{"id":"https://openalex.org/W2624935640","doi":"https://doi.org/10.1109/ivs.2017.7995724","title":"Classification of drivers manoeuvre for road intersection crossing with synthethic and real data","display_name":"Classification of drivers manoeuvre for road intersection crossing with synthethic and real data","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2624935640","doi":"https://doi.org/10.1109/ivs.2017.7995724","mag":"2624935640"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2017.7995724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5016849500","display_name":"Mathieu Barbier","orcid":"https://orcid.org/0000-0002-5154-2163"},"institutions":[{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1301102746","display_name":"Renault (France)","ror":"https://ror.org/04v98kq37","country_code":"FR","type":"company","lineage":["https://openalex.org/I1301102746"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Mathieu Barbier","raw_affiliation_strings":["Inria Grenoble Rh\u00f4ne-Alpes, Montbonnot-Saint-Martin, France","Renault S.A.S, Guyancourt, France"],"affiliations":[{"raw_affiliation_string":"Inria Grenoble Rh\u00f4ne-Alpes, Montbonnot-Saint-Martin, France","institution_ids":["https://openalex.org/I4210101348","https://openalex.org/I899635006"]},{"raw_affiliation_string":"Renault S.A.S, Guyancourt, France","institution_ids":["https://openalex.org/I1301102746"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109557660","display_name":"Christian Laugier","orcid":null},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Christian Laugier","raw_affiliation_strings":["Inria Grenoble Rh\u00f4ne-Alpes, Montbonnot-Saint-Martin, France"],"affiliations":[{"raw_affiliation_string":"Inria Grenoble Rh\u00f4ne-Alpes, Montbonnot-Saint-Martin, France","institution_ids":["https://openalex.org/I4210101348","https://openalex.org/I899635006"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103157757","display_name":"Olivier Simonin","orcid":"https://orcid.org/0000-0002-3070-7790"},"institutions":[{"id":"https://openalex.org/I48430043","display_name":"Institut National des Sciences Appliqu\u00e9es de Lyon","ror":"https://ror.org/050jn9y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I203339264","https://openalex.org/I48430043"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier Simonin","raw_affiliation_strings":["INSA Lyon, CITI Lab., France"],"affiliations":[{"raw_affiliation_string":"INSA Lyon, CITI Lab., France","institution_ids":["https://openalex.org/I48430043"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029347872","display_name":"Javier Iba\u00f1ez\u2010Guzm\u00e1n","orcid":"https://orcid.org/0000-0002-5300-9709"},"institutions":[{"id":"https://openalex.org/I1301102746","display_name":"Renault (France)","ror":"https://ror.org/04v98kq37","country_code":"FR","type":"company","lineage":["https://openalex.org/I1301102746"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Javier Ibanez-Guzman","raw_affiliation_strings":["Renault S.A.S, Guyancourt, France"],"affiliations":[{"raw_affiliation_string":"Renault S.A.S, Guyancourt, France","institution_ids":["https://openalex.org/I1301102746"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016849500"],"corresponding_institution_ids":["https://openalex.org/I1301102746","https://openalex.org/I4210101348","https://openalex.org/I899635006"],"apc_list":null,"apc_paid":null,"fwci":1.053,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.80081668,"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":"224","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9986000061035156,"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":0.9986000061035156,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9764000177383423,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/intersection","display_name":"Intersection (aeronautics)","score":0.8962269425392151},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.6757009029388428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6325100660324097},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5758675336837769},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.563837468624115},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.555137574672699},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5497164130210876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5038110613822937},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4661864936351776},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46306294202804565},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4536626935005188},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3991646468639374},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2033098042011261},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17415758967399597},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.09420967102050781}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.8962269425392151},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.6757009029388428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6325100660324097},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5758675336837769},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.563837468624115},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.555137574672699},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5497164130210876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5038110613822937},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4661864936351776},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46306294202804565},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4536626935005188},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3991646468639374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2033098042011261},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17415758967399597},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.09420967102050781},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2017.7995724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.46000000834465027,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2084246939","https://openalex.org/W2097545165","https://openalex.org/W2101234009","https://openalex.org/W2128301427","https://openalex.org/W2160419726","https://openalex.org/W2167865917","https://openalex.org/W2531184939","https://openalex.org/W2562824155","https://openalex.org/W2563101006","https://openalex.org/W2911964244","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2006251942","https://openalex.org/W2364741597","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W1492103595","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W1864774435","https://openalex.org/W2913146933","https://openalex.org/W946352265"],"abstract_inverted_index":{"When":[0],"approaching":[1,156],"a":[2,95,105],"road":[3],"intersection,":[4,79],"drivers":[5,26],"consider":[6],"several":[7],"factors":[8],"and":[9,43,58,108,181,190,198,213],"choose":[10],"amongst":[11],"different":[12],"likely":[13],"manoeuvres.":[14,33],"For":[15],"an":[16,157],"autonomous":[17],"agent,":[18],"it":[19],"is":[20,70,102,127,206],"fundamental":[21],"to":[22,53,59,129,150,178,221],"understand":[23],"what":[24],"other":[25,89,179],"are":[27,35,142],"doing":[28],"before":[29],"deciding":[30],"their":[31],"own":[32],"These":[34],"seldom":[36],"be":[37,51],"the":[38,44,71,83,88,119,131,152,163,169,188,191,194,209],"same":[39],"as":[40,166,168],"intersections":[41],"differ":[42],"situations":[45],"too.":[46],"Whilst,":[47],"learning":[48],"techniques":[49],"can":[50,161],"used":[52,128,143],"process":[54,73],"features":[55,135],"of":[56,62,74,82,87,134,154,193,203],"trajectories":[57,153],"predict":[60],"manoeuvres":[61],"others":[63],"cars.":[64],"The":[65,159],"problem":[66],"with":[67,110,146,208,219],"such":[68],"approaches":[69],"difficult":[72],"recording":[75],"data":[76,97,112,211],"for":[77,136],"each":[78,137],"not":[80],"only":[81],"subject":[84],"vehicle":[85],"but":[86],"vehicles.":[90],"To":[91,121],"address":[92],"this":[93],"problem,":[94],"hybrid":[96,210],"set":[98],"was":[99],"constructed.":[100],"It":[101],"built":[103],"in":[104,144],"simulated":[106,197],"environment":[107],"completed":[109],"real":[111,199],"after":[113],"has":[114],"driven":[115],"multiple":[116],"times":[117],"across":[118],"intersection.":[120,158],"analyze":[122,151],"these":[123],"data,":[124],"classification":[125],"technique":[126],"find":[130],"common":[132],"range":[133],"manoeuvre.":[138],"Random":[139],"forest":[140],"classifiers":[141,160,180],"conjunction":[145],"our":[147,174,216],"functional":[148,217],"discretization":[149,218],"cars":[155],"determine":[162],"longitudinal":[164],"manoeuvre":[165],"well":[167],"direction.":[170],"We":[171],"show":[172],"how":[173],"approach":[175],"performs":[176],"compared":[177],"space":[182],"discretization.":[183],"In":[184],"addition,":[185],"we":[186],"demonstrate":[187],"impact":[189],"usefulness":[192],"mixture":[195],"between":[196],"data.":[200],"An":[201],"improvement":[202],"30%":[204],"accuracy":[205],"obtained":[207],"set,":[212],"5%":[214],"using":[215],"respect":[220],"baseline":[222],"approach.":[223]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}