92],"inefficient":[94],"headway":[97],"but":[98],"also":[99],"eliminates":[100],"traffic":[102],"jerk,":[103],"compared":[104],"human":[106,112],"drivers.":[107],"outperformed":[110],"79%":[111],"drivers":[113],"public":[115],"data":[116],"set":[117],"road":[120],"efficiency":[121],"2%":[124],"less":[125],"than":[126,145],"optimal":[128],"bound.":[129],"Compared":[130],"ACC":[132,146],"model,":[133],"DDPG":[135],"allows":[137],"4.4%":[138],"more":[139],"finish":[142],"simulation":[144],"does,":[148],"increases":[150],"average":[152],"speed":[153],"28.4%.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}