{"id":"https://openalex.org/W2515486452","doi":"https://doi.org/10.1109/ivs.2016.7535466","title":"Human-like planning of swerve maneuvers for autonomous vehicles","display_name":"Human-like planning of swerve maneuvers for autonomous vehicles","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2515486452","doi":"https://doi.org/10.1109/ivs.2016.7535466","mag":"2515486452"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2016.7535466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 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/A5101573151","display_name":"Tianyu Gu","orcid":"https://orcid.org/0009-0004-7761-0357"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianyu Gu","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015076162","display_name":"John M. Dolan","orcid":"https://orcid.org/0000-0003-2062-100X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John M. Dolan","raw_affiliation_strings":["Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100406464","display_name":"Jin-Woo Lee","orcid":"https://orcid.org/0000-0002-5458-2697"},"institutions":[{"id":"https://openalex.org/I118136607","display_name":"General Motors (United States)","ror":"https://ror.org/05addee68","country_code":"US","type":"company","lineage":["https://openalex.org/I118136607"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin-Woo Lee","raw_affiliation_strings":["Research & Development, General Motors, Warren, MI, USA"],"affiliations":[{"raw_affiliation_string":"Research & Development, General Motors, Warren, MI, USA","institution_ids":["https://openalex.org/I118136607"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101573151"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.8137,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.87097693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"716","last_page":"721"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9930999875068665,"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/planner","display_name":"Planner","score":0.8328157067298889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6409054398536682},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6118896007537842},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5456356406211853},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5373313426971436},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.5185254812240601},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.5098220705986023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.482781320810318},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45379555225372314},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4198175072669983},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.39107683300971985},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.33146941661834717},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10577172040939331}],"concepts":[{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.8328157067298889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6409054398536682},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6118896007537842},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5456356406211853},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5373313426971436},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.5185254812240601},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.5098220705986023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.482781320810318},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45379555225372314},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4198175072669983},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.39107683300971985},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33146941661834717},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10577172040939331},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2016.7535466","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2016.7535466","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1976201601","https://openalex.org/W1976206117","https://openalex.org/W2066779729","https://openalex.org/W2082764616","https://openalex.org/W2084616221","https://openalex.org/W2104532622","https://openalex.org/W2134765105","https://openalex.org/W2138294955","https://openalex.org/W2144293566","https://openalex.org/W2145339207","https://openalex.org/W2148361676","https://openalex.org/W2149211351","https://openalex.org/W2154844948","https://openalex.org/W2262174858","https://openalex.org/W2293883387","https://openalex.org/W2406067508","https://openalex.org/W6692894317"],"related_works":["https://openalex.org/W804484174","https://openalex.org/W1568779110","https://openalex.org/W4244698559","https://openalex.org/W4246538999","https://openalex.org/W2002361198","https://openalex.org/W56933075","https://openalex.org/W2168364913","https://openalex.org/W1548568597","https://openalex.org/W2482749251","https://openalex.org/W2114119680"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,57],"develop":[4],"a":[5,24,39,89,113],"motion":[6],"planner":[7,82],"for":[8],"on-road":[9],"autonomous":[10],"swerve":[11,81,116],"maneuvers":[12],"that":[13,28,78],"is":[14],"capable":[15],"of":[16,92,102],"learning":[17,62,85],"passengers'":[18],"individual":[19,54],"driving":[20,55,67],"styles.":[21],"It":[22],"uses":[23],"hybrid":[25],"planning":[26],"approach":[27],"combines":[29],"sampling-based":[30],"graph":[31],"search":[32],"and":[33,83],"vehicle":[34],"model-based":[35],"evaluation":[36],"to":[37,52,64,97,111],"obtain":[38,112],"smooth":[40],"trajectory":[41],"plan.":[42],"To":[43],"automate":[44],"the":[45,79,98],"parameter":[46],"tuning":[47],"process,":[48],"as":[49,51],"well":[50],"reflect":[53],"styles,":[56],"further":[58],"adapt":[59],"inverse":[60],"reinforcement":[61],"techniques":[63],"distill":[65],"human":[66,103],"patterns":[68],"from":[69,73],"maneuver":[70,93],"demonstrations":[71],"collected":[72],"different":[74],"individuals.":[75],"We":[76],"found":[77],"proposed":[80],"its":[84],"routine":[86],"can":[87],"approximate":[88],"good":[90],"variety":[91],"demonstrations.":[94],"However,":[95],"due":[96],"underlying":[99],"stochastic":[100],"nature":[101],"driving,":[104],"more":[105,114],"data":[106],"are":[107],"needed":[108],"in":[109],"order":[110],"generative":[115],"model.":[117]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}