{"id":"https://openalex.org/W2952102303","doi":"https://doi.org/10.1109/itsc.2018.8569913","title":"Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications","display_name":"Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2952102303","doi":"https://doi.org/10.1109/itsc.2018.8569913","mag":"2952102303"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2018.8569913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1809.06394","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045265475","display_name":"Boyang Wang","orcid":"https://orcid.org/0000-0003-3613-8792"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Boyang Wang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100665612","display_name":"Jianwei Gong","orcid":"https://orcid.org/0000-0003-4651-8473"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Gong","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078091606","display_name":"Ruizeng Zhang","orcid":"https://orcid.org/0009-0008-9236-8975"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizeng Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010335898","display_name":"Huiyan Chen","orcid":"https://orcid.org/0009-0003-7464-3906"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyan Chen","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045265475"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.748,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.76431265,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1408","last_page":"1414"},"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994000196456909,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8089052438735962},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6806267499923706},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6439675688743591},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6157620549201965},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6063250303268433},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.545966625213623},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46099284291267395},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44751429557800293},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.43449151515960693},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.43191972374916077},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.41654422879219055},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.24518191814422607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8089052438735962},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6806267499923706},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6439675688743591},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6157620549201965},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6063250303268433},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.545966625213623},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46099284291267395},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44751429557800293},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.43449151515960693},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.43191972374916077},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.41654422879219055},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.24518191814422607},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/itsc.2018.8569913","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2018.8569913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1809.06394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.06394","pdf_url":"https://arxiv.org/pdf/1809.06394","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"pmh:oai:HAL:lirmm-02520197v1","is_oa":false,"landing_page_url":"https://hal-lirmm.ccsd.cnrs.fr/lirmm-02520197","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ITSC 2018 - 21st International Conference on Intelligent Transportation Systems, Nov 2018, Maui, Hi, United States. pp.1408-1414, &#x27E8;10.1109/ITSC.2018.8569913&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1809.06394","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1809.06394","pdf_url":"https://arxiv.org/pdf/1809.06394","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W650480612","https://openalex.org/W1986014385","https://openalex.org/W2012204020","https://openalex.org/W2012392077","https://openalex.org/W2012561930","https://openalex.org/W2110304639","https://openalex.org/W2115739375","https://openalex.org/W2116165149","https://openalex.org/W2121806728","https://openalex.org/W2136719407","https://openalex.org/W2163411428","https://openalex.org/W2167117957","https://openalex.org/W2174602916","https://openalex.org/W2199215277","https://openalex.org/W2306644740","https://openalex.org/W2330918716","https://openalex.org/W2406067508","https://openalex.org/W2467828995","https://openalex.org/W2473723854","https://openalex.org/W2508541768","https://openalex.org/W2528158400","https://openalex.org/W2554310451","https://openalex.org/W2745090846","https://openalex.org/W2789699693","https://openalex.org/W4297888977","https://openalex.org/W6653435097"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674"],"abstract_inverted_index":{"Developing":[0],"an":[1,74],"intelligent":[2,181],"vehicle":[3,182],"which":[4,41],"can":[5,132,191],"perform":[6],"human-like":[7],"actions":[8],"requires":[9],"the":[10,34,43,50,81,93,101,105,113,124,134,138,141,149,152,171,176,188,193,198],"ability":[11],"to":[12,56,156],"learn":[13],"basic":[14],"driving":[15,23,36,47,172],"skills":[16],"from":[17,175],"a":[18,62,69,86],"large":[19],"amount":[20],"of":[21,46,52,64,88,109,136,151,179],"naturalistic":[22],"data.":[24],"The":[25,97,163,184],"algorithms":[26],"will":[27],"become":[28],"efficient":[29],"if":[30],"we":[31,131],"could":[32],"decompose":[33],"complex":[35],"tasks":[37],"into":[38,61],"motion":[39,65,89,110,142,160,199],"primitives":[40,90,111],"represent":[42],"elementary":[44],"compositions":[45],"skills.":[48],"Therefore,":[49],"purpose":[51],"this":[53,120,127],"paper":[54,128],"is":[55,165],"segment":[57],"unlabeled":[58],"trajectory":[59],"data":[60,173],"library":[63,144,201],"primitives.":[66,96],"By":[67,118],"applying":[68],"probabilistic":[70],"inference":[71],"based":[72,115],"on":[73],"iterative":[75],"Expectation-Maximization":[76],"algorithm,":[77],"our":[78],"method":[79,99,155],"segments":[80],"collected":[82,174],"trajectories":[83],"while":[84],"learning":[85,158],"set":[87],"represented":[91],"by":[92,169],"dynamic":[94],"movement":[95],"proposed":[98,189],"utilizes":[100],"mutual":[102,121],"dependencies":[103],"between":[104],"segmentation":[106,139,195],"and":[107,112,123,140,159,167,196],"representation":[108,154],"driving-specific":[114],"initial":[116,125],"segmentation.":[117],"utilizing":[119],"dependency":[122],"condition,":[126],"presents":[129],"how":[130],"enhance":[133],"performance":[135],"both":[137],"primitive":[143,153,200],"establishment.":[145],"We":[146],"also":[147],"evaluate":[148],"applicability":[150],"imitation":[157],"planning":[161],"algorithms.":[162],"model":[164],"trained":[166],"validated":[168],"using":[170],"Beijing":[177],"Institute":[178],"Technology":[180],"platform.":[183],"results":[185],"show":[186],"that":[187],"approach":[190],"find":[192],"proper":[194],"establish":[197],"simultaneously.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-06-27T00:00:00"}
