{"id":"https://openalex.org/W3131807685","doi":"https://doi.org/10.1109/iros45743.2020.9341034","title":"Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles","display_name":"Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3131807685","doi":"https://doi.org/10.1109/iros45743.2020.9341034","mag":"3131807685"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9341034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101509832","display_name":"Chenxu Luo","orcid":"https://orcid.org/0000-0001-6647-8283"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]},{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenxu Luo","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD","Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070657531","display_name":"Lin Sun","orcid":"https://orcid.org/0000-0003-2923-3281"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Sun","raw_affiliation_strings":["Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060540407","display_name":"Dariush Dabiri","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dariush Dabiri","raw_affiliation_strings":["Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Strategy and Innovation Center, Samsung, Inc., San Jose, CA","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086706224","display_name":"Alan Yuille","orcid":"https://orcid.org/0000-0001-5207-9249"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Yuille","raw_affiliation_strings":["Johns Hopkins University, Baltimore, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johns Hopkins University, Baltimore, MD","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2370","last_page":"2376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9416000247001648,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9114999771118164,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8314332962036133},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.73772132396698},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7196884751319885},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6535634398460388},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6345457434654236},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5512332916259766},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5472261309623718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47474128007888794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3387490510940552}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8314332962036133},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73772132396698},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7196884751319885},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6535634398460388},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6345457434654236},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5512332916259766},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5472261309623718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47474128007888794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3387490510940552},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros45743.2020.9341034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1689711448","https://openalex.org/W2084835622","https://openalex.org/W2105934661","https://openalex.org/W2157331557","https://openalex.org/W2183341477","https://openalex.org/W2424778531","https://openalex.org/W2607296803","https://openalex.org/W2798930779","https://openalex.org/W2883602772","https://openalex.org/W2886617718","https://openalex.org/W2898900571","https://openalex.org/W2948479456","https://openalex.org/W2948511093","https://openalex.org/W2953920792","https://openalex.org/W2955189650","https://openalex.org/W2963001155","https://openalex.org/W2963309363","https://openalex.org/W2963759562","https://openalex.org/W2963906196","https://openalex.org/W2964121744","https://openalex.org/W2967177252","https://openalex.org/W2967390659","https://openalex.org/W2969340007","https://openalex.org/W2970116586","https://openalex.org/W2970971581","https://openalex.org/W2980160556","https://openalex.org/W2982389908","https://openalex.org/W2986406093","https://openalex.org/W2989851631","https://openalex.org/W3004201988","https://openalex.org/W3028769608","https://openalex.org/W3114753236","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6753376238","https://openalex.org/W6755864109","https://openalex.org/W6766795455","https://openalex.org/W6766978945","https://openalex.org/W6767342764","https://openalex.org/W6769043036"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"Trajectory":[0],"prediction":[1],"is":[2,50,97,138],"crucial":[3],"for":[4,31,81],"autonomous":[5],"vehicles.":[6],"The":[7],"planning":[8],"system":[9],"not":[10,68,150],"only":[11],"needs":[12],"to":[13,44,62,99,129,143,154],"know":[14],"the":[15,19,28,39,47,56,86,101,105,110,116,124,145,169,173,187],"current":[16],"state":[17],"of":[18,51,55,104,175],"surrounding":[20],"objects":[21],"but":[22],"also":[23],"their":[24,33],"possible":[25],"states":[26],"in":[27,186],"future.":[29],"As":[30],"vehicles,":[32],"trajectories":[34],"are":[35],"significantly":[36],"influenced":[37],"by":[38],"lane":[40,48,82,87,94,112,117],"geometry":[41],"and":[42,89,158,165],"how":[43],"effectively":[45],"use":[46,59],"information":[49],"active":[52],"interest.":[53],"Most":[54,133],"existing":[57],"works":[58],"rasterized":[60],"maps":[61],"explore":[63],"road":[64],"information,":[65],"which":[66],"does":[67,149],"distinguish":[69],"different":[70],"lanes.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75],"propose":[76],"a":[77,92,141],"novel":[78],"instance-aware":[79],"representation":[80,113],"representation.":[83],"By":[84],"integrating":[85],"features":[88],"trajectory":[90,137],"features,":[91],"goal-oriented":[93],"attention":[95,118],"module":[96,119],"proposed":[98,111,177,181],"predict":[100],"future":[102],"locations":[103],"vehicle.":[106],"We":[107],"show":[108],"that":[109],"together":[114],"with":[115,140],"can":[120,159],"be":[121],"integrated":[122],"into":[123],"widely":[125],"used":[126],"encoder-decoder":[127],"framework":[128],"generate":[130],"diverse":[131,161],"predictions.":[132],"importantly,":[134],"each":[135],"generated":[136],"associated":[139],"probability":[142],"handle":[144],"uncertainty.":[146],"Our":[147],"method":[148,182],"suffer":[151],"from":[152],"collapsing":[153],"one":[155],"behavior":[156],"modal":[157],"cover":[160],"possibilities.":[162],"Extensive":[163],"experiments":[164],"ablation":[166],"studies":[167],"on":[168],"benchmark":[170],"datasets":[171],"corroborate":[172],"effectiveness":[174],"our":[176,180],"method.":[178],"Notably,":[179],"ranks":[183],"third":[184],"place":[185],"Argoverse":[188],"motion":[189],"forecasting":[190],"competition":[191],"at":[192],"NeurIPS":[193],"2019":[194],"<sup":[195],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[196],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[197],".":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":11}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
