{"id":"https://openalex.org/W2963625099","doi":"https://doi.org/10.1109/icra.2018.8461233","title":"Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning","display_name":"Navigating Occluded Intersections with Autonomous Vehicles Using Deep Reinforcement Learning","publication_year":2018,"publication_date":"2018-05-01","ids":{"openalex":"https://openalex.org/W2963625099","doi":"https://doi.org/10.1109/icra.2018.8461233","mag":"2963625099"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2018.8461233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8461233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Navigating_Occluded_Intersections_with_Autonomous_Vehicles_Using_Deep_Reinforcement_Learning/20582574","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063634505","display_name":"David Isele","orcid":"https://orcid.org/0000-0001-9749-6951"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David Isele","raw_affiliation_strings":["The University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"The University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020409722","display_name":"Reza Rahimi","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza Rahimi","raw_affiliation_strings":["The University of Virginia"],"affiliations":[{"raw_affiliation_string":"The University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028574557","display_name":"Akansel Cosgun","orcid":"https://orcid.org/0000-0003-4203-6477"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akansel Cosgun","raw_affiliation_strings":["Honda Research Institute"],"affiliations":[{"raw_affiliation_string":"Honda Research Institute","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kaushik Subramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Subramanian","raw_affiliation_strings":["The Georgia Institute of Technology"],"affiliations":[{"raw_affiliation_string":"The Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112249344","display_name":"Kikuo Fujimura","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kikuo Fujimura","raw_affiliation_strings":["Honda Research Institute"],"affiliations":[{"raw_affiliation_string":"Honda Research Institute","institution_ids":["https://openalex.org/I1283473643"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5063634505"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":25.8025,"has_fulltext":false,"cited_by_count":365,"citation_normalized_percentile":{"value":0.99803578,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2034","last_page":"2039"},"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":0.996399998664856,"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/T10370","display_name":"Traffic and Road Safety","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8996044397354126},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.8455830216407776},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7319462299346924},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.7312177419662476},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.697614312171936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6352617740631104},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5656759738922119},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5195612907409668},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46263521909713745},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3424980640411377},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1343824863433838},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.08911964297294617}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8996044397354126},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.8455830216407776},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7319462299346924},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.7312177419662476},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.697614312171936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6352617740631104},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5656759738922119},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5195612907409668},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46263521909713745},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3424980640411377},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1343824863433838},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.08911964297294617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icra.2018.8461233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2018.8461233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},{"id":"pmh:oai:figshare.com:article/20582574","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Navigating_Occluded_Intersections_with_Autonomous_Vehicles_Using_Deep_Reinforcement_Learning/20582574","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20582574","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Navigating_Occluded_Intersections_with_Autonomous_Vehicles_Using_Deep_Reinforcement_Learning/20582574","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W1498681823","https://openalex.org/W1869778509","https://openalex.org/W1965455100","https://openalex.org/W2010725166","https://openalex.org/W2017052912","https://openalex.org/W2055501135","https://openalex.org/W2073177254","https://openalex.org/W2092187344","https://openalex.org/W2171496510","https://openalex.org/W2178328776","https://openalex.org/W2201581102","https://openalex.org/W2243721295","https://openalex.org/W2291973609","https://openalex.org/W2342840547","https://openalex.org/W2344396459","https://openalex.org/W2402106645","https://openalex.org/W2406067508","https://openalex.org/W2951799221","https://openalex.org/W2962901581","https://openalex.org/W2963454359","https://openalex.org/W2963575966","https://openalex.org/W2964048876","https://openalex.org/W4237036536","https://openalex.org/W4298392598","https://openalex.org/W4298857966","https://openalex.org/W4299851364","https://openalex.org/W4301501993","https://openalex.org/W6639086533","https://openalex.org/W6737199497","https://openalex.org/W6743563064","https://openalex.org/W6746542636","https://openalex.org/W6748613090","https://openalex.org/W6818721677"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W1977169298","https://openalex.org/W2371953206","https://openalex.org/W2382500641","https://openalex.org/W4230797523","https://openalex.org/W2801497733"],"abstract_inverted_index":{"Providing":[0],"an":[1],"efficient":[2],"strategy":[3],"to":[4,30,43,70,78,83,126],"navigate":[5],"safely":[6,86],"through":[7],"unsignaled":[8],"intersections":[9],"is":[10],"a":[11,51,75],"difficult":[12],"task":[13,59],"that":[14,46],"requires":[15],"determining":[16],"the":[17,24,48,88,97,101,105,116],"intent":[18],"of":[19,26,50,90,111,118],"other":[20],"drivers.":[21],"We":[22,72],"explore":[23,74],"effectiveness":[25],"Deep":[27,38],"Reinforcement":[28],"Learning":[29],"handle":[31],"intersection":[32,98],"problems.":[33],"Using":[34],"recent":[35],"advances":[36],"in":[37,55,87],"RL,":[39],"we":[40],"are":[41],"able":[42],"learn":[44,79],"policies":[45],"surpass":[47],"performance":[49],"commonly-used":[52],"heuristic":[53],"approach":[54],"several":[56,109],"metrics":[57],"including":[58],"completion":[60],"time":[61],"and":[62,66,115],"goal":[63],"success":[64],"rate":[65],"have":[67],"limited":[68],"ability":[69,77],"generalize.":[71],"then":[73],"system's":[76],"active":[80],"sensing":[81],"behaviors":[82],"enable":[84],"navigating":[85],"case":[89],"occlusions.":[91],"Our":[92],"analysis,":[93],"provides":[94],"insight":[95],"into":[96],"handling":[99],"problem,":[100],"solutions":[102],"learned":[103],"by":[104],"network":[106],"point":[107,125],"out":[108],"shortcomings":[110],"current":[112,120],"rule-based":[113],"methods,":[114],"failures":[117],"our":[119],"deep":[121],"reinforcement":[122],"learning":[123],"system":[124],"future":[127],"research":[128],"directions.":[129]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":45},{"year":2023,"cited_by_count":47},{"year":2022,"cited_by_count":68},{"year":2021,"cited_by_count":63},{"year":2020,"cited_by_count":62},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":3}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}