{"id":"https://openalex.org/W2084835622","doi":"https://doi.org/10.1109/ivs.2012.6232277","title":"Probabilistic trajectory prediction with Gaussian mixture models","display_name":"Probabilistic trajectory prediction with Gaussian mixture models","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2084835622","doi":"https://doi.org/10.1109/ivs.2012.6232277","mag":"2084835622"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2012.6232277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2012.6232277","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Intelligent Vehicles Symposium","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/A5068309008","display_name":"J\u00fcrgen Wiest","orcid":null},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jurgen Wiest","raw_affiliation_strings":["Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]"],"affiliations":[{"raw_affiliation_string":"Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","institution_ids":[]},{"raw_affiliation_string":"[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019884869","display_name":"Matthias H\u00f6ffken","orcid":null},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Hoffken","raw_affiliation_strings":["Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]"],"affiliations":[{"raw_affiliation_string":"Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","institution_ids":[]},{"raw_affiliation_string":"[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069787575","display_name":"Ulrich Kresel","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ulrich Kresel","raw_affiliation_strings":["[Daimler AG, Ulm, Germany]"],"affiliations":[{"raw_affiliation_string":"[Daimler AG, Ulm, Germany]","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085054529","display_name":"Klaus Dietmayer","orcid":"https://orcid.org/0000-0002-1651-014X"},"institutions":[{"id":"https://openalex.org/I196349391","display_name":"Universit\u00e4t Ulm","ror":"https://ror.org/032000t02","country_code":"DE","type":"education","lineage":["https://openalex.org/I196349391"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Dietmayer","raw_affiliation_strings":["Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]"],"affiliations":[{"raw_affiliation_string":"Institute of Measurement Control an Microtechnology Ulm University, Ulm, Germany","institution_ids":[]},{"raw_affiliation_string":"[Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany]","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068309008"],"corresponding_institution_ids":["https://openalex.org/I196349391"],"apc_list":null,"apc_paid":null,"fwci":14.7386,"has_fulltext":false,"cited_by_count":341,"citation_normalized_percentile":{"value":0.99010769,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"141","last_page":"146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9939000010490417,"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":0.9939000010490417,"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/T10370","display_name":"Traffic and Road Safety","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T12759","display_name":"Vehicle Noise and Vibration Control","score":0.9817000031471252,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8613743782043457},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.733241081237793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6729835271835327},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6242308616638184},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5930625200271606},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5726247429847717},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.49412801861763},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.49370965361595154},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46769097447395325},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4552435278892517},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4169633388519287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.389138400554657},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21777033805847168},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15811088681221008}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8613743782043457},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.733241081237793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6729835271835327},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6242308616638184},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5930625200271606},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5726247429847717},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.49412801861763},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.49370965361595154},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46769097447395325},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4552435278892517},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4169633388519287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.389138400554657},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21777033805847168},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15811088681221008},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2012.6232277","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2012.6232277","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Intelligent Vehicles Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W78101415","https://openalex.org/W152912987","https://openalex.org/W1506806321","https://openalex.org/W1579925870","https://openalex.org/W1738124305","https://openalex.org/W1973166425","https://openalex.org/W2037629065","https://openalex.org/W2049633694","https://openalex.org/W2120211304","https://openalex.org/W2123665586","https://openalex.org/W2126413547","https://openalex.org/W2139391802","https://openalex.org/W2148238513","https://openalex.org/W2213928808","https://openalex.org/W6603204851","https://openalex.org/W6678680539","https://openalex.org/W6682028543"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W1964286703","https://openalex.org/W2169866437"],"abstract_inverted_index":{"In":[0,44],"the":[1,12,24,31,57,61,68,101,104,109,118,123,136,147,150,154,164,171,174],"context":[2],"of":[3,11,26,117,149,156,163,173],"driver":[4],"assistance,":[5],"an":[6,161],"accurate":[7],"and":[8,139],"reliable":[9],"prediction":[10,52,142],"vehicle's":[13,62],"trajectory":[14,51,63,95],"is":[15,53,121,125],"beneficial.":[16],"This":[17],"can":[18,96,143,166],"be":[19,97,144,167],"useful":[20],"either":[21],"to":[22,35,59,82,169],"increase":[23],"flexibility":[25],"comfort":[27],"systems":[28],"or,":[29],"in":[30,66],"more":[32],"interesting":[33],"case,":[34],"detect":[36],"potentially":[37],"dangerous":[38],"situations":[39],"as":[40,42,88],"early":[41],"possible.":[43],"this":[45,92,157],"contribution,":[46],"a":[47,84,94,128,132,140],"novel":[48],"approach":[49],"for":[50,103],"proposed":[54],"which":[55],"has":[56],"capability":[58],"predict":[60],"several":[64],"seconds":[65],"advance,":[67],"so":[69],"called":[70],"long-term":[71],"prediction.":[72,175],"To":[73],"achieve":[74],"this,":[75],"previously":[76],"observed":[77,111],"motion":[78,89,113],"patterns":[79],"are":[80],"used":[81,168],"infer":[83],"joint":[85],"probability":[86,102],"distribution":[87,134],"model.":[90],"Using":[91],"distribution,":[93],"predicted":[98],"by":[99,146],"calculating":[100],"future":[105,137],"motion,":[106],"conditioned":[107,158],"on":[108],"current":[110],"history":[112],"pattern.":[114],"The":[115],"advantage":[116],"probabilistic":[119],"modeling":[120],"that":[122],"result":[124],"not":[126],"only":[127],"prediction,":[129],"but":[130],"rather":[131],"whole":[133],"over":[135],"trajectories":[138],"specific":[141],"made":[145],"evaluation":[148,162],"statistical":[151],"properties,":[152],"e.g.":[153],"mean":[155],"distribution.":[159],"Additionally,":[160],"variance":[165],"examine":[170],"reliability":[172]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":45},{"year":2021,"cited_by_count":48},{"year":2020,"cited_by_count":49},{"year":2019,"cited_by_count":36},{"year":2018,"cited_by_count":26},{"year":2017,"cited_by_count":18},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":8}],"updated_date":"2026-04-04T08:04:53.788161","created_date":"2025-10-10T00:00:00"}