{"id":"https://openalex.org/W4400644586","doi":"https://doi.org/10.1109/iv55156.2024.10588630","title":"Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention","display_name":"Towards Consistent and Explainable Motion Prediction using Heterogeneous Graph Attention","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400644586","doi":"https://doi.org/10.1109/iv55156.2024.10588630"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5047875711","display_name":"Tobias Demmler","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tobias Demmler","raw_affiliation_strings":["Robert Bosch GmbH,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH,Stuttgart,Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057181669","display_name":"Andreas Tamke","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Tamke","raw_affiliation_strings":["Robert Bosch GmbH,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH,Stuttgart,Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717722","display_name":"Thao Dang","orcid":"https://orcid.org/0000-0002-7629-3853"},"institutions":[{"id":"https://openalex.org/I134656947","display_name":"Esslingen University of Applied Sciences","ror":"https://ror.org/056cezx90","country_code":"DE","type":"education","lineage":["https://openalex.org/I134656947"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thao Dang","raw_affiliation_strings":["Esslingen University,Institute for Intelligent Systems,Department of Computer Science and Engineering,Germany"],"affiliations":[{"raw_affiliation_string":"Esslingen University,Institute for Intelligent Systems,Department of Computer Science and Engineering,Germany","institution_ids":["https://openalex.org/I134656947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045118146","display_name":"Karsten Haug","orcid":"https://orcid.org/0009-0005-7004-2876"},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karsten Haug","raw_affiliation_strings":["Robert Bosch GmbH,Stuttgart,Germany"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH,Stuttgart,Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026694402","display_name":"Lars Mikelsons","orcid":"https://orcid.org/0009-0005-9006-9726"},"institutions":[{"id":"https://openalex.org/I179225836","display_name":"University of Augsburg","ror":"https://ror.org/03p14d497","country_code":"DE","type":"education","lineage":["https://openalex.org/I179225836"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lars Mikelsons","raw_affiliation_strings":["University of Augsburg,Leads the Chair of Mechatronics,Germany"],"affiliations":[{"raw_affiliation_string":"University of Augsburg,Leads the Chair of Mechatronics,Germany","institution_ids":["https://openalex.org/I179225836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047875711"],"corresponding_institution_ids":["https://openalex.org/I889804353"],"apc_list":null,"apc_paid":null,"fwci":0.7661,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71588815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"168","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9812999963760376,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9812999963760376,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9649999737739563,"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/T10862","display_name":"AI in cancer detection","score":0.9620000123977661,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6890547275543213},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4964638352394104},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4535168707370758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44838806986808777},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.4178963303565979},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29920458793640137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15490174293518066},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.06833693385124207}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6890547275543213},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4964638352394104},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4535168707370758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44838806986808777},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4178963303565979},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29920458793640137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15490174293518066},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.06833693385124207}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.5199999809265137,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2955189650","https://openalex.org/W3028769608","https://openalex.org/W3034722190","https://openalex.org/W3108486966","https://openalex.org/W3187966659","https://openalex.org/W3196864007","https://openalex.org/W3209837334","https://openalex.org/W4212774754","https://openalex.org/W4231449374","https://openalex.org/W4297899246","https://openalex.org/W4297944254","https://openalex.org/W4383109074","https://openalex.org/W4383172002","https://openalex.org/W4384918448","https://openalex.org/W4386076672","https://openalex.org/W4390788068","https://openalex.org/W6769043036","https://openalex.org/W6778883912","https://openalex.org/W6779371077","https://openalex.org/W6782468546","https://openalex.org/W6797464607","https://openalex.org/W6801880476","https://openalex.org/W6803278392","https://openalex.org/W6843475265","https://openalex.org/W6843510756","https://openalex.org/W6854866820"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In":[0],"autonomous":[1],"driving,":[2],"accurately":[3],"interpreting":[4],"the":[5,26,73,84,97,103,116,121,172,176,188],"movements":[6],"of":[7,28,34,86,144],"other":[8],"road":[9],"users":[10],"and":[11,31,88,127,159],"leveraging":[12],"this":[13,40,180],"knowledge":[14],"to":[15,53,100,114],"forecast":[16],"future":[17,55],"trajectories":[18,33,90,99,118],"is":[19,22,50,91],"crucial.":[20],"This":[21,94,106,133],"typically":[23],"achieved":[24],"through":[25],"integration":[27],"map":[29,81],"data":[30],"tracked":[32],"various":[35],"agents.":[36],"Numerous":[37],"methodologies":[38],"combine":[39],"information":[41,71],"into":[42,140,187],"a":[43,61,109,141,149,163,195],"singular":[44],"embedding":[45],"for":[46],"each":[47],"agent,":[48],"which":[49],"then":[51],"utilized":[52],"predict":[54],"behavior.":[56],"However,":[57,83],"these":[58,125],"approaches":[59],"have":[60],"notable":[62],"drawback":[63],"in":[64,162,179],"that":[65,153],"they":[66],"may":[67],"lose":[68],"exact":[69],"location":[70],"during":[72],"encoding":[74,77],"process.":[75],"The":[76],"still":[78],"includes":[79],"general":[80],"information.":[82],"generation":[85],"valid":[87],"consistent":[89,131],"not":[92],"guaranteed.":[93],"can":[95,136,183],"cause":[96],"predicted":[98,117],"stray":[101],"from":[102],"actual":[104,122],"lanes.":[105],"paper":[107],"introduces":[108],"new":[110],"refinement":[111],"module":[112,135],"designed":[113],"project":[115],"back":[119],"onto":[120],"map,":[123],"rectifying":[124],"discrepancies":[126],"leading":[128,193],"towards":[129,194],"more":[130,196],"predictions.":[132],"versatile":[134],"be":[137],"readily":[138],"incorporated":[139],"wide":[142],"range":[143],"architectures.":[145],"Additionally,":[146],"we":[147,182],"propose":[148],"novel":[150],"scene":[151],"encoder":[152],"handles":[154],"all":[155],"relations":[156],"between":[157],"agents":[158],"their":[160],"environment":[161],"single":[164],"unified":[165],"heterogeneous":[166],"graph":[167],"attention":[168,173],"network.":[169],"By":[170],"analyzing":[171],"values":[174],"on":[175],"different":[177],"edges":[178],"graph,":[181],"gain":[184],"unique":[185],"insights":[186],"neural":[189],"network\u2019s":[190],"inner":[191],"workings":[192],"explainable":[197],"prediction.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}