{"id":"https://openalex.org/W2124984887","doi":"https://doi.org/10.1109/itsc.2008.4732700","title":"Towards a Driver Model: Preliminary Study of Lane Change Behavior","display_name":"Towards a Driver Model: Preliminary Study of Lane Change Behavior","publication_year":2008,"publication_date":"2008-10-01","ids":{"openalex":"https://openalex.org/W2124984887","doi":"https://doi.org/10.1109/itsc.2008.4732700","mag":"2124984887"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2008.4732700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2008.4732700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 11th International IEEE Conference on Intelligent Transportation Systems","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/A5008172097","display_name":"U. Dogan","orcid":null},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ueruen Dogan","raw_affiliation_strings":["Institut f\u00fc Neuroinformatik, Ruhr Universit\u00e4t Bochum, Bochum, Germany","Inst. fur Neuroinformatik, Ruhr-Univ. Bochum, Bochum"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut f\u00fc Neuroinformatik, Ruhr Universit\u00e4t Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]},{"raw_affiliation_string":"Inst. fur Neuroinformatik, Ruhr-Univ. Bochum, Bochum","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055318790","display_name":"H. Edelbrunner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hannes Edelbrunner","raw_affiliation_strings":["Technology Center Ruhr, NISYS GmbH, Bochum, Germany","NISYS GmbH, Technol. Center Ruhr, Bochum"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technology Center Ruhr, NISYS GmbH, Bochum, Germany","institution_ids":[]},{"raw_affiliation_string":"NISYS GmbH, Technol. Center Ruhr, Bochum","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084075127","display_name":"Ioannis Iossifidis","orcid":"https://orcid.org/0000-0002-9876-4396"},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ioannis Iossifidis","raw_affiliation_strings":["Institut f\u00fc Neuroinformatik, Ruhr Universit\u00e4t Bochum, Bochum, Germany","Inst. fur Neuroinformatik, Ruhr-Univ. Bochum, Bochum"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut f\u00fc Neuroinformatik, Ruhr Universit\u00e4t Bochum, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]},{"raw_affiliation_string":"Inst. fur Neuroinformatik, Ruhr-Univ. Bochum, Bochum","institution_ids":["https://openalex.org/I904495901"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9172,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.93122363,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"931","last_page":"937"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.790674090385437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7123502492904663},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6465508341789246},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5260474681854248},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.4827636778354645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4623689651489258},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4382195472717285},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4197882413864136},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.4118083417415619},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3696863651275635},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32142943143844604}],"concepts":[{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.790674090385437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123502492904663},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6465508341789246},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5260474681854248},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.4827636778354645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4623689651489258},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4382195472717285},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4197882413864136},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.4118083417415619},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3696863651275635},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32142943143844604},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/itsc.2008.4732700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2008.4732700","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 11th International IEEE Conference on Intelligent Transportation Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.874.9647","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.874.9647","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://www.researchgate.net/profile/Ioannis_Iossifidis/publication/224364986_Towards_a_Driver_Model_Preliminary_Study_of_Lane_Change_Behavior/links/09e4151065b9d28526000000.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1518969363","https://openalex.org/W1560724230","https://openalex.org/W1602265563","https://openalex.org/W1755734830","https://openalex.org/W1973058638","https://openalex.org/W2002011878","https://openalex.org/W2076944915","https://openalex.org/W2110485445","https://openalex.org/W2111204826","https://openalex.org/W2114528843","https://openalex.org/W2115557648","https://openalex.org/W2119821739","https://openalex.org/W2121553911","https://openalex.org/W2124776405","https://openalex.org/W2131076267","https://openalex.org/W2149748474","https://openalex.org/W2162419813","https://openalex.org/W2163541453","https://openalex.org/W2167615167","https://openalex.org/W2168382721","https://openalex.org/W4239510810","https://openalex.org/W6676391964","https://openalex.org/W6684678765"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2073313993"],"abstract_inverted_index":{"The":[0,90,136],"presented":[1],"work":[2],"formulates":[3],"an":[4],"framework":[5,141],"in":[6,28,66,98],"which":[7,147],"early":[8],"prediction":[9,130],"of":[10,23,50,53,112,125,132],"drivers":[11,24],"lane":[12,25,75,128],"change":[13,26,76,129],"behavior":[14,27],"is":[15],"realized.":[16],"We":[17],"aim":[18],"to":[19,30,33,80,86,95],"build":[20],"a":[21,38,42,100,104,110,127,140,151,154],"representation":[22],"order":[29],"recognize":[31],"and":[32,69,84,109,145],"predict":[34],"driver's":[35],"intentions":[36],"as":[37,150],"first":[39],"step":[40],"towards":[41],"realistic":[43],"driver":[44,156],"model.":[45,157],"In":[46,116],"the":[47,51,57,67,81,117,121],"test":[48,119],"bed":[49],"Institute":[52],"Neuroinformatik,":[54],"based":[55],"on":[56],"traffic":[58],"simulator":[59],"NISYS":[60],"TRS1,":[61],"10":[62],"individuals":[63],"have":[64],"driven":[65],"experiments":[68],"they":[70],"performed":[71],"more":[72],"then":[73],"150":[74],"maneuvers.":[77],"Lane-offset,":[78],"distance":[79],"front":[82],"car":[83],"time":[85,131],"contact,":[87],"were":[88],"recorded.":[89],"acquired":[91],"data":[92],"was":[93,123],"used":[94],"train":[96],"-":[97],"parallel-":[99],"recurrent":[101],"neural":[102,107],"network,":[103],"feed":[105],"forward":[106],"network":[108],"set":[111],"support":[113],"vector":[114],"machines.":[115],"followed":[118],"drives":[120],"system":[122],"able":[124],"performing":[126],"1.5":[133],"sec":[134],"beforehand.":[135],"proposed":[137],"approach":[138],"describes":[139],"for":[142,153],"lane-change":[143],"detection":[144],"prediction,":[146],"will":[148],"serve":[149],"prerequisite":[152],"successful":[155]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}