{"id":"https://openalex.org/W2069040327","doi":"https://doi.org/10.1109/tits.2014.2353302","title":"TraPlan: An Effective Three-in-One Trajectory-Prediction Model in Transportation Networks","display_name":"TraPlan: An Effective Three-in-One Trajectory-Prediction Model in Transportation Networks","publication_year":2014,"publication_date":"2014-09-17","ids":{"openalex":"https://openalex.org/W2069040327","doi":"https://doi.org/10.1109/tits.2014.2353302","mag":"2069040327"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2014.2353302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2014.2353302","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/A5074090518","display_name":"Shaojie Qiao","orcid":"https://orcid.org/0000-0002-4703-780X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojie Qiao","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","School of Information Science and Technology, Southwest Jiaotong University, ChengDu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, ChengDu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103232473","display_name":"Nan Han","orcid":"https://orcid.org/0000-0002-6233-6322"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Han","raw_affiliation_strings":["School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, China","School of Life Science and Engineering , Southwest Jiaotong University , Chengdu , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Life Science and Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"School of Life Science and Engineering , Southwest Jiaotong University , Chengdu , China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078911343","display_name":"William Zhu","orcid":"https://orcid.org/0000-0001-8898-9244"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"William Zhu","raw_affiliation_strings":["Provincial Key Laboratory of Granular Computing, Minnan Normal University, Zhangzhou, China","Provincial Key Lab. of Granular Comput., Minnan Normal Univ., Zhangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Provincial Key Laboratory of Granular Computing, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]},{"raw_affiliation_string":"Provincial Key Lab. of Granular Comput., Minnan Normal Univ., Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089162573","display_name":"Louis Alberto Gutierrez","orcid":"https://orcid.org/0009-0006-4513-2455"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louis Alberto Gutierrez","raw_affiliation_strings":["Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, USA","[Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]},{"raw_affiliation_string":"[Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA]","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6068,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.9044508,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"16","issue":"3","first_page":"1188","last_page":"1198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994999766349792,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7670975923538208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6857684254646301},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6589831113815308},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5303415060043335},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.505176842212677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35003983974456787},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18272754549980164}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7670975923538208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6857684254646301},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6589831113815308},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5303415060043335},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.505176842212677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35003983974456787},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18272754549980164},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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":[{"id":"doi:10.1109/tits.2014.2353302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2014.2353302","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5}],"awards":[{"id":"https://openalex.org/G3294029364","display_name":null,"funder_award_id":"61170128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3350464265","display_name":"\u57fa\u4e8e\u7fa4\u4f53\u667a\u80fd\u6d8c\u73b0\u7684\u85cf\u6587\u7f51\u7edc\u8206\u60c5\u5206\u6790\u53ca\u7a81\u53d1\u4e8b\u4ef6\u9884\u8b66\u673a\u5236\u7814\u7a76","funder_award_id":"61165013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5981163201","display_name":null,"funder_award_id":"2682013BR023","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6887838965","display_name":null,"funder_award_id":"20110184120008","funder_id":"https://openalex.org/F4320336024","funder_display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China"},{"id":"https://openalex.org/G7908117107","display_name":null,"funder_award_id":"61379049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8497662656","display_name":"\u52a8\u6001\u73af\u5883\u611f\u77e5\u7684\u79fb\u52a8\u5bf9\u8c61\u4e0d\u786e\u5b9a\u6027\u8f68\u8ff9\u9884\u6d4b\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61100045","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336024","display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W192663430","https://openalex.org/W578585133","https://openalex.org/W1563419623","https://openalex.org/W1987228002","https://openalex.org/W2008925288","https://openalex.org/W2021016794","https://openalex.org/W2037552411","https://openalex.org/W2062826247","https://openalex.org/W2067261106","https://openalex.org/W2072699031","https://openalex.org/W2077451659","https://openalex.org/W2099594331","https://openalex.org/W2099729613","https://openalex.org/W2108196201","https://openalex.org/W2115482638","https://openalex.org/W2116135393","https://openalex.org/W2126751256","https://openalex.org/W2133675752","https://openalex.org/W2133747588","https://openalex.org/W2153207204","https://openalex.org/W2154882603","https://openalex.org/W2163075788","https://openalex.org/W2166258313","https://openalex.org/W2166931257","https://openalex.org/W2401054706","https://openalex.org/W6607845999","https://openalex.org/W6633556924","https://openalex.org/W6674703308","https://openalex.org/W6674944021"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2387529410","https://openalex.org/W2039473718","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674","https://openalex.org/W3186928667"],"abstract_inverted_index":{"The":[0,155],"existing":[1],"approaches":[2,24],"for":[3],"trajectory":[4,13,103,190,234],"prediction":[5,225],"(TP)":[6],"are":[7],"primarily":[8],"concerned":[9],"with":[10,178,194,261],"discovering":[11],"frequent":[12],"patterns":[14],"(FTPs)":[15],"from":[16,151],"historical":[17],"movement":[18],"data.":[19],"Moreover,":[20,192],"most":[21,47],"of":[22,36,46,82,102,125,136,166,173,189,201,210,226,230,250],"these":[23,245],"work":[25],"by":[26,169,237,258],"using":[27],"a":[28,55,77,90,99,110],"linear":[29],"TP":[30,57,112,257,263],"model":[31,58,253],"to":[32,43,97,118,121,132,256],"depict":[33],"the":[34,44,134,137,159,163,179,186,199,214,219,248,251],"positions":[35],"objects,":[37],"which":[38,75],"does":[39],"not":[40],"lend":[41],"itself":[42],"complexities":[45],"real-world":[48,152],"applications.":[49],"In":[50,130],"this":[51],"research,":[52],"we":[53,142,243],"propose":[54],"three-in-one":[56],"in":[59,232,254],"road-constrained":[60],"transportation":[61,87,153],"networks":[62],"called":[63,114],"TraPlan.":[64],"TraPlan":[65,220,252],"contains":[66],"three":[67],"essential":[68],"techniques:":[69],"1)":[70],"constrained":[71],"network":[72,196],"R-tree":[73],"(CNR-tree),":[74],"is":[76,95,116],"two-tiered":[78],"dynamic":[79],"index":[80,140,167],"structure":[81],"moving":[83,127],"objects":[84,126,231],"based":[85],"on":[86,145,207,240],"networks;":[88],"2)":[89],"region-of-interest":[91],"(RoI)":[92],"discovery":[93],"algorithm":[94],"employed":[96],"partition":[98],"large":[100],"number":[101],"points":[104],"into":[105],"distinct":[106,233],"clusters;":[107],"and":[108,223,247],"3)":[109],"FTP-tree-based":[111],"approach,":[113],"FTP-mining,":[115],"proposed":[117,138],"discover":[119],"FTPs":[120],"infer":[122],"future":[123],"locations":[124],"within":[128],"RoIs.":[129],"order":[131],"evaluate":[133,244],"results":[135,156,216,246],"CNR-tree":[139,160],"structure,":[141],"conducted":[143],"experiments":[144],"synthetically":[146],"generated":[147],"data":[148,235],"sets":[149,236],"taken":[150],"networks.":[154],"show":[157,217],"that":[158,218],"can":[161],"reduce":[162,185],"time":[164,187],"cost":[165,188],"maintenance":[168],"an":[170,206],"average":[171,208],"gap":[172],"about":[174,211],"40%":[175],"when":[176],"compared":[177,193],"traditional":[180],"NDTR-tree,":[181],"as":[182,184],"well":[183],"queries.":[191],"fixed":[195],"R-Tree":[197],"(FNR-trees),":[198],"accuracy":[200],"range":[202],"queries":[203],"has":[204],"shown":[205],"improvement":[209],"32%.":[212],"Furthermore,":[213],"experimental":[215],"demonstrates":[221],"accurate":[222],"efficient":[224],"possible":[227],"motion":[228],"curves":[229],"over":[238],"80%":[239],"average.":[241],"Finally,":[242],"performance":[249],"regard":[255],"comparing":[259],"it":[260],"other":[262],"algorithms.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}