{"id":"https://openalex.org/W7136240301","doi":"https://doi.org/10.1109/itsc60802.2025.11423495","title":"3D Indoor Pedestrian Route Choice Modeling Using Machine Learning-Based Wi-Fi Fingerprint Observations","display_name":"3D Indoor Pedestrian Route Choice Modeling Using Machine Learning-Based Wi-Fi Fingerprint Observations","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7136240301","doi":"https://doi.org/10.1109/itsc60802.2025.11423495"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (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/A5072056125","display_name":"Jingran Su","orcid":"https://orcid.org/0000-0002-9873-1770"},"institutions":[{"id":"https://openalex.org/I153327471","display_name":"Bunkyo University","ror":"https://ror.org/053h75930","country_code":"JP","type":"education","lineage":["https://openalex.org/I153327471"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jingran Su","raw_affiliation_strings":["The University of Tokyo,Department of Civil Engineering,Bunkyo,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Civil Engineering,Bunkyo,Tokyo,Japan","institution_ids":["https://openalex.org/I153327471","https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061487176","display_name":"Eiji Hato","orcid":"https://orcid.org/0000-0003-3932-7791"},"institutions":[{"id":"https://openalex.org/I153327471","display_name":"Bunkyo University","ror":"https://ror.org/053h75930","country_code":"JP","type":"education","lineage":["https://openalex.org/I153327471"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eiji Hato","raw_affiliation_strings":["The University of Tokyo,Department of Civil Engineering,Bunkyo,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo,Department of Civil Engineering,Bunkyo,Tokyo,Japan","institution_ids":["https://openalex.org/I153327471","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"172","last_page":"178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.5194000005722046,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.5194000005722046,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.2547999918460846,"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.029899999499320984,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/pedestrian","display_name":"Pedestrian","score":0.5846999883651733},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.48579999804496765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.30079999566078186},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.27459999918937683}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5846999883651733},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5703999996185303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5389000177383423},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5051000118255615},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.48579999804496765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.28369998931884766},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24130000174045563},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.23420000076293945}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6365212798118591,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1601795611","https://openalex.org/W1977822596","https://openalex.org/W2040870580","https://openalex.org/W2053180906","https://openalex.org/W2055264660","https://openalex.org/W2057094343","https://openalex.org/W2149706766","https://openalex.org/W2295598076","https://openalex.org/W2526606216","https://openalex.org/W2774684174","https://openalex.org/W2775990209","https://openalex.org/W2805987667","https://openalex.org/W2811148470","https://openalex.org/W2963539531","https://openalex.org/W2972355358","https://openalex.org/W3015310491","https://openalex.org/W3111423960","https://openalex.org/W4362454981","https://openalex.org/W4400762160"],"related_works":[],"abstract_inverted_index":{"Route":[0],"choice":[1,80],"modeling":[2],"is":[3],"an":[4],"essential":[5],"yet":[6],"challenging":[7],"problem":[8],"in":[9,52,73,134],"transportation":[10],"research.":[11],"Recently,":[12],"increasing":[13],"attention":[14],"has":[15],"been":[16],"devoted":[17],"to":[18,47,57],"three-dimensional":[19],"(3D)":[20],"indoor":[21,136],"pedestrian":[22,76,131],"behavior":[23],"analysis,":[24],"driven":[25],"by":[26],"its":[27],"importance":[28],"for":[29,78],"urban":[30],"design,":[31],"smart":[32],"building":[33],"operations,":[34],"and":[35,50,90,111,125],"emergency":[36],"evacuation":[37],"management.":[38],"However,":[39],"traditional":[40],"GPS-based":[41],"methods":[42],"are":[43,87],"unreliable":[44],"indoors":[45],"due":[46],"signal":[48],"degradation":[49],"difficulty":[51],"capturing":[53],"vertical":[54],"movements,":[55],"leading":[56],"the":[58],"growing":[59],"use":[60],"of":[61],"alternative":[62],"localization":[63],"signals":[64],"such":[65],"as":[66],"Wi-Fi":[67],"fingerprint":[68],"data.":[69],"Another":[70],"issue":[71],"lies":[72],"reconstructing":[74],"accurate":[75],"trajectories":[77],"route":[79,123],"analysis":[81,133],"based":[82],"on":[83],"these":[84],"signals,":[85],"which":[86],"often":[88],"sparse":[89],"noisy.":[91],"In":[92],"this":[93],"study,":[94],"we":[95],"develop":[96],"a":[97,105,112],"comprehensive":[98],"framework":[99],"integrating":[100],"ML-based":[101],"link-level":[102],"observation":[103],"models,":[104],"temporal":[106],"greedy":[107],"map":[108],"matching":[109],"algorithm,":[110],"weighted":[113],"recursive":[114],"logit":[115],"model.":[116],"The":[117],"proposed":[118],"approach":[119],"enables":[120],"robust":[121],"3D":[122],"reconstruction":[124],"extracts":[126],"interpretable":[127],"behavioral":[128],"parameters,":[129],"advancing":[130],"mobility":[132],"complex":[135],"environments.":[137]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-17T00:00:00"}
