{"id":"https://openalex.org/W3118868204","doi":"https://doi.org/10.1109/iv47402.2020.9304668","title":"Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning","display_name":"Automated Lane Change Strategy using Proximal Policy Optimization-based Deep Reinforcement Learning","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3118868204","doi":"https://doi.org/10.1109/iv47402.2020.9304668","mag":"3118868204"},"language":"en","primary_location":{"id":"doi:10.1109/iv47402.2020.9304668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","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/A5100357227","display_name":"Fei Ye","orcid":"https://orcid.org/0000-0002-8875-4186"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I1304598786","display_name":"Program for Appropriate Technology in Health","ror":"https://ror.org/02ycvrx49","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1304598786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fei Ye","raw_affiliation_strings":["California PATH, University of California, Berkeley, Richmond, CA, USA"],"affiliations":[{"raw_affiliation_string":"California PATH, University of California, Berkeley, Richmond, CA, USA","institution_ids":["https://openalex.org/I1304598786","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018420548","display_name":"Xuxin Cheng","orcid":"https://orcid.org/0009-0002-6244-2931"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I1304598786","display_name":"Program for Appropriate Technology in Health","ror":"https://ror.org/02ycvrx49","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1304598786"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Xuxin Cheng","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China","California PATH, University of California, Berkeley, Richmond, CA, USA"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"California PATH, University of California, Berkeley, Richmond, CA, USA","institution_ids":["https://openalex.org/I1304598786","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100735652","display_name":"Pin Wang","orcid":"https://orcid.org/0000-0002-1400-4497"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]},{"id":"https://openalex.org/I1304598786","display_name":"Program for Appropriate Technology in Health","ror":"https://ror.org/02ycvrx49","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1304598786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin Wang","raw_affiliation_strings":["California PATH, University of California, Berkeley, Richmond, CA, USA"],"affiliations":[{"raw_affiliation_string":"California PATH, University of California, Berkeley, Richmond, CA, USA","institution_ids":["https://openalex.org/I1304598786","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014661259","display_name":"Ching\u2010Yao Chan","orcid":"https://orcid.org/0000-0003-3992-2312"},"institutions":[{"id":"https://openalex.org/I1304598786","display_name":"Program for Appropriate Technology in Health","ror":"https://ror.org/02ycvrx49","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1304598786"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ching-Yao Chan","raw_affiliation_strings":["California PATH, University of California, Berkeley, Richmond, CA, USA"],"affiliations":[{"raw_affiliation_string":"California PATH, University of California, Berkeley, Richmond, CA, USA","institution_ids":["https://openalex.org/I1304598786","https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014940997","display_name":"Jiucai Zhang","orcid":"https://orcid.org/0000-0002-6245-9736"},"institutions":[{"id":"https://openalex.org/I4210148712","display_name":"Silicon Valley University","ror":"https://ror.org/04jk6hn97","country_code":"US","type":"education","lineage":["https://openalex.org/I4210148712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiucai Zhang","raw_affiliation_strings":["GAC R&D Center Silicon Valley Inc., Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"GAC R&D Center Silicon Valley Inc., Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210148712"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100357227"],"corresponding_institution_ids":["https://openalex.org/I1304598786","https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":5.0809,"has_fulltext":false,"cited_by_count":121,"citation_normalized_percentile":{"value":0.95699051,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1746","last_page":"1752"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"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":0.9997000098228455,"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/T10524","display_name":"Traffic control and management","score":0.9983999729156494,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9932000041007996,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8924275636672974},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7478107810020447},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.6908693909645081},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5723003149032593},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5158397555351257},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.4700053334236145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3234788179397583},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.30465954542160034},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.15729984641075134},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14322036504745483}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8924275636672974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7478107810020447},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.6908693909645081},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5723003149032593},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5158397555351257},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.4700053334236145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3234788179397583},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.30465954542160034},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.15729984641075134},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14322036504745483},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv47402.2020.9304668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv47402.2020.9304668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W24067677","https://openalex.org/W1575592356","https://openalex.org/W1757796397","https://openalex.org/W1771410628","https://openalex.org/W1965455100","https://openalex.org/W2013375980","https://openalex.org/W2119717200","https://openalex.org/W2290104316","https://openalex.org/W2342840547","https://openalex.org/W2583993537","https://openalex.org/W2736601468","https://openalex.org/W2736629007","https://openalex.org/W2751422670","https://openalex.org/W2787196707","https://openalex.org/W2795064979","https://openalex.org/W2884690226","https://openalex.org/W2903927235","https://openalex.org/W2904263972","https://openalex.org/W2905249540","https://openalex.org/W2905334533","https://openalex.org/W2950786996","https://openalex.org/W2963322416","https://openalex.org/W2963575966","https://openalex.org/W2963590100","https://openalex.org/W2970065535","https://openalex.org/W2991030916","https://openalex.org/W2991052353","https://openalex.org/W3100944043","https://openalex.org/W3102777717","https://openalex.org/W4298857966","https://openalex.org/W6634413486","https://openalex.org/W6638018090","https://openalex.org/W6696380822","https://openalex.org/W6748571143","https://openalex.org/W6757564580","https://openalex.org/W6771278216"],"related_works":["https://openalex.org/W2264067234","https://openalex.org/W3124243301","https://openalex.org/W1571502335","https://openalex.org/W1589409554","https://openalex.org/W2759038785","https://openalex.org/W2172232600","https://openalex.org/W3123876860","https://openalex.org/W3124172198","https://openalex.org/W1819938260","https://openalex.org/W2340892746"],"abstract_inverted_index":{"Lane-change":[0],"maneuvers":[1,206],"are":[2],"commonly":[3],"executed":[4,212],"by":[5,189],"drivers":[6],"to":[7,18,48,58,63,103,156,165],"follow":[8],"a":[9,14,19,31,158,214],"certain":[10],"routing":[11],"plan,":[12],"overtake":[13],"slower":[15],"vehicle,":[16],"adapt":[17],"merging":[20],"lane":[21,26,50,129,204],"ahead,":[22],"etc.":[23],"However,":[24,100],"improper":[25],"change":[27,51,130,205],"behaviors":[28],"can":[29,207],"be":[30,208],"major":[32],"cause":[33],"of":[34,68,113,183,192],"traffic":[35,179],"flow":[36],"disruptions":[37],"and":[38,66,96,119,161,171,196,211,217],"even":[39],"crashes.":[40],"While":[41],"many":[42,89,108],"rule-based":[43],"methods":[44,74],"have":[45],"been":[46],"proposed":[47,185],"solve":[49],"problems":[52],"for":[53],"autonomous":[54,104],"driving,":[55],"they":[56],"tend":[57],"exhibit":[59],"limited":[60],"performance":[61],"due":[62],"the":[64,69,184,203],"uncertainty":[65],"complexity":[67],"driving":[70,105,163],"environment.":[71],"Machine":[72],"learning-based":[73],"offer":[75],"an":[76,127],"alternative":[77],"approach,":[78],"as":[79,177],"Deep":[80],"reinforcement":[81,137],"learning":[82,115,144],"(DRL)":[83],"has":[84],"shown":[85],"promising":[86],"success":[87,194],"in":[88,111,143,173,213],"application":[90],"domains":[91],"including":[92],"robotic":[93],"manipulation,":[94],"navigation,":[95],"playing":[97],"video":[98],"games.":[99],"applying":[101],"DRL":[102],"still":[106,147],"faces":[107],"practical":[109],"challenges":[110],"terms":[112],"slow":[114],"rates,":[116],"sample":[117],"inefficiency,":[118],"safety":[120],"concerns.":[121],"In":[122],"this":[123],"study,":[124],"we":[125],"propose":[126],"automated":[128],"strategy":[131],"using":[132,190],"proximal":[133],"policy":[134,164,186],"optimization-based":[135],"deep":[136],"learning,":[138],"which":[139],"shows":[140],"great":[141],"advantages":[142],"efficiency":[145],"while":[146],"maintaining":[148],"stable":[149],"performance.":[150],"The":[151,181,199],"trained":[152],"agent":[153],"is":[154,187],"able":[155],"learn":[157],"smooth,":[159],"safe,":[160,215],"efficient":[162,218],"make":[166],"lane-change":[167],"decisions":[168],"(i.e.":[169],"when":[170],"how)":[172],"challenging":[174],"situation":[175],"such":[176],"dense":[178],"scenarios.":[180],"effectiveness":[182],"validated":[188],"metrics":[191],"task":[193],"rate":[195],"collision":[197],"rate.":[198],"simulation":[200],"results":[201],"demonstrate":[202],"efficiently":[209],"learned":[210],"smooth":[216],"manner.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":39},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}