{"id":"https://openalex.org/W4385695905","doi":"https://doi.org/10.1109/mits.2023.3296331","title":"Spatiotemporal <i>K</i>-Nearest Neighbors Algorithm and Bayesian Approach for Estimating Urban Link Travel Time Distribution From Sparse GPS Trajectories","display_name":"Spatiotemporal <i>K</i>-Nearest Neighbors Algorithm and Bayesian Approach for Estimating Urban Link Travel Time Distribution From Sparse GPS Trajectories","publication_year":2023,"publication_date":"2023-08-09","ids":{"openalex":"https://openalex.org/W4385695905","doi":"https://doi.org/10.1109/mits.2023.3296331"},"language":"en","primary_location":{"id":"doi:10.1109/mits.2023.3296331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3296331","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"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 Intelligent Transportation Systems Magazine","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/A5040133388","display_name":"Wenwen Qin","orcid":"https://orcid.org/0000-0003-4982-2024"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenwen Qin","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0003-4982-2024","affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103160102","display_name":"Mingfeng Zhang","orcid":"https://orcid.org/0000-0002-8537-6829"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingfeng Zhang","raw_affiliation_strings":["Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326391","display_name":"Wu Li","orcid":"https://orcid.org/0000-0002-8607-5454"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Li","raw_affiliation_strings":["Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-8607-5454","affiliations":[{"raw_affiliation_string":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090429901","display_name":"Yunyi Liang","orcid":"https://orcid.org/0000-0003-3693-0106"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yunyi Liang","raw_affiliation_strings":["Department Mobility Systems Engineering, Technical University of Munich, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0003-3693-0106","affiliations":[{"raw_affiliation_string":"Department Mobility Systems Engineering, Technical University of Munich, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5351,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62935502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"15","issue":"6","first_page":"152","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9983000159263611,"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/T10370","display_name":"Traffic and Road Safety","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.6600974798202515},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5476391315460205},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5264502167701721},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5188428163528442},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4681048095226288},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4680452346801758},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4660286605358124},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.4631580412387848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33243805170059204},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.1174415647983551}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6600974798202515},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5476391315460205},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5264502167701721},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5188428163528442},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4681048095226288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4680452346801758},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4660286605358124},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.4631580412387848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33243805170059204},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.1174415647983551},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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},{"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/mits.2023.3296331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3296331","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"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 Intelligent Transportation Systems Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4237855338","display_name":null,"funder_award_id":"52062024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6077345446","display_name":null,"funder_award_id":"2023JJ40731","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7697054680","display_name":null,"funder_award_id":"52002281","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7963201109","display_name":null,"funder_award_id":"52002161","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1982252353","https://openalex.org/W1984006069","https://openalex.org/W2022364459","https://openalex.org/W2030397365","https://openalex.org/W2051503055","https://openalex.org/W2056902888","https://openalex.org/W2075407851","https://openalex.org/W2085234095","https://openalex.org/W2088906176","https://openalex.org/W2092208658","https://openalex.org/W2124299914","https://openalex.org/W2138159469","https://openalex.org/W2141585124","https://openalex.org/W2142382652","https://openalex.org/W2144475703","https://openalex.org/W2150010190","https://openalex.org/W2280865380","https://openalex.org/W2307933510","https://openalex.org/W2332401067","https://openalex.org/W2482406075","https://openalex.org/W2556487516","https://openalex.org/W2602441310","https://openalex.org/W2624886053","https://openalex.org/W2749405588","https://openalex.org/W2793245033","https://openalex.org/W2883345462","https://openalex.org/W2892302657","https://openalex.org/W2892910290","https://openalex.org/W2911826336","https://openalex.org/W2922034560","https://openalex.org/W2946634724","https://openalex.org/W2949285127","https://openalex.org/W2953462469","https://openalex.org/W2957240059","https://openalex.org/W2963995014","https://openalex.org/W2964098640","https://openalex.org/W2968542883","https://openalex.org/W2978273467","https://openalex.org/W3014365253","https://openalex.org/W3016546268","https://openalex.org/W3024861527","https://openalex.org/W3037106793","https://openalex.org/W3152743306","https://openalex.org/W3176108125","https://openalex.org/W4283701218","https://openalex.org/W4295548122"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2586280620","https://openalex.org/W2805505483","https://openalex.org/W2334071950","https://openalex.org/W2384744344","https://openalex.org/W4233932308","https://openalex.org/W1799694159","https://openalex.org/W2393169196","https://openalex.org/W2366610330","https://openalex.org/W4242143973"],"abstract_inverted_index":{"Travel":[0],"time":[1,194],"distribution":[2,220],"(TTD)":[3],"estimation":[4],"on":[5,106,226,239],"urban":[6],"arterial":[7,242],"links":[8],"with":[9,253],"sparse":[10],"trajectory":[11,141],"data":[12,88,152,256],"is":[13,96,176,214],"a":[14,79,99,139,157,172,201,240],"practically":[15],"important":[16],"while":[17],"substantially":[18],"challenging":[19],"subject.":[20],"Although":[21],"several":[22],"methods":[23,36,265],"have":[24],"been":[25],"proposed":[26,177,251],"to":[27,85,97,148,178,216,262],"estimate":[28,179],"link":[29,76,103,181,222],"TTDs,":[30],"the":[31,34,45,75,87,113,150,161,188,192,218,227,250,254,263],"applications":[32],"of":[33,66,74,93,101,184,190,221,268],"existing":[35],"are":[37,128],"often":[38],"limited":[39],"by":[40,111],"their":[41],"shortcomings,":[42],"such":[43],"as":[44,156],"needs":[46],"for":[47,144,159,187],"extra":[48],"road":[49],"geometric":[50],"features,":[51],"signal":[52],"control":[53],"plans,":[54],"model":[55],"assumptions,":[56],"etc.":[57],"As":[58],"an":[59,207],"alternative,":[60],"this":[61,94],"article":[62],"makes":[63],"full":[64],"use":[65],"ubiquitous":[67],"incomplete":[68,107,164,185],"trajectories":[69,110,186],"that":[70,249],"only":[71],"traverse":[72],"part":[73],"and":[77,108,122,154,165,211,270],"introduces":[78],"novel":[80],"bilevel":[81,202],"Bayesian":[82,123],"sampling":[83,204,213],"method":[84,143,205],"alleviate":[86],"sparsity":[89],"problem.":[90],"The":[91,246],"focus":[92],"study":[95,236],"develop":[98],"framework":[100],"estimating":[102],"TTDs":[104],"based":[105,225],"complete":[109,166],"using":[112],"spatiotemporal":[114,173],"<italic":[115],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[116,132,233],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">K</i>":[117],"-nearest":[118],"neighbors":[119],"(KNN)":[120],"algorithm":[121,175],"approach.":[124],"Three":[125],"major":[126,241],"steps":[127],"involved:":[129],"<list":[130],"list-type=\"bullet\"":[131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[133],"<list-item>":[134,169,198],"<label>\u2022</label>":[135,170,199],"First,":[136],"we":[137],"consider":[138],"straightforward":[140],"imputation":[142],"missing":[145],"GPS":[146],"points":[147],"improve":[149],"input":[151],"quality":[153],"serve":[155],"basis":[158],"measuring":[160],"similarity":[162],"between":[163],"trajectories.":[167],"</list-item>":[168,197,230],"Then,":[171],"KNN":[174],"virtual":[180],"travel":[182,193,223],"times":[183,224],"purposes":[189],"increasing":[191],"sample":[195],"size.":[196],"Finally,":[200],"Bayesian-based":[203],"comprising":[206],"improved":[208],"particle":[209],"filter":[210],"Gibbs":[212],"introduced":[215],"approximate":[217],"posterior":[219],"enhanced":[228],"data.":[229],"</list>":[231],"<p":[232],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">A":[234],"case":[235],"was":[237],"conducted":[238],"in":[243,266],"Nanjing,":[244],"China.":[245],"results":[247],"indicate":[248],"approach":[252],"augmented":[255],"can":[257],"achieve":[258],"promising":[259],"performance":[260],"compared":[261],"competing":[264],"terms":[267],"effectiveness":[269],"adaptiveness.":[271]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}