{"id":"https://openalex.org/W2964396132","doi":null,"title":"Deep Kinematic Models for Physically Realistic Prediction of Vehicle Trajectories","display_name":"Deep Kinematic Models for Physically Realistic Prediction of Vehicle Trajectories","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2964396132","mag":"2964396132"},"language":"en","primary_location":{"id":"mag:2964396132","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1908.00219v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/1908.00219v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101059479","display_name":"Henggang Cui","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henggang Cui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102832143","display_name":"Thi Nguyen","orcid":"https://orcid.org/0000-0002-1215-3480","observed_orcids":["https://orcid.org/0000-0002-1215-3480"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thi Nguyen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-1215-3480","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007055093","display_name":"Fang\u2010Chieh Chou","orcid":"https://orcid.org/0000-0001-6535-0894","observed_orcids":["https://orcid.org/0000-0001-6535-0894"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang\u2010Chieh Chou","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6535-0894","affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Tsung-Han Lin","orcid":"https://orcid.org/0000-0003-0149-7621","observed_orcids":["https://orcid.org/0000-0003-0149-7621"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsung-Han Lin","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0149-7621","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055199976","display_name":"Jeff Schneider","orcid":"https://orcid.org/0000-0002-5080-9073","observed_orcids":["https://orcid.org/0000-0002-5080-9073"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeff Schneider","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-5080-9073","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063307502","display_name":"David Bradley","orcid":"https://orcid.org/0000-0002-7310-8990","observed_orcids":["https://orcid.org/0000-0002-7310-8990"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Bradley","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7310-8990","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5082498217","display_name":"Nemanja Djuric","orcid":"https://orcid.org/0000-0002-6502-7891","observed_orcids":["https://orcid.org/0000-0002-6502-7891"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nemanja Djuric","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-6502-7891","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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":0.9990000128746033,"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":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vehicle-trajectory-prediction","display_name":"vehicle trajectory prediction","score":0.9629999995231628},{"id":"https://openalex.org/keywords/kinematic-constraints","display_name":"kinematic constraints","score":0.7260000109672546},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.7360000014305115},{"id":"https://openalex.org/keywords/autonomous-vehicles","display_name":"autonomous vehicles","score":0.5490000247955322}],"concepts":[{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.7450871467590332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.69849693775177},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6459870934486389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6119838356971741},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5570980906486511},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5220303535461426},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5165497064590454},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.5021247863769531},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4537610411643982},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18641135096549988},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2964396132","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1908.00219v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2964396132","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/1908.00219v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5378999710083008,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W649552100","https://openalex.org/W1520813427","https://openalex.org/W1540972459","https://openalex.org/W1544016679","https://openalex.org/W1592601589","https://openalex.org/W1749494163","https://openalex.org/W1931877416","https://openalex.org/W1976467619","https://openalex.org/W1986864914","https://openalex.org/W1999874108","https://openalex.org/W2032924574","https://openalex.org/W2098774185","https://openalex.org/W2111849249","https://openalex.org/W2124609748","https://openalex.org/W2130942839","https://openalex.org/W2153323685","https://openalex.org/W2212765426","https://openalex.org/W2343781317","https://openalex.org/W2610302693","https://openalex.org/W2794787653","https://openalex.org/W2894978157","https://openalex.org/W2898900571","https://openalex.org/W2964193755","https://openalex.org/W2967177252","https://openalex.org/W3114753236"],"related_works":["https://openalex.org/W3090202852","https://openalex.org/W4396877667","https://openalex.org/W4405785811","https://openalex.org/W6979339954","https://openalex.org/W4288056815","https://openalex.org/W4400644591","https://openalex.org/W4405411635","https://openalex.org/W7125093681","https://openalex.org/W4400314721","https://openalex.org/W2892119467"],"abstract_inverted_index":{"Self-driving":[0],"vehicles":[1,44],"(SDVs)":[2],"hold":[3],"great":[4],"potential":[5,27],"for":[6,54,132],"improving":[7],"traffic":[8,61],"safety":[9],"and":[10,39,71],"are":[11],"poised":[12],"to":[13,77,142],"positively":[14],"affect":[15],"the":[16,30,34,46,75,79,83,106,121,161],"quality":[17],"of":[18,20,22,29,33,43,59,120,145],"life":[19],"millions":[21],"people.":[23],"To":[24,93],"unlock":[25],"this":[26,95,115],"one":[28],"critical":[31],"aspects":[32],"autonomous":[35],"technology":[36],"is":[37,138],"understanding":[38],"predicting":[40],"future":[41],"movement":[42],"surrounding":[45],"SDV.":[47],"This":[48],"work":[49,64],"presents":[50],"a":[51,99],"deep-learning-based":[52],"method":[53,100],"kinematically":[55,88],"feasible":[56],"motion":[57,112],"prediction":[58],"such":[60],"actors.":[62],"Previous":[63],"did":[65],"not":[66],"explicitly":[67],"encode":[68],"vehicle":[69,111],"kinematics":[70],"instead":[72],"relied":[73],"on":[74,153],"models":[76,127],"learn":[78],"constraints":[80],"directly":[81],"from":[82,105],"data,":[84],"potentially":[85],"resulting":[86],"in":[87],"infeasible,":[89],"suboptimal":[90],"trajectory":[91],"predictions.":[92],"address":[94],"issue":[96],"we":[97,117],"propose":[98],"that":[101],"seamlessly":[102],"combines":[103],"ideas":[104],"AI":[107],"with":[108,128],"physically":[109],"grounded":[110],"models.":[113],"In":[114],"way":[116],"employ":[118],"best":[119],"both":[122],"worlds,":[123],"coupling":[124],"powerful":[125],"learning":[126,146],"strong":[129],"feasibility":[130],"guarantees":[131],"their":[133],"outputs.":[134],"The":[135],"proposed":[136],"approach":[137],"general,":[139],"being":[140],"applicable":[141],"any":[143],"type":[144],"method.":[147],"Extensive":[148],"experiments":[149],"using":[150],"deep":[151],"convnets":[152],"real-world":[154],"data":[155],"strongly":[156],"indicate":[157],"its":[158],"benefits,":[159],"outperforming":[160],"existing":[162],"state-of-the-art.":[163]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":10}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2019-08-13T00:00:00"}