{"id":"https://openalex.org/W3084578038","doi":"https://doi.org/10.1109/tvt.2020.3023861","title":"Age of Information Aware Trajectory Planning of UAVs in Intelligent Transportation Systems: A Deep Learning Approach","display_name":"Age of Information Aware Trajectory Planning of UAVs in Intelligent Transportation Systems: A Deep Learning Approach","publication_year":2020,"publication_date":"2020-09-14","ids":{"openalex":"https://openalex.org/W3084578038","doi":"https://doi.org/10.1109/tvt.2020.3023861","mag":"3084578038"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2020.3023861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.3023861","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5109086141","display_name":"Moataz Samir","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Moataz Samir","raw_affiliation_strings":["Concordia University, Montr\u00e9al, QC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University, Montr\u00e9al, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072393948","display_name":"Chadi Assi","orcid":"https://orcid.org/0000-0002-3161-1846"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chadi Assi","raw_affiliation_strings":["Concordia University, Montr\u00e9al, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3161-1846","affiliations":[{"raw_affiliation_string":"Concordia University, Montr\u00e9al, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071725114","display_name":"Sanaa Sharafeddine","orcid":"https://orcid.org/0000-0001-6548-1624"},"institutions":[{"id":"https://openalex.org/I56306041","display_name":"Lebanese American University","ror":"https://ror.org/00hqkan37","country_code":"LB","type":"education","lineage":["https://openalex.org/I56306041"]}],"countries":["LB"],"is_corresponding":false,"raw_author_name":"Sanaa Sharafeddine","raw_affiliation_strings":["Lebanese American University, Beirut, Lebanon"],"raw_orcid":"https://orcid.org/0000-0001-6548-1624","affiliations":[{"raw_affiliation_string":"Lebanese American University, Beirut, Lebanon","institution_ids":["https://openalex.org/I56306041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022986816","display_name":"Dariush Ebrahimi","orcid":"https://orcid.org/0000-0003-2489-8858"},"institutions":[{"id":"https://openalex.org/I72541430","display_name":"Lakehead University","ror":"https://ror.org/023p7mg82","country_code":"CA","type":"education","lineage":["https://openalex.org/I72541430"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dariush Ebrahimi","raw_affiliation_strings":["Lakehead University, Thunder Bay, ON, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2489-8858","affiliations":[{"raw_affiliation_string":"Lakehead University, Thunder Bay, ON, Canada","institution_ids":["https://openalex.org/I72541430"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014049864","display_name":"Ali Ghrayeb","orcid":null},"institutions":[{"id":"https://openalex.org/I58152225","display_name":"Texas A&M University at Qatar","ror":"https://ror.org/03vb4dm14","country_code":"QA","type":"education","lineage":["https://openalex.org/I58152225","https://openalex.org/I91045830"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Ali Ghrayeb","raw_affiliation_strings":["Texas A and M University, Qatar, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0002-6808-5886","affiliations":[{"raw_affiliation_string":"Texas A and M University, Qatar, Doha, Qatar","institution_ids":["https://openalex.org/I58152225"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109086141"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":14.8915,"has_fulltext":false,"cited_by_count":193,"citation_normalized_percentile":{"value":0.99190329,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"69","issue":"11","first_page":"12382","last_page":"12395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":1.0,"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/T13553","display_name":"Age of Information Optimization","score":1.0,"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/T12079","display_name":"IoT Networks and Protocols","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.6955903172492981},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.676644504070282},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.671509861946106},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6315709948539734},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5636408925056458},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.46399471163749695},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4606059193611145},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.401965856552124},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3662523329257965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3342139422893524},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.20989400148391724},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1920158863067627}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6955903172492981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.676644504070282},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.671509861946106},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6315709948539734},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5636408925056458},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.46399471163749695},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4606059193611145},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.401965856552124},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3662523329257965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3342139422893524},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.20989400148391724},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1920158863067627},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2020.3023861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2020.3023861","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.49000000953674316}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321588","display_name":"Concordia University","ror":"https://ror.org/0420zvk78"},{"id":"https://openalex.org/F4320321747","display_name":"Fonds Qu\u00e9b\u00e9cois de la Recherche sur la Nature et les Technologies","ror":"https://ror.org/00b9f9778"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1757796397","https://openalex.org/W1955773994","https://openalex.org/W2000644019","https://openalex.org/W2005477504","https://openalex.org/W2034614500","https://openalex.org/W2062457326","https://openalex.org/W2103048107","https://openalex.org/W2108498890","https://openalex.org/W2121863487","https://openalex.org/W2125896931","https://openalex.org/W2132987094","https://openalex.org/W2170880416","https://openalex.org/W2173248099","https://openalex.org/W2460736120","https://openalex.org/W2588468001","https://openalex.org/W2625133885","https://openalex.org/W2754517384","https://openalex.org/W2768771208","https://openalex.org/W2791487310","https://openalex.org/W2796882881","https://openalex.org/W2897417898","https://openalex.org/W2922260520","https://openalex.org/W2925554975","https://openalex.org/W2945874132","https://openalex.org/W2961899294","https://openalex.org/W2962141687","https://openalex.org/W2962262066","https://openalex.org/W2962691117","https://openalex.org/W2963061782","https://openalex.org/W2963085502","https://openalex.org/W2963120839","https://openalex.org/W2963580658","https://openalex.org/W2973697444","https://openalex.org/W2982537683","https://openalex.org/W2999877931","https://openalex.org/W3007091509","https://openalex.org/W3022601977","https://openalex.org/W3101996971","https://openalex.org/W4205984110","https://openalex.org/W4298857966","https://openalex.org/W6637967152","https://openalex.org/W6641103747","https://openalex.org/W6744123322","https://openalex.org/W6755326576"],"related_works":["https://openalex.org/W2160425906","https://openalex.org/W2937181779","https://openalex.org/W1985560493","https://openalex.org/W1882733036","https://openalex.org/W1556532828","https://openalex.org/W1574991376","https://openalex.org/W2546696010","https://openalex.org/W1992741870","https://openalex.org/W4297782457","https://openalex.org/W2799840547"],"abstract_inverted_index":{"Unmanned":[0],"aerial":[1],"vehicles":[2,90],"(UAVs)":[3],"are":[4,42,98],"envisioned":[5],"to":[6,15,45,63,100,116,127,142,152,205,215,239,272],"play":[7],"a":[8,60,78,108,183],"key":[9],"role":[10],"in":[11,20,167,213,270],"intelligent":[12],"transportation":[13],"systems":[14],"complement":[16],"the":[17,34,47,50,119,129,157,176,189,194,207,233,236,242,251,254,259,266,274],"communication":[18],"infrastructure":[19],"future":[21],"smart":[22],"cities.":[23],"UAV-assisted":[24,79],"vehicular":[25,81,195,208],"networking":[26],"research":[27],"typically":[28],"adopts":[29],"throughput":[30,134],"and":[31,70,87,96,102,123,149,178,210,219,257],"latency":[32],"as":[33,59,67,182],"main":[35],"performance":[36],"metrics.":[37],"These":[38],"conventional":[39],"metrics,":[40],"however,":[41],"not":[43],"adequate":[44],"reflect":[46],"freshness":[48],"of":[49,111,121,159,235,253],"information,":[51],"an":[52],"attribute":[53],"that":[54],"has":[55],"been":[56],"recently":[57],"identified":[58],"critical":[61],"requirement":[62],"enable":[64],"services":[65],"such":[66],"autonomous":[68],"driving":[69],"accident":[71],"prevention.":[72],"In":[73,222],"this":[74,104],"paper,":[75],"we":[76,174,199,224],"consider":[77],"single-hop":[80],"network,":[82],"wherein":[83],"sensors":[84],"(e.g.,":[85],"LiDARs":[86],"cameras)":[88],"on":[89],"generate":[91],"time":[92],"sensitive":[93],"data":[94,105,267],"streams,":[95],"UAVs":[97,122,238,261],"used":[99],"collect":[101],"process":[103,186],"while":[106],"maintaining":[107],"minimum":[109,133],"age":[110],"information":[112,130],"(AoI).":[113],"We":[114],"aim":[115],"jointly":[117],"optimize":[118],"trajectories":[120,177,234],"find":[124],"scheduling":[125,179,220],"policies":[126,180],"keep":[128],"fresh":[131],"under":[132],"constraints.":[135],"The":[136],"formulated":[137],"optimization":[138],"problem":[139,181],"is":[140],"shown":[141],"be":[143,153],"mixed":[144],"integer":[145],"non-linear":[146],"program":[147],"(MINLP)":[148],"generally":[150],"hard":[151],"solved.":[154],"Motivated":[155],"by":[156],"success":[158],"machine":[160],"learning":[161,166,203,232],"(ML)":[162],"techniques":[163],"particularly":[164],"deep":[165,201],"solving":[168],"complex":[169],"problems":[170],"with":[171],"low":[172],"complexity,":[173],"reformulate":[175],"Markov":[184],"decision":[185],"(MDP)":[187],"where":[188],"system":[190],"state":[191],"space":[192],"considers":[193],"network":[196],"dynamics.":[197],"Then,":[198],"develop":[200],"reinforcement":[202],"(DRL)":[204],"learn":[206],"environment":[209],"its":[211],"dynamics":[212],"order":[214,271],"handle":[216],"UAVs'":[217],"trajectory":[218],"policy.":[221],"particular,":[223],"leverage":[225],"Deep":[226],"Deterministic":[227],"Policy":[228],"Gradient":[229],"(DDPG)":[230],"for":[231],"deployed":[237,260],"efficiently":[240],"minimize":[241,273],"Expected":[243],"Weighted":[244],"Sum":[245],"AoI":[246],"(EWSA).":[247],"Simulations":[248],"results":[249],"demonstrate":[250],"effectiveness":[252],"proposed":[255],"design":[256],"show":[258],"adapt":[262],"their":[263],"velocities":[264],"during":[265],"collection":[268],"mission":[269],"AoI.":[275]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":55},{"year":2023,"cited_by_count":43},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}
