{"id":"https://openalex.org/W2897889564","doi":"https://doi.org/10.1109/ivs.2018.8500450","title":"Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning","display_name":"Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2897889564","doi":"https://doi.org/10.1109/ivs.2018.8500450","mag":"2897889564"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2018.8500450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 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/A5039920748","display_name":"Xiaobai Ma","orcid":"https://orcid.org/0000-0001-7491-3935"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaobai Ma","raw_affiliation_strings":["Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059066811","display_name":"Katherine Driggs-Campbell","orcid":"https://orcid.org/0000-0003-3760-9859"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katherine Driggs-Campbell","raw_affiliation_strings":["Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068326377","display_name":"Mykel J. Kochenderfer","orcid":"https://orcid.org/0000-0002-7238-9663"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mykel J. Kochenderfer","raw_affiliation_strings":["Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aeronautics and Astronautics Department, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":3.3796,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.93968397,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9958000183105469,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9958000183105469,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9833999872207642,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9789999723434448,"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":0.9256148338317871},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7764713764190674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7251360416412354},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6978987455368042},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.6000897288322449},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.5825406312942505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4991755485534668},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4272165596485138},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42448562383651733},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.35640883445739746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3316911458969116},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14939087629318237}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.9256148338317871},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7764713764190674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7251360416412354},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6978987455368042},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.6000897288322449},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.5825406312942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4991755485534668},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4272165596485138},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42448562383651733},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.35640883445739746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3316911458969116},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14939087629318237},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2018.8500450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1579118835","https://openalex.org/W1771410628","https://openalex.org/W2005299943","https://openalex.org/W2053572490","https://openalex.org/W2144274908","https://openalex.org/W2165698076","https://openalex.org/W2167696704","https://openalex.org/W2291986326","https://openalex.org/W2296360731","https://openalex.org/W2296452361","https://openalex.org/W2342662072","https://openalex.org/W2498694880","https://openalex.org/W2529477964","https://openalex.org/W2602963933","https://openalex.org/W2610784855","https://openalex.org/W2949963197","https://openalex.org/W2963342207","https://openalex.org/W2963641140","https://openalex.org/W2963937357","https://openalex.org/W2964164283","https://openalex.org/W4244577181","https://openalex.org/W4297789683","https://openalex.org/W4297824641","https://openalex.org/W6638018090","https://openalex.org/W6681187623","https://openalex.org/W6684763656","https://openalex.org/W6696772115","https://openalex.org/W6704571135","https://openalex.org/W6728252718","https://openalex.org/W6735677848","https://openalex.org/W6743367460"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W4320018150","https://openalex.org/W2918664383","https://openalex.org/W2040808657","https://openalex.org/W4320855730","https://openalex.org/W106056076","https://openalex.org/W2135200719"],"abstract_inverted_index":{"To":[0],"improve":[1],"efficiency":[2,107],"and":[3,15,46,62,67,84],"reduce":[4],"failures":[5],"in":[6,24,29],"autonomous":[7,44,72],"vehicles,":[8],"research":[9],"has":[10],"focused":[11],"on":[12,70],"developing":[13],"robust":[14,30,102],"safe":[16],"learning":[17,32,35,122],"methods":[18],"that":[19,86,94],"take":[20],"into":[21],"account":[22],"disturbances":[23,93],"the":[25,34,43,56,77,87],"environment.":[26],"Existing":[27],"literature":[28],"reinforcement":[31,121],"poses":[33],"problem":[36],"as":[37],"a":[38,81],"two":[39,51],"player":[40],"game":[41,78],"between":[42],"system":[45],"disturbances.":[47],"This":[48],"paper":[49],"examines":[50],"different":[52],"algorithms":[53],"to":[54,80,96,114],"solve":[55],"game,":[57],"Robust":[58],"Adversarial":[59],"Reinforcement":[60],"Learning":[61],"Neural":[63],"Fictitious":[64],"Self":[65],"Play,":[66],"compares":[68],"performance":[69],"an":[71],"driving":[73,106],"scenario.":[74],"We":[75],"extend":[76],"formulation":[79],"semi-competitive":[82],"setting":[83],"demonstrate":[85],"resulting":[88,101],"adversary":[89],"better":[90,97],"captures":[91],"meaningful":[92],"lead":[95],"overall":[98],"performance.":[99],"The":[100],"policy":[103],"exhibits":[104],"improved":[105],"while":[108],"effectively":[109],"reducing":[110],"collision":[111],"rates":[112],"compared":[113],"baseline":[115],"control":[116],"policies":[117],"produced":[118],"by":[119],"traditional":[120],"methods.":[123]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}