{"id":"https://openalex.org/W3209823822","doi":"https://doi.org/10.1109/itsc48978.2021.9564900","title":"TQAM: Temporal Attention for Cycle-wise Queue Length Estimation using High-Resolution Loop Detector Data","display_name":"TQAM: Temporal Attention for Cycle-wise Queue Length Estimation using High-Resolution Loop Detector Data","publication_year":2021,"publication_date":"2021-09-19","ids":{"openalex":"https://openalex.org/W3209823822","doi":"https://doi.org/10.1109/itsc48978.2021.9564900","mag":"3209823822"},"language":"en","primary_location":{"id":"doi:10.1109/itsc48978.2021.9564900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","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/A5036781787","display_name":"Rahul Sengupta","orcid":"https://orcid.org/0000-0001-9793-5176"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rahul Sengupta","raw_affiliation_strings":["University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037977602","display_name":"Yashaswi Karnati","orcid":"https://orcid.org/0000-0002-2512-1250"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yashaswi Karnati","raw_affiliation_strings":["University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059870257","display_name":"Anand Rangarajan","orcid":"https://orcid.org/0000-0001-8695-8436"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand Rangarajan","raw_affiliation_strings":["University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077570468","display_name":"Sanjay Ranka","orcid":"https://orcid.org/0000-0003-4886-1988"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanjay Ranka","raw_affiliation_strings":["University of Florida"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.2713,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.43129327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3313","last_page":"3320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10138","display_name":"Network Traffic and Congestion Control","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9954000115394592,"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/T10974","display_name":"Advanced Queuing Theory Analysis","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7007740139961243},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.6664929389953613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6535787582397461},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.6056692004203796},{"id":"https://openalex.org/keywords/phase-locked-loop","display_name":"Phase-locked loop","score":0.5428680181503296},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5065046548843384},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4249309003353119},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3496682643890381},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18174195289611816},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1449066400527954},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13736963272094727},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10413694381713867},{"id":"https://openalex.org/keywords/jitter","display_name":"Jitter","score":0.08467927575111389}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7007740139961243},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.6664929389953613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535787582397461},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.6056692004203796},{"id":"https://openalex.org/C12707504","wikidata":"https://www.wikidata.org/wiki/Q52637","display_name":"Phase-locked loop","level":3,"score":0.5428680181503296},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5065046548843384},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4249309003353119},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3496682643890381},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18174195289611816},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1449066400527954},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13736963272094727},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10413694381713867},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.08467927575111389},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc48978.2021.9564900","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc48978.2021.9564900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G7700432364","display_name":"SCC: Video Based Machine Learning for Smart Traffic Analysis and Management","funder_award_id":"1922782","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W75399273","https://openalex.org/W645946133","https://openalex.org/W821435292","https://openalex.org/W1858032223","https://openalex.org/W2013009562","https://openalex.org/W2016589492","https://openalex.org/W2042388588","https://openalex.org/W2064675550","https://openalex.org/W2088252337","https://openalex.org/W2095797625","https://openalex.org/W2098567572","https://openalex.org/W2130942839","https://openalex.org/W2133292407","https://openalex.org/W2156271471","https://openalex.org/W2157331557","https://openalex.org/W2530867817","https://openalex.org/W2901504064","https://openalex.org/W2903709398","https://openalex.org/W2936783042","https://openalex.org/W2941531368","https://openalex.org/W2944614423","https://openalex.org/W2963403868","https://openalex.org/W2970971581","https://openalex.org/W2982001275","https://openalex.org/W2982974789","https://openalex.org/W3103161491","https://openalex.org/W3103720336","https://openalex.org/W3125445645","https://openalex.org/W3210806956","https://openalex.org/W4288375408","https://openalex.org/W4295312788","https://openalex.org/W4385245566","https://openalex.org/W6620976923","https://openalex.org/W6661257171","https://openalex.org/W6674344953","https://openalex.org/W6679436768","https://openalex.org/W6728147721","https://openalex.org/W6739901393","https://openalex.org/W6761837902","https://openalex.org/W6762527370","https://openalex.org/W6766978945","https://openalex.org/W6785773631"],"related_works":["https://openalex.org/W1576949837","https://openalex.org/W4360861688","https://openalex.org/W3134930219","https://openalex.org/W984417604","https://openalex.org/W2967785526","https://openalex.org/W2908000842","https://openalex.org/W2065391525","https://openalex.org/W2113001378","https://openalex.org/W2353997301","https://openalex.org/W4311152761"],"abstract_inverted_index":{"Queue":[0],"Length":[1],"Estimation":[2],"along":[3,165],"urban":[4],"arterials":[5],"is":[6,48],"vital":[7],"to":[8,22,51,93,201],"city":[9],"traffic":[10,52,95,126,177,187,212],"planners":[11],"for":[12,61],"calculating":[13],"\u2018Level":[14],"of":[15,110,151,157,211,221],"Service\u2019":[16],"measures":[17],"and":[18,57,73,99,107,204,232],"optimizing":[19],"signal":[20],"plans":[21],"alleviate":[23],"congestion.":[24],"While":[25],"several":[26],"data":[27,200],"sources":[28],"such":[29],"as":[30,89],"GPS,":[31],"Video,":[32],"Bluetooth,":[33],"DSRC":[34],"etc.":[35],"are":[36,87,91,130,149],"now":[37],"available,":[38],"we":[39,143,179],"focus":[40],"exclusively":[41],"on":[42,66,133],"high-resolution":[43],"loop":[44,193],"detector":[45,81,97,162,194],"data,":[46],"which":[47,121],"widely":[49],"available":[50],"authorities":[53],"in":[54,79],"North":[55],"America":[56],"elsewhere.":[58],"Analytical":[59],"methods":[60,86],"queue":[62,123,206],"length":[63],"estimation":[64],"rely":[65],"counting":[67],"input-output":[68],"vehicle":[69],"flows":[70],"over":[71,237],"advance":[72],"stop-bar":[74],"detectors":[75],"or":[76],"identifying":[77],"breakpoints":[78],"the":[80,108,158,215,219],"actuation":[82,163],"waveforms.":[83],"However,":[84],"these":[85],"limited,":[88],"they":[90],"sensitive":[92],"assumed":[94],"parameters,":[96],"placement":[98],"do":[100],"not":[101],"take":[102],"into":[103],"account":[104],"driving":[105],"behaviors":[106],"effect":[109],"left-turn":[111,172],"buffers.":[112],"More":[113],"recently,":[114],"Machine":[115],"Learning":[116],"models":[117],"have":[118],"been":[119],"developed":[120],"learn":[122],"lengths":[124,207],"from":[125,161,190],"state":[127],"data.":[128],"These":[129],"usually":[131],"trained":[132,228],"localized":[134],"datasets":[135],"at":[136,214],"coarse":[137],"time":[138],"resolutions.":[139],"In":[140],"this":[141],"work,":[142],"show":[144,233],"that":[145],"Deep":[146],"Neural":[147,240],"Networks":[148],"capable":[150],"directly":[152],"learning":[153],"an":[154,166,170],"abstract":[155],"representation":[156],"queuing":[159],"process,":[160],"waveforms":[164],"intersection":[167],"approach":[168],"with":[169,225],"exclusive":[171],"buffer.":[173],"Using":[174],"a":[175,181,191,209],"microscopic":[176],"simulator,":[178],"generate":[180],"large":[182],"dataset":[183],"by":[184],"approximately":[185],"replicating":[186],"arrival":[188],"patterns":[189],"realworld":[192],"dataset.":[195],"We":[196,217],"then":[197],"feed":[198],"multi-cycle":[199],"compute":[202],"maximum":[203],"residual":[205],"across":[208],"range":[210],"conditions,":[213],"cycle-level.":[216],"explore":[218],"use":[220],"lightweight":[222],"Encoder-Decoder":[223],"architectures":[224],"Temporal":[226],"Attention,":[227],"using":[229],"teacher-forcing":[230],"strategy,":[231],"their":[234],"superior":[235],"performance":[236],"regular":[238],"Feed-Forward":[239],"Networks.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
