{"id":"https://openalex.org/W3200482837","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533456","title":"ZED-TTE: Zone Embedding and Deep Neural Network based Travel Time Estimation Approach","display_name":"ZED-TTE: Zone Embedding and Deep Neural Network based Travel Time Estimation Approach","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200482837","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533456","mag":"3200482837"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5068897535","display_name":"Chahinez Ounoughi","orcid":"https://orcid.org/0000-0002-2063-2844"},"institutions":[{"id":"https://openalex.org/I108714496","display_name":"Tunis University","ror":"https://ror.org/02q1spa57","country_code":"TN","type":"education","lineage":["https://openalex.org/I108714496"]},{"id":"https://openalex.org/I111112146","display_name":"Tallinn University of Technology","ror":"https://ror.org/0443cwa12","country_code":"EE","type":"education","lineage":["https://openalex.org/I111112146"]},{"id":"https://openalex.org/I63596082","display_name":"Tunis El Manar University","ror":"https://ror.org/029cgt552","country_code":"TN","type":"education","lineage":["https://openalex.org/I63596082"]}],"countries":["EE","TN"],"is_corresponding":false,"raw_author_name":"Chahinez Ounoughi","raw_affiliation_strings":["Tallinn University of Technology, Tallinn, Estonia","Universit\u00e9 de Tunis El Manar Facult\u00e9 des Sciences de Tunis LR11ES14, Tunis, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tallinn University of Technology, Tallinn, Estonia","institution_ids":["https://openalex.org/I111112146"]},{"raw_affiliation_string":"Universit\u00e9 de Tunis El Manar Facult\u00e9 des Sciences de Tunis LR11ES14, Tunis, Tunisia","institution_ids":["https://openalex.org/I108714496","https://openalex.org/I63596082"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068456361","display_name":"Taoufik Yeferny","orcid":"https://orcid.org/0000-0003-4600-8131"},"institutions":[{"id":"https://openalex.org/I108714496","display_name":"Tunis University","ror":"https://ror.org/02q1spa57","country_code":"TN","type":"education","lineage":["https://openalex.org/I108714496"]},{"id":"https://openalex.org/I63596082","display_name":"Tunis El Manar University","ror":"https://ror.org/029cgt552","country_code":"TN","type":"education","lineage":["https://openalex.org/I63596082"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Taoufik Yeferny","raw_affiliation_strings":["Universit\u00e9 de Tunis El Manar Facult\u00e9 des Sciences de Tunis LR11ES14, Tunis, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Tunis El Manar Facult\u00e9 des Sciences de Tunis LR11ES14, Tunis, Tunisia","institution_ids":["https://openalex.org/I108714496","https://openalex.org/I63596082"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070511935","display_name":"Sadok Ben Yahia","orcid":"https://orcid.org/0000-0001-8939-8948"},"institutions":[{"id":"https://openalex.org/I111112146","display_name":"Tallinn University of Technology","ror":"https://ror.org/0443cwa12","country_code":"EE","type":"education","lineage":["https://openalex.org/I111112146"]}],"countries":["EE"],"is_corresponding":false,"raw_author_name":"Sadok Ben Yahia","raw_affiliation_strings":["Tallinn University of Technology, Tallinn, Estonia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tallinn University of Technology, Tallinn, Estonia","institution_ids":["https://openalex.org/I111112146"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3645,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59681605,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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":0.9993000030517578,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9991000294685364,"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":0.7313747406005859},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7277978658676147},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6088300347328186},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.533251941204071},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4963279366493225},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4937375485897064},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4570583701133728},{"id":"https://openalex.org/keywords/travel-time","display_name":"Travel time","score":0.4413938820362091},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.42502737045288086},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4147488474845886},{"id":"https://openalex.org/keywords/trips-architecture","display_name":"TRIPS architecture","score":0.41073575615882874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3765505850315094},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3666437864303589},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3449832797050476},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2261551320552826},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1803187131881714},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10590636730194092},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09705314040184021},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09248948097229004},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0842481255531311}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7313747406005859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7277978658676147},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6088300347328186},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.533251941204071},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4963279366493225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4937375485897064},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4570583701133728},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.4413938820362091},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.42502737045288086},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4147488474845886},{"id":"https://openalex.org/C157085824","wikidata":"https://www.wikidata.org/wiki/Q2384809","display_name":"TRIPS architecture","level":2,"score":0.41073575615882874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3765505850315094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3666437864303589},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3449832797050476},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2261551320552826},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1803187131881714},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10590636730194092},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09705314040184021},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09248948097229004},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0842481255531311},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/ijcnn52387.2021.9533456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2004774614","https://openalex.org/W2016287239","https://openalex.org/W2049503088","https://openalex.org/W2616536158","https://openalex.org/W2788997482","https://openalex.org/W2789371837","https://openalex.org/W2790680701","https://openalex.org/W2809128166","https://openalex.org/W2889793454","https://openalex.org/W2907138842","https://openalex.org/W2912462370","https://openalex.org/W2919295905","https://openalex.org/W2921000573","https://openalex.org/W2942121324","https://openalex.org/W2946563989","https://openalex.org/W2962834725","https://openalex.org/W2964121744","https://openalex.org/W2966819461","https://openalex.org/W2970079819","https://openalex.org/W2972581457","https://openalex.org/W2976168788","https://openalex.org/W2976882027","https://openalex.org/W2978273467","https://openalex.org/W2984598834","https://openalex.org/W2993170525","https://openalex.org/W2999798734","https://openalex.org/W3004018578","https://openalex.org/W3005353079","https://openalex.org/W3102435039","https://openalex.org/W3103553187","https://openalex.org/W3106295757","https://openalex.org/W4246587917","https://openalex.org/W6631190155","https://openalex.org/W6748397481"],"related_works":["https://openalex.org/W2807758032","https://openalex.org/W2152103536","https://openalex.org/W4224254130","https://openalex.org/W3048948123","https://openalex.org/W413879896","https://openalex.org/W1983530038","https://openalex.org/W3088340659","https://openalex.org/W2972374246","https://openalex.org/W3205006318","https://openalex.org/W4293174494"],"abstract_inverted_index":{"Travel":[0,84],"time":[1,30,129],"estimation":[2],"is":[3,24,37,95],"an":[4],"important":[5],"dynamic":[6],"measure":[7],"in":[8],"developing":[9],"mobility":[10],"on":[11,58,154],"the":[12,29,60,66,93,99,121,127,131,163,168],"road":[13,50,100,148],"navigation":[14],"services":[15],"of":[16,46,92,120],"Intelligent":[17],"Transportation":[18],"System":[19],"(ITS).":[20],"The":[21,89],"key":[22],"challenge":[23],"how":[25],"to":[26,124],"accurately":[27],"assess":[28],"required":[31],"for":[32,64,106,130],"a":[33,43,74,117,137,140],"given":[34],"path":[35],"that":[36,96,162],"extensively":[38],"varied":[39],"and":[40,49,80,111,139],"affected":[41],"by":[42,134],"wealthy":[44],"number":[45],"spatial,":[47],"temporal,":[48],"conditions":[51],"factors.":[52],"However,":[53],"former":[54],"works":[55],"have":[56],"focused":[57],"capturing":[59],"local":[61],"trajectory":[62,144],"patterns":[63],"reducing":[65],"model's":[67],"accuracy.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"introduce":[73],"novel":[75],"approach":[76,165],"called":[77],"Zone":[78],"Embedding":[79],"Deep":[81],"Neural":[82],"Network-based":[83],"Time":[85],"Estimation":[86],"Approach":[87],"(ZED-TTE).":[88],"main":[90],"originality":[91],"latter":[94],"it":[97,115],"summarizes":[98],"network":[101],"into":[102],"several":[103],"meaningful":[104],"zones":[105],"extracting":[107],"global":[108,122],"spatial":[109],"correlations":[110],"temporal":[112],"dependencies.":[113],"Thus,":[114],"has":[116],"better":[118],"overview":[119],"picture":[123],"efficiently":[125],"gauge":[126],"travel":[128],"full":[132],"path,":[133],"directly":[135],"providing":[136],"source":[138],"destination":[141],"without":[142],"intermediate":[143],"points":[145],"involving":[146],"some":[147],"external":[149],"conditions.":[150],"Experiments":[151],"carried":[152],"out":[153],"two":[155],"large-scale":[156],"real-world":[157],"taxi":[158],"trips":[159],"datasets":[160],"show":[161],"proposed":[164],"sharply":[166],"outperforms":[167],"state-of-the-art":[169],"models.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
