{"id":"https://openalex.org/W2981684860","doi":"https://doi.org/10.1109/icite.2019.8880168","title":"Trajectory Prediction of Vehicles Based on Deep Learning","display_name":"Trajectory Prediction of Vehicles Based on Deep Learning","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2981684860","doi":"https://doi.org/10.1109/icite.2019.8880168","mag":"2981684860"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite.2019.8880168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5043973969","display_name":"Huatao Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huatao Jiang","raw_affiliation_strings":["Institute of Microelectronics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Beijing, China","institution_ids":["https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084843712","display_name":"Lin Chang","orcid":"https://orcid.org/0000-0002-8102-9213"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Chang","raw_affiliation_strings":["Institute of Microelectronics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Beijing, China","institution_ids":["https://openalex.org/I4210119392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344211","display_name":"Qing Li","orcid":"https://orcid.org/0000-0003-4364-1257"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["Institute of Microelectronics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Beijing, China","institution_ids":["https://openalex.org/I4210119392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100723409","display_name":"Dapeng Chen","orcid":"https://orcid.org/0000-0003-2000-401X"},"institutions":[{"id":"https://openalex.org/I4210119392","display_name":"Institute of Microelectronics","ror":"https://ror.org/02s6gs133","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210119392"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dapeng Chen","raw_affiliation_strings":["Institute of Microelectronics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Microelectronics, Beijing, China","institution_ids":["https://openalex.org/I4210119392"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.551,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.873393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"190","last_page":"195"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998,"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":0.9998,"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":0.9944,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.9903,"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/position","display_name":"Position (finance)","score":0.5245186}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8439327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70162964},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6904178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6891142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6435717},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.56022656},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.53429765},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5245186},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.46425682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4043439},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.19313028},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite.2019.8880168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.59,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":18,"referenced_works":["https://openalex.org/W104713727","https://openalex.org/W1520813427","https://openalex.org/W2012849708","https://openalex.org/W2019550475","https://openalex.org/W2055556996","https://openalex.org/W2079150870","https://openalex.org/W2085281262","https://openalex.org/W2097545165","https://openalex.org/W2101545882","https://openalex.org/W2136848157","https://openalex.org/W2424778531","https://openalex.org/W2564701384","https://openalex.org/W2580495915","https://openalex.org/W2607296803","https://openalex.org/W2608536805","https://openalex.org/W2784715585","https://openalex.org/W2964193755","https://openalex.org/W3104946437"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W3034302643","https://openalex.org/W3032952384","https://openalex.org/W3008584592","https://openalex.org/W2982145560","https://openalex.org/W2964335273","https://openalex.org/W2953061907","https://openalex.org/W1847088711"],"abstract_inverted_index":{"In":[0,50,88],"order":[1,156],"to":[2,39,112,152,157,214],"safely":[3],"and":[4,26,108,116,188],"efficiently":[5],"drive":[6],"through":[7],"the":[8,13,16,32,40,44,65,68,79,114,117,120,125,133,159,164,172,180,192,209,216],"complex":[9],"traffic":[10],"scenarios,":[11],"predicting":[12],"trajectory":[14,28,62,84,195],"of":[15,43,48,67,74,95,119,127,139,142,161,194,199,211],"forward":[17,121],"vehicle":[18,217],"accurately":[19],"is":[20,78,86],"important":[21],"for":[22,61,83,207],"intelligent":[23,33],"vehicles.":[24,122],"Accurate":[25],"realtime":[27],"prediction":[29,63,85],"can":[30],"make":[31],"vehicles":[34,45,143],"adjust":[35],"their":[36],"maneuvers":[37],"according":[38],"running":[41],"state":[42],"in":[46,155,171,191],"front":[47],"them.":[49],"recent":[51],"years,":[52],"deep-learning-based":[53],"methods":[54],"have":[55,203],"been":[56],"applied":[57],"as":[58],"novel":[59],"alternatives":[60],"with":[64],"development":[66],"machine":[69],"learning.":[70],"But":[71],"which":[72,137],"kind":[73],"deep":[75,96,174],"neural":[76,97,175,212],"networks":[77,176],"most":[80],"suitable":[81],"model":[82,182,187,190,210],"uncertain.":[87],"this":[89],"paper,":[90],"we":[91,148,178],"design":[92],"three":[93,129,173],"kinds":[94],"networks:":[98],"Long":[99],"Short":[100],"Term":[101],"Memory":[102],"(LSTM),":[103],"Gated":[104],"Recurrent":[105],"Units":[106],"(GRU),":[107],"Stacked":[109],"Autoencoders":[110],"(SAEs)":[111],"predict":[113,215],"position":[115],"velocity":[118],"We":[123],"verify":[124],"performance":[126],"these":[128],"network":[130,213],"models":[131],"on":[132,144,163],"NGSIM":[134],"I-80":[135],"dataset":[136],"consists":[138],"real":[140],"trajectories":[141],"multi-lanes.":[145],"What's":[146],"more,":[147],"use":[149],"Savitzky-Golay":[150],"filter":[151,153],"noise":[154,162],"reduce":[158],"effect":[160],"training":[165],"models.":[166],"Our":[167],"results":[168,198],"demonstrate":[169],"that":[170,177],"designed,":[179],"LSTM":[181],"perform":[183],"better":[184],"than":[185],"GRU":[186],"SAEs":[189],"area":[193],"prediction.":[196],"The":[197],"our":[200],"works":[201],"will":[202],"certain":[204],"guiding":[205],"significance":[206],"choosing":[208],"trajectories.":[218]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2981684860","counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2}],"updated_date":"2025-04-20T18:17:40.523592","created_date":"2019-11-01"}