{"id":"https://openalex.org/W4213069740","doi":"https://doi.org/10.1109/tits.2022.3151263","title":"A Novel Multimodal Vehicle Path Prediction Method Based on Temporal Convolutional Networks","display_name":"A Novel Multimodal Vehicle Path Prediction Method Based on Temporal Convolutional Networks","publication_year":2022,"publication_date":"2022-02-18","ids":{"openalex":"https://openalex.org/W4213069740","doi":"https://doi.org/10.1109/tits.2022.3151263"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3151263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3151263","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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/A5016289526","display_name":"Mozhgan Nasr Azadani","orcid":"https://orcid.org/0000-0002-2872-1438"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mozhgan Nasr Azadani","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0002-2872-1438","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada","institution_ids":["https://openalex.org/I153718931"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012195474","display_name":"Azzedine Boukerche","orcid":"https://orcid.org/0000-0002-3851-9938"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Azzedine Boukerche","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3851-9938","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada","institution_ids":["https://openalex.org/I153718931"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I153718931"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":2.7325,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.90718968,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":100},"biblio":{"volume":"23","issue":"12","first_page":"25384","last_page":"25395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"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":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9976999759674072,"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.641237199306488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5032238364219666},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4631793797016144},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4227476119995117},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10324284434318542}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641237199306488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5032238364219666},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4631793797016144},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4227476119995117},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10324284434318542}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3151263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3151263","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320994","display_name":"Canada Research Chairs","ror":"https://ror.org/0517h6h17"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2010725166","https://openalex.org/W2012849708","https://openalex.org/W2030032449","https://openalex.org/W2092272787","https://openalex.org/W2107105977","https://openalex.org/W2166813035","https://openalex.org/W2167434358","https://openalex.org/W2194775991","https://openalex.org/W2306644740","https://openalex.org/W2741066535","https://openalex.org/W2782474430","https://openalex.org/W2784715585","https://openalex.org/W2791814097","https://openalex.org/W2883602772","https://openalex.org/W2896554943","https://openalex.org/W2932960505","https://openalex.org/W2954301951","https://openalex.org/W2967177252","https://openalex.org/W2973026470","https://openalex.org/W2989621528","https://openalex.org/W2996287921","https://openalex.org/W2997958396","https://openalex.org/W3011590044","https://openalex.org/W3011742000","https://openalex.org/W3015927450","https://openalex.org/W3016826426","https://openalex.org/W3019688365","https://openalex.org/W3031632615","https://openalex.org/W3036171677","https://openalex.org/W3049690032","https://openalex.org/W3083228182","https://openalex.org/W3091146265","https://openalex.org/W3093896348","https://openalex.org/W3104946437","https://openalex.org/W3109888120","https://openalex.org/W3114950604","https://openalex.org/W3128196514","https://openalex.org/W3131008338","https://openalex.org/W3153801153","https://openalex.org/W3162665729","https://openalex.org/W3164282918","https://openalex.org/W3167145836","https://openalex.org/W3196361212","https://openalex.org/W3204998033","https://openalex.org/W3215488089","https://openalex.org/W3217238041","https://openalex.org/W6772580117","https://openalex.org/W6790128831","https://openalex.org/W6790484778","https://openalex.org/W6795430596"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Accurate":[0],"and":[1,11,19,29,45,112,153,192],"reliable":[2],"prediction":[3,160,186],"of":[4,7,115,156,183],"future":[5,34,72],"motions":[6],"the":[8,24,67,76,109,151,180],"nearby":[9],"agents":[10],"effective":[12],"environment":[13],"understanding":[14],"will":[15],"contribute":[16],"to":[17,56,69,93,105],"high-quality":[18],"meticulous":[20],"path":[21,96,159,185],"planning":[22],"for":[23,33,66],"automated":[25],"vehicles":[26,58,68,95,116],"under":[27],"uncertainty":[28,111],"guarantee":[30],"traffic":[31],"safety":[32],"real-world":[35],"deployments.":[36],"This":[37],"task":[38],"becomes":[39],"more":[40,171],"challenging":[41],"in":[42,78,127],"highly":[43],"dynamic":[44],"complex":[46],"scenarios":[47],"such":[48],"as":[49],"unsignalized":[50,98],"intersections":[51],"where":[52],"no":[53],"lights":[54],"exist":[55],"control":[57],"behavior,":[59],"or":[60],"there":[61],"are":[62,81,144],"not":[63],"multiple":[64],"lines":[65],"anticipate":[70,94],"drivers\u2019":[71],"intentions":[73],"based":[74,122,146],"on":[75,123,147],"lane":[77],"which":[79],"they":[80],"driving.":[82],"In":[83],"this":[84],"study,":[85],"we":[86],"introduce":[87],"a":[88,130,166],"novel":[89],"deep":[90],"learning-based":[91],"methodology":[92],"at":[97],"intersections.":[99],"The":[100,176],"method":[101],"provides":[102],"multimodal":[103],"outputs":[104],"take":[106],"into":[107,140],"account":[108],"inherited":[110],"multimodality":[113],"nature":[114],"behavior.":[117],"Our":[118],"proposed":[119],"model":[120,161],"works":[121],"dilated":[124],"convolutional":[125],"networks":[126],"combination":[128],"with":[129,189],"mixture":[131],"density":[132],"layer.":[133],"We":[134,149],"then":[135],"cluster":[136],"various":[137],"existing":[138],"mixes":[139],"possible":[141],"paths":[142],"that":[143],"ranked":[145],"probability.":[148],"assess":[150],"performance":[152,182],"generalization":[154],"capability":[155],"our":[157,184],"vehicle":[158,174],"using":[162],"several":[163,190],"metrics":[164],"over":[165],"large":[167],"naturalistic":[168],"dataset":[169],"containing":[170],"than":[172],"23800":[173],"trajectories.":[175],"obtained":[177],"results":[178],"reveal":[179],"higher":[181],"approach":[187],"compared":[188],"baselines":[191],"benchmarks.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":2}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}