{"id":"https://openalex.org/W2155263026","doi":"https://doi.org/10.1109/itsc.2011.6082996","title":"Hierarchical road understanding for intelligent vehicles based on sensor fusion","display_name":"Hierarchical road understanding for intelligent vehicles based on sensor fusion","publication_year":2011,"publication_date":"2011-10-01","ids":{"openalex":"https://openalex.org/W2155263026","doi":"https://doi.org/10.1109/itsc.2011.6082996","mag":"2155263026"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2011.6082996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2011.6082996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","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/A5008333736","display_name":"Chunzhao Guo","orcid":"https://orcid.org/0000-0002-2992-6320"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Chunzhao Guo","raw_affiliation_strings":["Toyota Technological Institute, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112282385","display_name":"Seiichi Mita","orcid":null},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Seiichi Mita","raw_affiliation_strings":["Toyota Technological Institute, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033089246","display_name":"David McAllester","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David McAllester","raw_affiliation_strings":["Toyota Technological Institute, Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I160992636"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008333736"],"corresponding_institution_ids":["https://openalex.org/I4840577"],"apc_list":null,"apc_paid":null,"fwci":1.0303,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81122417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1672","last_page":"1679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965999722480774,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9948999881744385,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/obstacle","display_name":"Obstacle","score":0.7500183582305908},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7084602117538452},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6421096920967102},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.6115226745605469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5877841114997864},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5109040141105652},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5078745484352112},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.47031036019325256},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4616573750972748},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45045074820518494},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41660356521606445},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17110449075698853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.16358891129493713},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11024865508079529},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.07810553908348083}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.7500183582305908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7084602117538452},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6421096920967102},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6115226745605469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5877841114997864},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5109040141105652},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5078745484352112},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.47031036019325256},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4616573750972748},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45045074820518494},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41660356521606445},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17110449075698853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.16358891129493713},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11024865508079529},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.07810553908348083},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2011.6082996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2011.6082996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320317941","display_name":"DENSO","ror":"https://ror.org/04hkpfa76"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1999478155","https://openalex.org/W2026328692","https://openalex.org/W2036989445","https://openalex.org/W2051610568","https://openalex.org/W2114220616","https://openalex.org/W2115519229","https://openalex.org/W2132360065","https://openalex.org/W2136929315","https://openalex.org/W2140200866","https://openalex.org/W2150408100","https://openalex.org/W2154844948","https://openalex.org/W2157117066","https://openalex.org/W2160337655","https://openalex.org/W2168356304","https://openalex.org/W2171541387","https://openalex.org/W2505763307","https://openalex.org/W6724576086"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W4245435724","https://openalex.org/W1996530509","https://openalex.org/W3028317537","https://openalex.org/W2389515972","https://openalex.org/W2055301889","https://openalex.org/W1505959757","https://openalex.org/W2376554934","https://openalex.org/W2077790809","https://openalex.org/W2906246018"],"abstract_inverted_index":{"Comprehensive":[0],"situational":[1],"awareness":[2],"is":[3,88],"paramount":[4],"to":[5,33,94],"the":[6,15,34,38,60,67,70,73,77,91,107,114,120,149,151,171,175,178],"effectiveness":[7,176],"of":[8,14,40,50,98,119,124,153,177],"proprietary":[9],"navigational":[10],"and":[11,37,76,101,130,143,166,170],"higher-level":[12],"functions":[13],"intelligent":[16,29],"vehicles.":[17],"In":[18,80,110,148],"this":[19],"paper,":[20],"we":[21],"address":[22],"a":[23,96,135,163,167],"hierarchical":[24],"road":[25,35,61,158],"understanding":[26],"system":[27,48],"for":[28,106,113],"vehicles":[30],"with":[31,139],"respect":[32],"topography":[36],"existence":[39],"objects":[41,123],"based":[42],"on":[43],"sensor":[44,165],"fusion.":[45],"The":[46],"proposed":[47,179],"consists":[49],"three":[51],"modules":[52],"that":[53],"run":[54],"in":[55,90,117],"parallel.":[56],"Module":[57],"one":[58],"classifies":[59],"environment":[62],"into":[63],"four":[64],"categories,":[65],"i.e.":[66],"reachable":[68],"region,":[69,72],"drivable":[71],"obstacle":[74,92],"region":[75,93],"unknown":[78],"region.":[79],"module":[81,111],"two,":[82],"an":[83],"efficient":[84],"graph-based":[85],"clustering":[86],"algorithm":[87],"performed":[89],"generate":[95],"list":[97],"object":[99,115,137],"hypotheses,":[100],"their":[102],"characteristics":[103],"are":[104,132],"used":[105],"coarse":[108],"identification.":[109],"three,":[112],"hypotheses":[116],"front":[118],"vehicle,":[121],"particular":[122],"interest,":[125],"including":[126],"vehicles,":[127],"pedestrians,":[128],"motorcycles":[129],"bicycles,":[131],"identified":[133],"using":[134,145],"multi-class":[136],"detector":[138],"deformable":[140],"part-based":[141],"models,":[142],"tracked":[144],"particle":[146],"filters.":[147],"experiments,":[150],"data":[152],"various":[154],"typical":[155],"but":[156],"challenging":[157],"scenarios":[159],"were":[160],"acquired":[161],"by":[162],"Velodyne":[164],"monocular":[168],"camera,":[169],"results":[172],"have":[173],"demonstrated":[174],"system.":[180]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
