{"id":"https://openalex.org/W3191161744","doi":"https://doi.org/10.1109/iwcmc51323.2021.9498960","title":"Safe Driving of Autonomous Vehicles through State Representation Learning","display_name":"Safe Driving of Autonomous Vehicles through State Representation Learning","publication_year":2021,"publication_date":"2021-06-28","ids":{"openalex":"https://openalex.org/W3191161744","doi":"https://doi.org/10.1109/iwcmc51323.2021.9498960","mag":"3191161744"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc51323.2021.9498960","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc51323.2021.9498960","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Wireless Communications and Mobile Computing (IWCMC)","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/A5003697769","display_name":"Abhishek Gupta","orcid":"https://orcid.org/0000-0002-8728-5146"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Abhishek Gupta","raw_affiliation_strings":["Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077151303","display_name":"Ahmed Shaharyar Khwaja","orcid":"https://orcid.org/0000-0002-9012-989X"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ahmed Shaharyar Khwaja","raw_affiliation_strings":["Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074463174","display_name":"Alagan Anpalagan","orcid":"https://orcid.org/0000-0002-6646-6052"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alagan Anpalagan","raw_affiliation_strings":["Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001287866","display_name":"Ling Guan","orcid":"https://orcid.org/0000-0002-2681-2504"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ling Guan","raw_affiliation_strings":["Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003697769"],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62796119,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"260","last_page":"265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9977999925613403,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9962000250816345,"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/autoencoder","display_name":"Autoencoder","score":0.6926275491714478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6727244257926941},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6395144462585449},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6236398816108704},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5396990180015564},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5032605528831482},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.47454723715782166},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.464183509349823},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.419704407453537},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3622244596481323},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3363455533981323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1385633945465088}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6926275491714478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727244257926941},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6395144462585449},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6236398816108704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5396990180015564},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5032605528831482},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.47454723715782166},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.464183509349823},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.419704407453537},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3622244596481323},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3363455533981323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1385633945465088},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc51323.2021.9498960","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc51323.2021.9498960","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Wireless Communications and Mobile Computing (IWCMC)","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":17,"referenced_works":["https://openalex.org/W2139160917","https://openalex.org/W2800773442","https://openalex.org/W2801194081","https://openalex.org/W2810677299","https://openalex.org/W2909906617","https://openalex.org/W2912541403","https://openalex.org/W2963165400","https://openalex.org/W2963697717","https://openalex.org/W2963762812","https://openalex.org/W2963900541","https://openalex.org/W2981207549","https://openalex.org/W2995649812","https://openalex.org/W3100789280","https://openalex.org/W4237655005","https://openalex.org/W4367295663","https://openalex.org/W6749479297","https://openalex.org/W6758582604"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,62,94],"propose":[4],"an":[5,108],"environment":[6,24],"perception":[7,25],"framework":[8],"for":[9,22,76,119,151],"autonomous":[10,69],"driving":[11,70,79],"using":[12],"state":[13],"representation":[14],"learning":[15,34,157],"(SRL).":[16],"Unlike":[17],"existing":[18],"Q-learning":[19],"based":[20,98],"methods":[21],"efficient":[23],"and":[26,58,66,111,148,153],"object":[27],"detection,":[28],"our":[29,134],"proposed":[30,135],"method":[31,136],"takes":[32],"the":[33,74,83,86,131,139,156],"loss":[35],"into":[36],"account":[37],"under":[38],"deterministic":[39,54],"as":[40,42],"well":[41],"stochastic":[43],"policy":[44,55,142],"gradient.":[45],"Through":[46],"a":[47,77,89,96,101,112],"combination":[48],"of":[49,85,92,133],"variational":[50],"autoencoder":[51],"(VAE),":[52],"deep":[53],"gradient":[56],"(DDPG),":[57],"soft":[59],"actor-critic":[60],"(SAC),":[61],"focus":[63],"on":[64,127],"uninterrupted":[65],"reasonably":[67],"safe":[68],"without":[71],"steering":[72],"off":[73],"track":[75],"considerable":[78],"distance.":[80],"To":[81],"ensure":[82],"effectiveness":[84,132],"scheme":[87],"over":[88,155],"sustained":[90],"period":[91],"time,":[93],"employ":[95],"reward-penalty":[97],"system":[99],"where":[100],"higher":[102],"negative":[103],"penalty":[104],"is":[105,117],"associated":[106],"with":[107],"unfavourable":[109],"action":[110],"comparatively":[113],"lower":[114],"positive":[115],"reward":[116,146,150],"awarded":[118],"favourable":[120],"actions.":[121],"The":[122],"results":[123],"obtained":[124],"through":[125],"simulations":[126],"DonKey":[128],"simulator":[129],"show":[130],"by":[137],"examining":[138],"variations":[140],"in":[141],"loss,":[143,145],"value":[144],"function,":[147],"cumulative":[149],"`VAE+DDPG'":[152],"`VAE+SAC'":[154],"process.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}