{"id":"https://openalex.org/W3013701719","doi":"https://doi.org/10.1080/13658816.2020.1740999","title":"Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories","display_name":"Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories","publication_year":2020,"publication_date":"2020-03-23","ids":{"openalex":"https://openalex.org/W3013701719","doi":"https://doi.org/10.1080/13658816.2020.1740999","mag":"3013701719"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2020.1740999","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2020.1740999","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","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/A5006223324","display_name":"Karl Rehrl","orcid":"https://orcid.org/0000-0003-4052-5867"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Karl Rehrl","raw_affiliation_strings":["Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria"],"raw_orcid":"https://orcid.org/0000-0003-4052-5867","affiliations":[{"raw_affiliation_string":"Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038692436","display_name":"Simon Gr\u00f6chenig","orcid":"https://orcid.org/0000-0003-3546-1627"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Simon Gr\u00f6chenig","raw_affiliation_strings":["Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria"],"raw_orcid":"https://orcid.org/0000-0003-3546-1627","affiliations":[{"raw_affiliation_string":"Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003056802","display_name":"Stefan Kranzinger","orcid":"https://orcid.org/0000-0002-4014-7846"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Stefan Kranzinger","raw_affiliation_strings":["Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria"],"raw_orcid":"https://orcid.org/0000-0002-4014-7846","affiliations":[{"raw_affiliation_string":"Mobility & Transport Analytics, Salzburg Research, Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006223324"],"corresponding_institution_ids":["https://openalex.org/I182212641"],"apc_list":null,"apc_paid":null,"fwci":0.7424,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.6910695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"34","issue":"10","first_page":"1953","last_page":"1979"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11719","display_name":"Data Quality and Management","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7599170207977295},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6475350856781006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6323362588882446},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.592679500579834},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5821813941001892},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5192192196846008},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5182780623435974},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.514754056930542},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4675072133541107},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4284828007221222},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42683807015419006}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7599170207977295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6475350856781006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323362588882446},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.592679500579834},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5821813941001892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5192192196846008},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5182780623435974},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.514754056930542},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4675072133541107},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4284828007221222},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42683807015419006},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/13658816.2020.1740999","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2020.1740999","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},{"id":"pmh:oai:research.wu.ac.at:openaire_cris_publications/0c8c3867-ec13-4799-b52e-c72a7653decb","is_oa":false,"landing_page_url":"https://research.wu.ac.at/de/publications/0c8c3867-ec13-4799-b52e-c72a7653decb","pdf_url":null,"source":{"id":"https://openalex.org/S7407055123","display_name":"WU Research","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Rehrl, K, Kranzinger, S & Gr\u00f6chenig, S 2020, 'Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories', International Journal of Geographical Information Science, vol. 34, no. 10. https://doi.org/10.1080/13658816.2020.1740999","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:share.osf.io:E010A-5D0-148","is_oa":false,"landing_page_url":"http://api.osf.io/v2/nodes/cqsr8/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401127","display_name":"OSF Preprints (OSF Preprints)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2799848540","host_organization_name":"Center for Open Science","host_organization_lineage":["https://openalex.org/I2799848540"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"project"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W381257294","https://openalex.org/W1513618424","https://openalex.org/W1521843029","https://openalex.org/W1678356000","https://openalex.org/W1809873675","https://openalex.org/W1967495148","https://openalex.org/W1975846642","https://openalex.org/W1980649904","https://openalex.org/W1985258161","https://openalex.org/W1988790447","https://openalex.org/W1995341919","https://openalex.org/W2002199299","https://openalex.org/W2008559906","https://openalex.org/W2009155608","https://openalex.org/W2012580531","https://openalex.org/W2047100010","https://openalex.org/W2053154970","https://openalex.org/W2067193733","https://openalex.org/W2072106293","https://openalex.org/W2096451472","https://openalex.org/W2104634417","https://openalex.org/W2109182426","https://openalex.org/W2109553965","https://openalex.org/W2116079122","https://openalex.org/W2125697820","https://openalex.org/W2135293965","https://openalex.org/W2148143831","https://openalex.org/W2149308034","https://openalex.org/W2151387597","https://openalex.org/W2155653793","https://openalex.org/W2158698691","https://openalex.org/W2164777277","https://openalex.org/W2295598076","https://openalex.org/W2338471116","https://openalex.org/W2500341640","https://openalex.org/W2560674852","https://openalex.org/W2582743722","https://openalex.org/W2615831413","https://openalex.org/W2620760558","https://openalex.org/W2765303224","https://openalex.org/W2768871299","https://openalex.org/W2789825783","https://openalex.org/W2804957041","https://openalex.org/W2911964244","https://openalex.org/W2938524560","https://openalex.org/W2987883775","https://openalex.org/W3004732066","https://openalex.org/W3102476541","https://openalex.org/W4212883601","https://openalex.org/W4255136483","https://openalex.org/W4285719527","https://openalex.org/W4302187655","https://openalex.org/W4385400191","https://openalex.org/W6761450353","https://openalex.org/W6769764061","https://openalex.org/W6869608176"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W4248382324","https://openalex.org/W4360995134","https://openalex.org/W2387529410","https://openalex.org/W2039473718","https://openalex.org/W3023605104","https://openalex.org/W2383578611","https://openalex.org/W2987583674","https://openalex.org/W3186928667"],"abstract_inverted_index":{"Trajectory":[0,15],"data":[1,13,93,175],"mining":[2,17,24,94,122,176],"is":[3,62,166],"a":[4,19,33,59,88,143],"lively":[5],"research":[6],"field":[7],"in":[8,104,112,130],"the":[9,36,46,56,71,97,114,120,163],"domain":[10],"of":[11,21,52,73,101,146],"spatio-temporal":[12,43],"mining.":[14],"pattern":[16,23],"comprises":[18],"set":[20],"specific":[22],"methods,":[25],"which":[26],"are":[27],"applied":[28,115],"as":[29,107,170],"consecutive":[30],"steps":[31,123],"on":[32],"trajectory":[34,92,174],"with":[35,117,150],"goal":[37],"to":[38,70,119,159,168],"extract":[39],"and":[40,49,86,99,128,132,135],"classify":[41],"re-occurring":[42],"patterns.":[44],"Despite":[45],"common":[47],"nature":[48],"frequent":[50],"usage":[51],"such":[53],"methods":[54],"by":[55,84],"GIScience":[57],"community,":[58],"methodological":[60],"approach":[61],"missing":[63],"so":[64],"far,":[65],"especially":[66],"when":[67],"it":[68],"comes":[69],"use":[72],"machine":[74,89,138],"learning-based":[75,90,139],"classification":[76,100,140],"methods.":[77],"The":[78,109],"current":[79],"work":[80,110],"closes":[81],"this":[82],"gap":[83],"proposing":[85],"evaluating":[87],"3-steps":[91],"methodology":[95,165],"using":[96,142],"detection":[98],"stop":[102],"points":[103],"vehicle":[105,148],"trajectories":[106,149],"example.":[108],"describes":[111],"detail":[113],"methodologies":[116],"respect":[118],"three":[121],"\u2018stop":[124],"detection\u2019,":[125],"\u2018feature":[126],"extraction\u2019":[127],"\u2018classification":[129],"traffic-relevant":[131],"non-traffic-relevant":[133],"stops\u2019":[134],"evaluates":[136],"six":[137],"algorithms":[141],"real-world":[144],"dataset":[145],"15,498":[147],"5,899":[151],"detected":[152],"stops":[153],"(thereof":[154],"2,032":[155],"manually":[156],"classified).":[157],"Due":[158],"its":[160],"exemplary":[161],"nature,":[162],"presented":[164],"suited":[167],"act":[169],"blueprint":[171],"for":[172],"similar":[173],"problems.":[177]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
