{"id":"https://openalex.org/W4399407310","doi":"https://doi.org/10.1109/access.2024.3410316","title":"Feasibility Analysis of Applying Deep Neural Network on Driving Distance Estimation","display_name":"Feasibility Analysis of Applying Deep Neural Network on Driving Distance Estimation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399407310","doi":"https://doi.org/10.1109/access.2024.3410316"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3410316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3410316","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3410316","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067217362","display_name":"Sanghwan Lee","orcid":"https://orcid.org/0000-0001-8431-0097"},"institutions":[{"id":"https://openalex.org/I110273157","display_name":"Kookmin University","ror":"https://ror.org/0049erg63","country_code":"KR","type":"education","lineage":["https://openalex.org/I110273157"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghwan Lee","raw_affiliation_strings":["Department of Computer Science, Kookmin University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-8431-0097","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kookmin University, Seoul, South Korea","institution_ids":["https://openalex.org/I110273157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109742136","display_name":"Jinsoo Moon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinsoo Moon","raw_affiliation_strings":["m2Cloud Inc., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"m2Cloud Inc., Seoul, South Korea","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7009,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67882553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"81075","last_page":"81087"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9976000189781189,"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":0.9976000189781189,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7123342156410217},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6576088666915894},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5296036005020142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5097786784172058},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3232801556587219},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10746225714683533}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123342156410217},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6576088666915894},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5296036005020142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5097786784172058},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3232801556587219},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10746225714683533},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3410316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3410316","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:988b9e11e7114b3dbc348c096667e196","is_oa":true,"landing_page_url":"https://doaj.org/article/988b9e11e7114b3dbc348c096667e196","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":"IEEE Access, Vol 12, Pp 81075-81087 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3410316","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3410316","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1949835739","display_name":null,"funder_award_id":"22183MFDS436","funder_id":"https://openalex.org/F4320322014","funder_display_name":"Ministry of Food and Drug Safety"}],"funders":[{"id":"https://openalex.org/F4320322014","display_name":"Ministry of Food and Drug Safety","ror":"https://ror.org/01f7dp456"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2040971874","https://openalex.org/W2048485254","https://openalex.org/W2066270051","https://openalex.org/W2073515924","https://openalex.org/W2123847705","https://openalex.org/W2132483546","https://openalex.org/W2147800946","https://openalex.org/W2160815625","https://openalex.org/W2262276395","https://openalex.org/W2604319603","https://openalex.org/W2657631929","https://openalex.org/W2761908665","https://openalex.org/W2889079547","https://openalex.org/W2910952060","https://openalex.org/W2933852525","https://openalex.org/W3014801121","https://openalex.org/W3124000861","https://openalex.org/W3132191748","https://openalex.org/W3134751001","https://openalex.org/W3135807412","https://openalex.org/W3195565796","https://openalex.org/W3207097050","https://openalex.org/W4223510587","https://openalex.org/W4285594709","https://openalex.org/W4288027294","https://openalex.org/W4309760351","https://openalex.org/W6631190155","https://openalex.org/W6744998784","https://openalex.org/W6769932331","https://openalex.org/W6870515352"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"In":[0],"numerous":[1],"location-based":[2],"applications,":[3],"such":[4,47],"as":[5],"the":[6,23,35,44,66,116,133,136,172,175,181,194,209,219,226,229,237,240],"vehicular":[7],"routing":[8],"problem,":[9],"driving":[10,18,36,58,73],"distances":[11,19,241],"play":[12],"a":[13,152,205,215,243,251],"crucial":[14,129,244],"role.":[15],"However,":[16,81],"these":[17,94],"often":[20],"differ":[21],"from":[22],"direct":[24,76],"geographic":[25],"distance":[26,37,74,77,157,168,201,262],"computed":[27],"using":[28],"latitude":[29],"and":[30,60,75,170,277],"longitude.":[31],"Hence,":[32],"accurately":[33],"estimating":[34],"between":[38,72],"two":[39],"positions":[40],"is":[41,78],"vital":[42],"for":[43,88,109,123],"success":[45],"of":[46,135,174,208,218,228,239,258,269],"services.":[48],"Researchers":[49],"have":[50,98,213,234],"worked":[51],"on":[52],"developing":[53],"efficient":[54],"methods":[55,264],"to":[56,130,149,273],"estimate":[57],"distances,":[59],"it":[61,128],"has":[62],"been":[63],"reported":[64],"that":[65,184,193,223,236,255],"inflation":[67],"ratio":[68],"(or":[69],"detour":[70],"index)":[71],"approximately":[79],"1.3.":[80],"this":[82,145,270],"simple":[83],"method":[84,159,196],"may":[85,121],"not":[86],"suffice":[87],"complex":[89],"road":[90,111,125,155,220,260],"networks.":[91],"To":[92],"address":[93],"challenges,":[95],"other":[96],"researchers":[97],"proposed":[99],"deep":[100,117,137,153],"learning":[101,118],"based":[102,119,141],"approaches.":[103],"They":[104],"show":[105],"relatively":[106],"good":[107],"performance":[108,173,276],"real":[110,124],"data":[112,126,221],"sets.":[113],"Even":[114],"though":[115],"approach":[120],"work":[122],"sets,":[127],"fully":[131],"understand":[132],"behavior":[134],"neural":[138],"network":[139,156,261],"(DNN)":[140],"approach.":[142,177],"Therefore,":[143],"in":[144,246],"study,":[146],"We":[147],"aim":[148],"thoroughly":[150],"examine":[151],"learning-based":[154],"estimation":[158,263],"under":[160],"controlled":[161],"conditions.":[162],"Specifically,":[163,232],"we":[164,179,191,212,233,253],"define":[165],"five":[166],"different":[167],"types":[169],"assess":[171],"DNN-based":[176,195,230,259],"Subsequently,":[178],"analyze":[180],"key":[182,216],"factors":[183],"influence":[185],"its":[186],"performance.":[187],"Through":[188],"extensive":[189],"simulations,":[190],"demonstrate":[192],"performs":[197],"well":[198],"across":[199],"most":[200],"definitions.":[202],"After":[203],"conducting":[204],"thorough":[206],"analysis":[207],"evaluation":[210],"results,":[211],"identified":[214],"characteristic":[217],"sets":[222],"significantly":[224],"impacts":[225],"accuracy":[227],"method.":[231],"found":[235],"\u201cdiscontinuity\u201d":[238,271],"plays":[242],"role":[245],"achieving":[247],"high":[248],"accuracy.":[249,280],"As":[250],"result,":[252],"propose":[254],"future":[256],"designs":[257],"should":[265],"prioritize":[266],"careful":[267],"consideration":[268],"aspect":[272],"optimize":[274],"their":[275],"ensure":[278],"better":[279]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
