{"id":"https://openalex.org/W3135495205","doi":"https://doi.org/10.1109/lra.2021.3062309","title":"IDE-Net: Interactive Driving Event and Pattern Extraction From Human Data","display_name":"IDE-Net: Interactive Driving Event and Pattern Extraction From Human Data","publication_year":2021,"publication_date":"2021-02-25","ids":{"openalex":"https://openalex.org/W3135495205","doi":"https://doi.org/10.1109/lra.2021.3062309","mag":"3135495205"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2021.3062309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3062309","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5015322877","display_name":"Xiaosong Jia","orcid":"https://orcid.org/0000-0002-5222-1476"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaosong Jia","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087667477","display_name":"Liting Sun","orcid":"https://orcid.org/0000-0002-1248-2137"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liting Sun","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064077634","display_name":"Masayoshi Tomizuka","orcid":"https://orcid.org/0000-0003-0206-6639"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masayoshi Tomizuka","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101770873","display_name":"Wei Zhan","orcid":"https://orcid.org/0000-0002-1474-1200"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Zhan","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015322877"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":1.758,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.83689268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"3065","last_page":"3072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"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":0.9991000294685364,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9848999977111816,"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/computer-science","display_name":"Computer science","score":0.8369699716567993},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7018673419952393},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6745491623878479},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5602629780769348},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5399970412254333},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.52741539478302},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5215256810188293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49962854385375977},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4717094600200653},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4345667362213135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8369699716567993},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7018673419952393},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6745491623878479},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5602629780769348},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5399970412254333},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.52741539478302},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5215256810188293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49962854385375977},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4717094600200653},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4345667362213135},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2021.3062309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2021.3062309","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2773225018","https://openalex.org/W2787337315","https://openalex.org/W2808545847","https://openalex.org/W2945913957","https://openalex.org/W2962079840","https://openalex.org/W2963373786","https://openalex.org/W2963403868","https://openalex.org/W2963464736","https://openalex.org/W2963907629","https://openalex.org/W2968008415","https://openalex.org/W2980087597","https://openalex.org/W2990048843","https://openalex.org/W2990702197","https://openalex.org/W2996474936","https://openalex.org/W3004408449","https://openalex.org/W3009561768","https://openalex.org/W3016228756","https://openalex.org/W3034722190","https://openalex.org/W3034796668","https://openalex.org/W3035172746","https://openalex.org/W3037606473","https://openalex.org/W3082071414","https://openalex.org/W3090789587","https://openalex.org/W3100859887","https://openalex.org/W3132530365","https://openalex.org/W4295276246","https://openalex.org/W4385245566","https://openalex.org/W6718379498","https://openalex.org/W6738893770","https://openalex.org/W6739901393","https://openalex.org/W6748320467","https://openalex.org/W6755103542","https://openalex.org/W6762446131","https://openalex.org/W6768870957","https://openalex.org/W6774670964","https://openalex.org/W6776193808","https://openalex.org/W6779643545","https://openalex.org/W6779977557"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W410723623","https://openalex.org/W2413243053","https://openalex.org/W2015341305","https://openalex.org/W3210196349","https://openalex.org/W4214728004","https://openalex.org/W2950181282","https://openalex.org/W2963261224","https://openalex.org/W2798287483","https://openalex.org/W2913410650"],"abstract_inverted_index":{"Autonomous":[0],"vehicles":[1],"(AVs)":[2],"need":[3,33,75],"to":[4,24,34,39,47,76,83,99,106,175,200,216],"share":[5],"the":[6,49,86,118,141,160,190,202,218,224,228,270],"road":[7,11],"with":[8,27,41,67],"multiple,":[9],"heterogeneous":[10],"users":[12],"in":[13,72,97,205,233,266],"a":[14,171,212],"variety":[15],"of":[16,53,58,62,89,122,135,140,192,230,235,247,269],"driving":[17,109],"scenarios.":[18],"It":[19],"is":[20,65,121,170],"overwhelming":[21],"and":[22,31,37,51,55,70,79,102,111,133,138,153,164,180,195,238,256,260],"unnecessary":[23],"carefully":[25],"interact":[26,40],"all":[28],"observed":[29],"agents,":[30],"AVs":[32],"determine":[35],"whether":[36,101],"when":[38],"each":[42],"surrounding":[43],"agent.":[44],"In":[45,155,186],"order":[46],"facilitate":[48],"design":[50,211],"testing":[52],"prediction":[54],"planning":[56],"modules":[57],"AVs,":[59],"in-depth":[60],"understanding":[61],"interactive":[63,108,136],"behavior":[64,73,253],"expected":[66],"proper":[68],"representation,":[69,254],"events":[71,110,179],"data":[74,115],"be":[77],"extracted":[78],"categorized":[80],"automatically.":[81],"Answers":[82],"what":[84],"are":[85,91,144,264],"essential":[87],"patterns":[88,112,181,246],"interactions":[90],"also":[92,210],"crucial":[93],"for":[94,116,125,251],"these":[95],"motivations":[96],"addition":[98],"answering":[100],"when.":[103],"Thus,":[104],"learning":[105,173,194],"extract":[107,177],"from":[113,183],"human":[114],"tackling":[117],"whether-when-what":[119],"tasks":[120,199],"critical":[123],"importance":[124],"AVs.":[126],"There":[127],"is,":[128],"however,":[129],"no":[130],"clear":[131],"definition":[132],"taxonomy":[134],"behavior,":[137],"most":[139],"existing":[142],"works":[143],"based":[145],"on":[146,223],"either":[147],"manual":[148],"labelling":[149],"or":[150],"hand-crafted":[151],"rules":[152],"features.":[154],"this":[156],"letter,":[157],"we":[158,188],"propose":[159],"Interactive":[161],"Driving":[162],"event":[163],"pattern":[165,203,240],"Extraction":[166],"Network":[167],"(IDE-Net),":[168],"which":[169],"deep":[172],"framework":[174],"automatically":[176],"interaction":[178],"directly":[182],"vehicle":[184],"trajectories.":[185],"IDE-Net,":[187],"leverage":[189],"power":[191],"multi-task":[193],"proposed":[196],"three":[197,244],"auxiliary":[198],"assist":[201],"extraction":[204],"an":[206],"unsupervised":[207],"fashion.":[208],"We":[209,242],"unique":[213],"spatial-temporal":[214],"block":[215],"encode":[217],"trajectory":[219],"data.":[220],"Experimental":[221],"results":[222],"INTERACTION":[225],"dataset":[226],"verified":[227],"effectiveness":[229],"such":[231],"designs":[232],"terms":[234],"better":[236],"generalizability":[237],"effective":[239],"extraction.":[241],"find":[243],"interpretable":[245],"interactions,":[248],"bringing":[249],"insights":[250],"driver":[252],"modeling":[255],"comprehension.":[257],"Both":[258],"objective":[259],"subjective":[261],"evaluation":[262],"metrics":[263],"adopted":[265],"our":[267],"analysis":[268],"learned":[271],"patterns.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
