{"id":"https://openalex.org/W7117974096","doi":"https://doi.org/10.3390/a19010032","title":"Cooperative 4D Trajectory Prediction and Conflict Detection in Integrated Airspace","display_name":"Cooperative 4D Trajectory Prediction and Conflict Detection in Integrated Airspace","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7117974096","doi":"https://doi.org/10.3390/a19010032"},"language":"en","primary_location":{"id":"doi:10.3390/a19010032","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010032","pdf_url":"https://www.mdpi.com/1999-4893/19/1/32/pdf?version=1767246857","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/19/1/32/pdf?version=1767246857","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121831786","display_name":"Xin Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Ma","raw_affiliation_strings":["Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China","institution_ids":["https://openalex.org/I58995867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109774283","display_name":"L. R. Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linxin Zheng","raw_affiliation_strings":["Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China"],"raw_orcid":"https://orcid.org/0009-0002-1676-9677","affiliations":[{"raw_affiliation_string":"Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China","institution_ids":["https://openalex.org/I58995867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121755855","display_name":"Jiajun Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiajun Zhao","raw_affiliation_strings":["AVIC Chengdu Aircraft Design & Research Institute, Chengdu 610091, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AVIC Chengdu Aircraft Design & Research Institute, Chengdu 610091, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113327734","display_name":"Yuxin Wu","orcid":"https://orcid.org/0009-0009-2083-8103"},"institutions":[{"id":"https://openalex.org/I58995867","display_name":"Civil Aviation Flight University of China","ror":"https://ror.org/01xyb1v19","country_code":"CN","type":"education","lineage":["https://openalex.org/I58995867"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Wu","raw_affiliation_strings":["Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Air Traffic Management Institute, Civil Aviation Flight University of China, Guanghan 618307, China","institution_ids":["https://openalex.org/I58995867"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5121831786"],"corresponding_institution_ids":["https://openalex.org/I58995867"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00779239,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"1","first_page":"32","last_page":"32"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11489","display_name":"Air Traffic Management and Optimization","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11489","display_name":"Air Traffic Management and Optimization","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11133","display_name":"UAV Applications and Optimization","score":0.003000000026077032,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12125","display_name":"Aerospace and Aviation Technology","score":0.002099999925121665,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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":0.7430999875068665},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5817000269889832},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5394999980926514},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5117999911308289},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4731000065803528},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.46320000290870667},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.40450000762939453},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7505999803543091},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7430999875068665},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5817000269889832},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5394999980926514},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5117999911308289},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48249998688697815},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4731000065803528},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3874000012874603},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3817000091075897},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C92446256","wikidata":"https://www.wikidata.org/wiki/Q3306762","display_name":"Data validation","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C166961238","wikidata":"https://www.wikidata.org/wiki/Q221395","display_name":"Air traffic control","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2565000057220459}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a19010032","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010032","pdf_url":"https://www.mdpi.com/1999-4893/19/1/32/pdf?version=1767246857","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:59eae5c9a6824b818ebd771de6c81de6","is_oa":true,"landing_page_url":"https://doaj.org/article/59eae5c9a6824b818ebd771de6c81de6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 19, Iss 1, p 32 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a19010032","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010032","pdf_url":"https://www.mdpi.com/1999-4893/19/1/32/pdf?version=1767246857","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7117974096.pdf","grobid_xml":"https://content.openalex.org/works/W7117974096.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W2950100951","https://openalex.org/W3023028824","https://openalex.org/W3082476527","https://openalex.org/W3212717258","https://openalex.org/W3214307562","https://openalex.org/W4417068755"],"related_works":[],"abstract_inverted_index":{"In":[0,35,108,168,265],"order":[1],"to":[2,52],"effectively":[3,14,63],"ensure":[4],"the":[5,17,54,65,68,71,86,91,113,128,140,147,169,174,177,180,193,197,200,208,219,224,227,247,250,257,267,285],"flight":[6,314],"safety":[7],"of":[8,19,29,37,43,56,75,110,132,139,171,176,182,196,261,287],"unmanned":[9],"aerial":[10],"vehicles":[11],"(UAVs)":[12],"and":[13,33,73,81,89,94,98,106,127,144,150,157,160,179,215,249,271,290,296,299,304,312],"deal":[15],"with":[16,45,199],"risk":[18,245],"integrated":[20,129,254,292],"airspace":[21,255,293,309],"operation,":[22],"this":[23,277],"study":[24,278],"carried":[25],"out":[26],"a":[27,96,280],"series":[28],"key":[30,281],"technology":[31],"exploration":[32],"verification.":[34,236],"terms":[36,109],"data":[38,66,77,87,92,100,195],"processing,":[39],"Density-based":[40],"spatial":[41,79],"clustering":[42,48],"applications":[44],"noise":[46,72],"(DBSCAN)":[47],"method":[49,231,274],"is":[50,124,134,205,232,242],"used":[51,233],"preprocess":[53],"characteristics":[55],"UAV":[57,248],"automatic":[58],"dependent":[59],"surveillance\u2013broadcast":[60],"(ADS-B)":[61],"data,":[62,203],"purify":[64],"from":[67],"source,":[69],"eliminate":[70],"outliers":[74],"track":[76,202],"in":[78,217,253,276],"dimension":[80],"spatial-temporal":[82],"dimension,":[83],"significantly":[84],"improve":[85],"quality":[88],"standardize":[90],"characteristics,":[93],"lay":[95],"reliable":[97],"high-quality":[99],"foundation":[101],"for":[102,164,234,284,307],"subsequent":[103],"trajectory":[104,111,121,165,268],"analysis":[105],"prediction.":[107],"prediction,":[112],"convolutional":[114],"neural":[115],"networks-bidirectional":[116],"gated":[117],"recurrent":[118],"unit":[119],"(CNN-BiGRU)":[120],"prediction":[122,210,269],"model":[123,141,178,198,211,270],"innovatively":[125],"constructed,":[126],"intelligent":[130],"calculation":[131],"\u2018prediction-judgment\u2019":[133],"successfully":[135],"realized.":[136],"The":[137,237],"output":[138],"can":[142],"accurately":[143],"prospectively":[145],"judge":[146],"conflict":[148,151,166,172,183,229,244,272],"situation":[149],"degree":[152],"between":[153,221,246],"any":[154],"two":[155],"trajectories,":[156],"provide":[158,279],"core":[159],"direct":[161],"technical":[162,282],"support":[163],"warning.":[167],"aspect":[170],"detection,":[173],"performance":[175],"effect":[181],"detection":[184,230,273],"are":[185],"fully":[186],"verified":[187],"by":[188],"simulation":[189],"experiments.":[190],"By":[191],"comparing":[192],"predicted":[194],"real":[201],"it":[204],"confirmed":[206],"that":[207,240],"CNN-BiGRU":[209],"has":[212],"high":[213],"accuracy":[214],"reliability":[216],"calculating":[218],"distance":[220],"aircraft.":[222],"At":[223],"same":[225],"time,":[226],"preset":[228],"further":[235],"results":[238],"show":[239],"there":[241],"no":[243],"manned":[251],"aircraft":[252],"during":[256],"full":[258],"800":[259],"s":[260],"terminal":[262],"area":[263],"flight.":[264],"summary,":[266],"proposed":[275],"guarantee":[283],"construction":[286],"an":[288],"active":[289],"accurate":[291],"security":[294],"management":[295,310],"control":[297],"system,":[298],"have":[300],"important":[301],"application":[302],"value":[303],"reference":[305],"significance":[306],"improving":[308],"efficiency":[311],"preventing":[313],"conflicts.":[315]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-02T00:00:00"}