{"id":"https://openalex.org/W3203124669","doi":"https://doi.org/10.1109/iros51168.2021.9636480","title":"Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning","display_name":"Motion Planning for Autonomous Vehicles in the Presence of Uncertainty Using Reinforcement Learning","publication_year":2021,"publication_date":"2021-09-27","ids":{"openalex":"https://openalex.org/W3203124669","doi":"https://doi.org/10.1109/iros51168.2021.9636480","mag":"3203124669"},"language":"en","primary_location":{"id":"doi:10.1109/iros51168.2021.9636480","doi":"https://doi.org/10.1109/iros51168.2021.9636480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636480","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2110.00640","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078758172","display_name":"Kasra Rezaee","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Kasra Rezaee","raw_affiliation_strings":["Noah\u2019s Ark Lab., Huawei Technologies, Markham, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noah\u2019s Ark Lab., Huawei Technologies, Markham, Ontario, Canada","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031841551","display_name":"Peyman Yadmellat","orcid":"https://orcid.org/0000-0001-9722-3873","observed_orcids":["https://orcid.org/0000-0001-9722-3873"]},"institutions":[{"id":"https://openalex.org/I4210115038","display_name":"Huawei Technologies (Canada)","ror":"https://ror.org/026venb53","country_code":"CA","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210115038"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Peyman Yadmellat","raw_affiliation_strings":["Noah\u2019s Ark Lab., Huawei Technologies, Markham, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noah\u2019s Ark Lab., Huawei Technologies, Markham, Ontario, Canada","institution_ids":["https://openalex.org/I4210115038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079514022","display_name":"Simon Chamorro","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135117807","display_name":"Universit\u00e9 de Sherbrooke","ror":"https://ror.org/00kybxq39","country_code":"CA","type":"education","lineage":["https://openalex.org/I135117807"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Simon Chamorro","raw_affiliation_strings":["Universit\u00e9 de Sherbrooke, Sherbrooke, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Sherbrooke, Sherbrooke, Quebec, Canada","institution_ids":["https://openalex.org/I135117807"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8803,"has_fulltext":true,"cited_by_count":27,"citation_normalized_percentile":{"value":0.88866506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3506","last_page":"3511"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6563000082969666,"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":0.6563000082969666,"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":0.33009999990463257,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.005200000014156103,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/motion-planning","display_name":"motion planning","score":0.9490000009536743},{"id":"https://openalex.org/keywords/autonomous-vehicles","display_name":"autonomous vehicles","score":0.9139999747276306},{"id":"https://openalex.org/keywords/uncertainty","display_name":"uncertainty","score":0.6380000114440918},{"id":"https://openalex.org/keywords/distributional-reinforcement-learning","display_name":"distributional reinforcement learning","score":0.753000020980835},{"id":"https://openalex.org/keywords/worst-case-optimization","display_name":"worst-case optimization","score":0.9039999842643738},{"id":"https://openalex.org/keywords/occlusion","display_name":"occlusion","score":0.8820000290870667},{"id":"https://openalex.org/keywords/sensing-range","display_name":"sensing range","score":0.6060000061988831},{"id":"https://openalex.org/keywords/limited-field-of-view","display_name":"limited field of view","score":0.8849999904632568},{"id":"https://openalex.org/keywords/soft-actor-critic","display_name":"soft actor-critic","score":0.7960000038146973},{"id":"https://openalex.org/keywords/deep-q-network","display_name":"deep Q-network","score":0.8529999852180481},{"id":"https://openalex.org/keywords/pedestrian-crossings","display_name":"pedestrian crossings","score":0.7829999923706055},{"id":"https://openalex.org/keywords/curved-roads","display_name":"road curves","score":0.8230000138282776},{"id":"https://openalex.org/keywords/sumo-traffic-simulator","display_name":"SUMO traffic simulator","score":0.6140000224113464}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8176907896995544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085592746734619},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5812615156173706},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5371201038360596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101476311683655},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5072721838951111},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48304492235183716},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.47540077567100525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.347150981426239},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3288322389125824},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.14739102125167847},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13665717840194702},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.136508047580719},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.10821777582168579},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iros51168.2021.9636480","doi":"https://doi.org/10.1109/iros51168.2021.9636480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros51168.2021.9636480","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2110.00640","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.00640","pdf_url":"https://arxiv.org/pdf/2110.00640","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2110.00640","doi":"https://doi.org/10.48550/arxiv.2110.00640","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2110.00640","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2110.00640","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2110.00640","pdf_url":"https://arxiv.org/pdf/2110.00640","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3203124669.pdf","grobid_xml":"https://content.openalex.org/works/W3203124669.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1581437610","https://openalex.org/W2107338474","https://openalex.org/W2121863487","https://openalex.org/W2342840547","https://openalex.org/W2343568200","https://openalex.org/W2765302304","https://openalex.org/W2781726626","https://openalex.org/W2803308811","https://openalex.org/W2810677299","https://openalex.org/W2903709398","https://openalex.org/W2948153973","https://openalex.org/W2949795681","https://openalex.org/W2963082979","https://openalex.org/W2963757175","https://openalex.org/W2968628392","https://openalex.org/W2969903565","https://openalex.org/W2991419354","https://openalex.org/W2998059334","https://openalex.org/W3003533476","https://openalex.org/W3004270765","https://openalex.org/W3015082424","https://openalex.org/W3162902207"],"related_works":["https://openalex.org/W4409795819","https://openalex.org/W4406736092","https://openalex.org/W4413967028","https://openalex.org/W7223093706","https://openalex.org/W4400727489","https://openalex.org/W3131356842","https://openalex.org/W7125922218","https://openalex.org/W7162543200","https://openalex.org/W4285278949","https://openalex.org/W3135875965"],"abstract_inverted_index":{"Motion":[0],"planning":[1,66,203],"under":[2],"uncertainty":[3,22,89],"is":[4,40,99,118,152,165,187],"one":[5],"of":[6,32,122,144,171,183],"the":[7,21,53,93,106,111,123,131,150,192],"main":[8],"challenges":[9],"in":[10,23,48,64,100],"developing":[11],"autonomous":[12],"driving":[13,215],"vehicles.":[14],"In":[15],"this":[16,61],"work,":[17],"we":[18],"focus":[19],"on":[20,120],"sensing":[24,36,54],"and":[25,35,67,161,176,189,210],"perception,":[26],"resulted":[27],"from":[28],"a":[29,81,142,148,180],"limited":[30,181],"field":[31,182],"view,":[33],"occlusions,":[34],"range.":[37],"This":[38,97,136],"problem":[39],"often":[41],"tackled":[42],"by":[43,90],"considering":[44],"hypothetical":[45,73],"hidden":[46],"objects":[47,74],"occluded":[49],"areas":[50],"or":[51],"beyond":[52],"range":[55,143],"to":[56,76,87,102,109,141,154,206,213],"guarantee":[57],"passive":[58],"safety.":[59],"However,":[60],"may":[62],"result":[63],"conservative":[65],"expensive":[68],"computation,":[69],"particularly":[70],"when":[71],"numerous":[72],"need":[75],"be":[77,139],"considered.":[78],"We":[79],"propose":[80],"reinforcement":[82],"learning":[83],"(RL)":[84],"based":[85],"solution":[86],"manage":[88],"optimizing":[91],"for":[92],"worst":[94],"case":[95],"outcome.":[96],"approach":[98,117,151,164,198],"contrast":[101],"traditional":[103],"RL,":[104],"where":[105],"agents":[107],"try":[108],"maximize":[110],"average":[112],"expected":[113],"reward.":[114],"The":[115,163,185,196],"proposed":[116,197],"built":[119],"top":[121],"Distributional":[124],"RL":[125,145,157,208],"with":[126,174,179],"its":[127],"policy":[128],"optimization":[129],"maximizing":[130],"stochastic":[132],"outcomes\u2019":[133],"lower":[134],"bound.":[135],"modification":[137],"can":[138],"applied":[140,153],"algorithms.":[146],"As":[147],"proof-of-concept,":[149],"two":[155,168],"different":[156],"algorithms,":[158],"Soft":[159],"Actor-Critic":[160],"DQN.":[162],"evaluated":[166,190],"against":[167],"challenging":[169],"scenarios":[170],"pedestrians":[172],"crossing":[173],"occlusion":[175],"curved":[177],"roads":[178],"view.":[184],"algorithm":[186],"trained":[188],"using":[191],"SUMO":[193],"traffic":[194],"simulator.":[195],"yields":[199],"much":[200],"better":[201],"motion":[202],"behavior":[204],"compared":[205],"conventional":[207],"algorithms":[209],"behaves":[211],"comparably":[212],"humans":[214],"style.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2021-10-11T00:00:00"}