{"id":"https://openalex.org/W2113739409","doi":"https://doi.org/10.1109/itsc.2013.6728265","title":"Motion pattern analysis enabling accurate travel mode detection from GPS data only","display_name":"Motion pattern analysis enabling accurate travel mode detection from GPS data only","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W2113739409","doi":"https://doi.org/10.1109/itsc.2013.6728265","mag":"2113739409"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2013.6728265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2013.6728265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","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/A5029433861","display_name":"Richard Brunauer","orcid":"https://orcid.org/0000-0001-7222-9638"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Richard Brunauer","raw_affiliation_strings":["Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria"],"affiliations":[{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","institution_ids":[]},{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022973038","display_name":"Michael Hufnagl","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Hufnagl","raw_affiliation_strings":["Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria"],"affiliations":[{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","institution_ids":[]},{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006223324","display_name":"Karl Rehrl","orcid":"https://orcid.org/0000-0003-4052-5867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karl Rehrl","raw_affiliation_strings":["Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria"],"affiliations":[{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","institution_ids":[]},{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064280180","display_name":"Andreas Wagner","orcid":"https://orcid.org/0000-0002-6000-3604"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andreas Wagner","raw_affiliation_strings":["Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria"],"affiliations":[{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH, Salzburg, Austria","institution_ids":[]},{"raw_affiliation_string":"Salzburg Research Forschungsgesellschaft mbH , Salzburg , Austria","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029433861"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.976,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.93356943,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"404","last_page":"411"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T11106","display_name":"Data Management and Algorithms","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.8579877614974976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.681960940361023},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.47830966114997864},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46957728266716003},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45948490500450134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45444947481155396},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44623124599456787},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.44338083267211914},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43671587109565735},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4247046113014221},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.375149667263031},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22357434034347534},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08048343658447266}],"concepts":[{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.8579877614974976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681960940361023},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.47830966114997864},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46957728266716003},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45948490500450134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45444947481155396},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44623124599456787},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.44338083267211914},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43671587109565735},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4247046113014221},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.375149667263031},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22357434034347534},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08048343658447266},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2013.6728265","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2013.6728265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8299999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W203848970","https://openalex.org/W206739251","https://openalex.org/W601032120","https://openalex.org/W1521536236","https://openalex.org/W1570448133","https://openalex.org/W1809001740","https://openalex.org/W1965106804","https://openalex.org/W1981039744","https://openalex.org/W1988115241","https://openalex.org/W1996285837","https://openalex.org/W2009155608","https://openalex.org/W2020642377","https://openalex.org/W2022749020","https://openalex.org/W2069249448","https://openalex.org/W2078920951","https://openalex.org/W2087327261","https://openalex.org/W2105046342","https://openalex.org/W2108328714","https://openalex.org/W2111120706","https://openalex.org/W2112006425","https://openalex.org/W2125055259","https://openalex.org/W2127127580","https://openalex.org/W2129480985","https://openalex.org/W2129857356","https://openalex.org/W2130578587","https://openalex.org/W2136317921","https://openalex.org/W2143364815","https://openalex.org/W2143394441","https://openalex.org/W2144485012","https://openalex.org/W2147693219","https://openalex.org/W2148217011","https://openalex.org/W4250857377","https://openalex.org/W4285719527","https://openalex.org/W6608254813","https://openalex.org/W6618102953","https://openalex.org/W6631341798","https://openalex.org/W6638487310","https://openalex.org/W6676424041","https://openalex.org/W6682044846"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2586280620","https://openalex.org/W2805505483","https://openalex.org/W2334071950","https://openalex.org/W2384744344","https://openalex.org/W4233932308","https://openalex.org/W1799694159","https://openalex.org/W2899848438","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Travel":[0],"modes":[1,52],"are":[2],"one":[3],"of":[4,8,20,42,142,168],"the":[5,50,74,119,126],"crucial":[6],"pieces":[7],"information":[9],"to":[10,38,48,71,79,125,132,158],"characterize":[11],"one's":[12],"travel":[13,170],"behavior.":[14],"In":[15,130],"recent":[16],"years":[17],"several":[18],"approaches":[19],"mode":[21,171],"detection":[22,97],"from":[23,65,99],"GPS":[24,144],"data":[25],"have":[26,147],"been":[27,148],"proposed.":[28],"The":[29,59,94],"approach":[30],"presented":[31],"in":[32,150],"this":[33,135],"paper":[34],"uses":[35,137],"machine":[36],"learning":[37],"evaluate":[39],"a":[40,138,159,165],"set":[41,77,141],"GPS-based":[43],"features":[44,61],"for":[45,117],"their":[46],"ability":[47],"recognize":[49],"common":[51],"walk,":[53],"bicycle,":[54],"car,":[55],"bus,":[56],"and":[57,105,109,152],"train.":[58],"proposed":[60,75],"describe":[62],"motion":[63],"characteristics":[64],"GPS-trajectories":[66],"by":[67,112],"relative":[68],"frequencies.":[69],"Compared":[70],"previous":[72],"work":[73],"feature":[76,115,122],"leads":[78],"higher":[80,160],"average":[81],"recognition":[82],"rates":[83,98],"around":[84],"92%":[85],"without":[86],"relying":[87],"on":[88],"additional":[89],"GIS":[90],"or":[91],"real-time":[92],"information.":[93],"evaluation":[95],"compares":[96],"multilayer":[100],"perceptrons,":[101],"logistic":[102],"model":[103],"trees,":[104],"C4.5":[106],"decision":[107],"trees":[108],"is":[110],"complemented":[111],"an":[113],"evolutionary":[114],"selection":[116],"selecting":[118],"most":[120],"beneficial":[121],"subsets":[123],"leading":[124],"best":[127],"quality":[128],"gain.":[129],"contrast":[131],"other":[133],"research,":[134],"study":[136],"comparatively":[139],"large":[140],"400":[143],"trajectories":[145],"which":[146],"recorded":[149],"rural":[151],"urban":[153],"European":[154],"areas.":[155],"Results":[156],"contribute":[157],"reliability":[161],"as":[162,164],"well":[163],"broader":[166],"applicability":[167],"GPS-only":[169],"detection.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}