{"id":"https://openalex.org/W3045642919","doi":"https://doi.org/10.1109/icc40277.2020.9149261","title":"GlobalInsight: An LSTM Based Model for Multi-Vehicle Trajectory Prediction","display_name":"GlobalInsight: An LSTM Based Model for Multi-Vehicle Trajectory Prediction","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3045642919","doi":"https://doi.org/10.1109/icc40277.2020.9149261","mag":"3045642919"},"language":"en","primary_location":{"id":"doi:10.1109/icc40277.2020.9149261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc40277.2020.9149261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","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/A5018985622","display_name":"Wenquan Xu","orcid":"https://orcid.org/0000-0002-8321-3225"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenquan Xu","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101585110","display_name":"Zhikang Chen","orcid":"https://orcid.org/0009-0003-2568-6184"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikang Chen","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103044002","display_name":"Chuwen Zhang","orcid":"https://orcid.org/0000-0002-2709-4989"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuwen Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038443691","display_name":"Xuefeng Ji","orcid":"https://orcid.org/0000-0001-9848-7993"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Ji","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754862","display_name":"Yunsheng Wang","orcid":"https://orcid.org/0000-0002-9876-5356"},"institutions":[{"id":"https://openalex.org/I39965400","display_name":"Kettering University","ror":"https://ror.org/03rcspa57","country_code":"US","type":"education","lineage":["https://openalex.org/I39965400"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunsheng Wang","raw_affiliation_strings":["Kettering University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kettering University","institution_ids":["https://openalex.org/I39965400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341885","display_name":"Hang Su","orcid":"https://orcid.org/0000-0001-8294-6315"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Su","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100395454","display_name":"Bin Liu","orcid":"https://orcid.org/0000-0001-9758-0352"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liu","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"54","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9988999962806702,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8575925827026367},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7676979899406433},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.45994728803634644},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4373679459095001},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.43592146039009094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3681953549385071},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.19309237599372864}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8575925827026367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7676979899406433},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.45994728803634644},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4373679459095001},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.43592146039009094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3681953549385071},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.19309237599372864},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc40277.2020.9149261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc40277.2020.9149261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"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/W1940872118","https://openalex.org/W2020209171","https://openalex.org/W2064675550","https://openalex.org/W2070678348","https://openalex.org/W2102113734","https://openalex.org/W2133564696","https://openalex.org/W2143783579","https://openalex.org/W2151570219","https://openalex.org/W2156387975","https://openalex.org/W2164489414","https://openalex.org/W2166813035","https://openalex.org/W2167052694","https://openalex.org/W2183679353","https://openalex.org/W2424778531","https://openalex.org/W2766836212","https://openalex.org/W2769282630","https://openalex.org/W2798024831","https://openalex.org/W2803184913","https://openalex.org/W2899675781","https://openalex.org/W2905385096","https://openalex.org/W2908193078","https://openalex.org/W2943919122","https://openalex.org/W2962687116","https://openalex.org/W2962733527","https://openalex.org/W2962834725","https://openalex.org/W2963906196","https://openalex.org/W2963914175","https://openalex.org/W2964189376","https://openalex.org/W2964193755","https://openalex.org/W2990702197","https://openalex.org/W3105115779","https://openalex.org/W6631190155","https://openalex.org/W6640362995","https://openalex.org/W6675365184","https://openalex.org/W6679434410","https://openalex.org/W6682889407","https://openalex.org/W6684373561","https://openalex.org/W6755472338","https://openalex.org/W6756026151","https://openalex.org/W6762190738"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W3131574667","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674"],"abstract_inverted_index":{"Intelligent":[0],"Transport":[1],"System":[2],"(ITS)":[3],"raises":[4],"the":[5,31,47,56,67,87,112,124,133,139,144,154,165],"increasing":[6],"demand":[7],"on":[8,86],"accurate":[9,41,91],"vehicle":[10,116],"trajectory":[11,42,60,92,145],"prediction":[12,43,61,93],"for":[13,33,44,59,94],"navigation":[14],"efficiency.":[15],"The":[16],"rapidly":[17],"developing":[18],"5G":[19],"networks":[20],"provides":[21],"communications":[22],"with":[23],"high":[24],"transmission":[25],"bandwidth":[26],"and":[27,123,147,157],"super-low":[28],"latency,":[29],"paving":[30],"way":[32],"Mobile":[34],"Edge":[35],"Computing":[36],"(MEC)":[37],"to":[38,66,89,109,142],"calculate":[39],"more":[40,51],"vehicles,":[45,122],"as":[46],"MEC":[48,88],"server":[49],"holds":[50],"comprehensive":[52],"vehicular":[53],"information.":[54],"However,":[55],"current":[57],"methods":[58],"are":[62],"not":[63],"efficient":[64],"due":[65],"dynamical":[68],"environment.":[69],"To":[70],"address":[71],"this":[72],"issue,":[73],"we":[74,104],"propose":[75],"GlobalInsight,":[76],"a":[77],"Long":[78],"Short-Term":[79],"Memory":[80],"(LSTM)":[81],"based":[82],"model,":[83],"which":[84],"runs":[85],"perform":[90],"multiple":[95],"vehicles":[96],"no":[97],"matter":[98],"how":[99],"scenario":[100],"changes.":[101],"In":[102],"particular,":[103],"use":[105],"three":[106],"auxiliary":[107],"layers":[108],"respectively":[110],"capture":[111],"principal":[113],"component":[114],"of":[115,120,127],"features,":[117],"social":[118],"interaction":[119],"adjacent":[121],"cross-vehicle":[125],"correlation":[126],"similar":[128],"vehicles.":[129],"We":[130,149],"further":[131],"integrate":[132],"above":[134],"information":[135],"into":[136],"LSTM":[137],"in":[138],"main":[140],"layer":[141],"enhance":[143],"learning":[146],"prediction.":[148],"evaluate":[150],"our":[151,162],"model":[152,163],"under":[153],"NGSIM":[155],"dataset,":[156],"experimental":[158],"results":[159],"exhibit":[160],"that":[161],"outperforms":[164],"state-of-the-art":[166],"approaches.":[167]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}