{"id":"https://openalex.org/W4286285611","doi":"https://doi.org/10.1109/iv51971.2022.9827207","title":"MEAT: Maneuver Extraction from Agent Trajectories","display_name":"MEAT: Maneuver Extraction from Agent Trajectories","publication_year":2022,"publication_date":"2022-06-05","ids":{"openalex":"https://openalex.org/W4286285611","doi":"https://doi.org/10.1109/iv51971.2022.9827207"},"language":"en","primary_location":{"id":"doi:10.1109/iv51971.2022.9827207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827207","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 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/A5012442384","display_name":"Julian Schmidt","orcid":"https://orcid.org/0000-0003-4944-4916"},"institutions":[{"id":"https://openalex.org/I1332474105","display_name":"Mercedes-Benz (Germany)","ror":"https://ror.org/055rn2a38","country_code":"DE","type":"company","lineage":["https://openalex.org/I1332474105"]},{"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":"Julian Schmidt","raw_affiliation_strings":["Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany","Ulm University, Institute of Measurement, Control and Microtechnology, Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany","institution_ids":["https://openalex.org/I1332474105"]},{"raw_affiliation_string":"Ulm University, Institute of Measurement, Control and Microtechnology, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025907983","display_name":"Julian Jordan","orcid":null},"institutions":[{"id":"https://openalex.org/I1332474105","display_name":"Mercedes-Benz (Germany)","ror":"https://ror.org/055rn2a38","country_code":"DE","type":"company","lineage":["https://openalex.org/I1332474105"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Julian Jordan","raw_affiliation_strings":["Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany","institution_ids":["https://openalex.org/I1332474105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063201508","display_name":"David Raba","orcid":"https://orcid.org/0000-0002-7393-3237"},"institutions":[{"id":"https://openalex.org/I1332474105","display_name":"Mercedes-Benz (Germany)","ror":"https://ror.org/055rn2a38","country_code":"DE","type":"company","lineage":["https://openalex.org/I1332474105"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Raba","raw_affiliation_strings":["Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany","institution_ids":["https://openalex.org/I1332474105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037645607","display_name":"Tobias Welz","orcid":null},"institutions":[{"id":"https://openalex.org/I1332474105","display_name":"Mercedes-Benz (Germany)","ror":"https://ror.org/055rn2a38","country_code":"DE","type":"company","lineage":["https://openalex.org/I1332474105"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Welz","raw_affiliation_strings":["Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Mercedes-Benz AG, R&#x0026;D,Stuttgart,Germany","institution_ids":["https://openalex.org/I1332474105"]}]},{"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"]},{"id":"https://openalex.org/I4210163522","display_name":"Technische Hochschule Ulm","ror":"https://ror.org/05e5kd476","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210163522"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Dietmayer","raw_affiliation_strings":["Ulm University, Institute of Measurement, Control and Microtechnology,Ulm,Germany","Ulm University, Institute of Measurement, Control and Microtechnology, Ulm, Germany"],"affiliations":[{"raw_affiliation_string":"Ulm University, Institute of Measurement, Control and Microtechnology,Ulm,Germany","institution_ids":["https://openalex.org/I196349391","https://openalex.org/I4210163522"]},{"raw_affiliation_string":"Ulm University, Institute of Measurement, Control and Microtechnology, Ulm, Germany","institution_ids":["https://openalex.org/I196349391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012442384"],"corresponding_institution_ids":["https://openalex.org/I1332474105","https://openalex.org/I196349391"],"apc_list":null,"apc_paid":null,"fwci":0.4328,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47028256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1810","last_page":"1816"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9909999966621399,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9675999879837036,"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/trajectory","display_name":"Trajectory","score":0.8728604316711426},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7896868586540222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.551962673664093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.503091037273407},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4757237732410431},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43031591176986694},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41969555616378784}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8728604316711426},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896868586540222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.551962673664093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.503091037273407},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4757237732410431},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43031591176986694},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41969555616378784},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv51971.2022.9827207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv51971.2022.9827207","pdf_url":null,"source":{"id":"https://openalex.org/S4363605370","display_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320307110","display_name":"Delta","ror":"https://ror.org/03g9c1e75"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2091281530","https://openalex.org/W2896642734","https://openalex.org/W2898900571","https://openalex.org/W2955189650","https://openalex.org/W2963195425","https://openalex.org/W2980087597","https://openalex.org/W2989506443","https://openalex.org/W3034722190","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3037058446","https://openalex.org/W3090232952","https://openalex.org/W3108486966","https://openalex.org/W3129935960","https://openalex.org/W3200533894","https://openalex.org/W3202707544","https://openalex.org/W3204875639","https://openalex.org/W4221140004","https://openalex.org/W4285102480","https://openalex.org/W6755864109","https://openalex.org/W6768870957","https://openalex.org/W6780503301","https://openalex.org/W6781231738","https://openalex.org/W6801880476","https://openalex.org/W6809893666"],"related_works":["https://openalex.org/W1941703695","https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W4248382324","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":{"Advances":[0],"in":[1,32,53],"learning-based":[2],"trajectory":[3,93,102],"prediction":[4,22,103,116],"are":[5],"enabled":[6],"by":[7],"large-scale":[8],"datasets.":[9,55],"However,":[10],"in-depth":[11],"analysis":[12,95,107],"of":[13,21,99,108,114],"such":[14,54],"datasets":[15,110],"is":[16,24,76,123],"limited.":[17],"Moreover,":[18],"the":[19,33,61,67,70,80,109,115,120],"evaluation":[20,98,113],"models":[23,117],"limited":[25],"to":[26,42,78],"metrics":[27],"averaged":[28],"over":[29],"all":[30],"samples":[31],"dataset.":[34],"We":[35],"propose":[36],"an":[37,106,112],"automated":[38],"methodology":[39,57],"that":[40],"allows":[41],"extract":[43],"maneuvers":[44,82],"(e.g.,":[45],"left":[46],"turn,":[47],"lane":[48,68],"change)":[49],"from":[50],"agent":[51,62,71,121],"trajectories":[52],"The":[56],"considers":[58],"information":[59,65],"about":[60,66],"dynamics":[63,122],"and":[64,96,111],"segments":[69],"traveled":[72],"along.":[73],"Although":[74],"it":[75],"possible":[77],"use":[79,89],"resulting":[81],"for":[83,91],"training":[84],"classification":[85],"networks,":[86],"we":[87],"exemplary":[88],"them":[90],"extensive":[92],"dataset":[94],"maneuver-specific":[97],"multiple":[100],"state-of-the-art":[101],"models.":[104],"Additionally,":[105],"based":[118],"on":[119],"provided.":[124]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
