{"id":"https://openalex.org/W2014214764","doi":"https://doi.org/10.1109/icves.2012.6294301","title":"Impact of driving context on stochastic driver-behavior model: Quantitative analysis of car following task","display_name":"Impact of driving context on stochastic driver-behavior model: Quantitative analysis of car following task","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2014214764","doi":"https://doi.org/10.1109/icves.2012.6294301","mag":"2014214764"},"language":"en","primary_location":{"id":"doi:10.1109/icves.2012.6294301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves.2012.6294301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012)","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/A5026807873","display_name":"Pongtep Angkititrakul","orcid":"https://orcid.org/0000-0001-9739-2052"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Pongtep Angkititrakul","raw_affiliation_strings":["Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","Department of Media Science, Nagoya University, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"Department of Media Science, Nagoya University, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108524583","display_name":"Chiyomi Miyajima","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chiyomi Miyajima","raw_affiliation_strings":["Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","Department of Media Science, Nagoya University, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"Department of Media Science, Nagoya University, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042118446","display_name":"Kazuya Takeda","orcid":"https://orcid.org/0000-0002-0330-1787"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuya Takeda","raw_affiliation_strings":["Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","Department of Media Science, Nagoya University, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Media Science, University of Nagoya, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"Department of Media Science, Nagoya University, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026807873"],"corresponding_institution_ids":["https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":0.4281,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.70915492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9975000023841858,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9975000023841858,"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":0.9873999953269958,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9674000144004822,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.823794424533844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.609342098236084},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5862748622894287},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5795788764953613},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.5604798197746277},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.5528181195259094},{"id":"https://openalex.org/keywords/stochastic-modelling","display_name":"Stochastic modelling","score":0.4183005094528198},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3411077857017517},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26782166957855225},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16480082273483276},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10123476386070251},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06843000650405884}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.823794424533844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.609342098236084},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5862748622894287},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5795788764953613},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.5604798197746277},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.5528181195259094},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.4183005094528198},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3411077857017517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26782166957855225},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16480082273483276},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10123476386070251},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06843000650405884},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves.2012.6294301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves.2012.6294301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1967182764","https://openalex.org/W2077012593","https://openalex.org/W2080972498","https://openalex.org/W2088978090","https://openalex.org/W2112008099","https://openalex.org/W2121416338","https://openalex.org/W2133822758","https://openalex.org/W2152300605","https://openalex.org/W2170003873","https://openalex.org/W2488678869","https://openalex.org/W3150904112","https://openalex.org/W4233805061"],"related_works":["https://openalex.org/W2258033839","https://openalex.org/W4297884099","https://openalex.org/W3203668668","https://openalex.org/W4391055430","https://openalex.org/W3214769583","https://openalex.org/W2116812645","https://openalex.org/W1980239608","https://openalex.org/W4377157894","https://openalex.org/W2395327451","https://openalex.org/W3009214786"],"abstract_inverted_index":{"Driving":[0],"context":[1,50,63,70,97,118],"plays":[2],"an":[3],"essential":[4],"role":[5],"in":[6,146],"driving":[7,10,20,44,49,62,92,96,123,144,148],"behavior":[8,67,107,145],"and":[9,25,69,134],"performance":[11,72],"of":[12,60,73,90,108],"a":[13,19,29,33,42,79],"driver.":[14],"The":[15,111],"contextual":[16],"information":[17],"surrounding":[18],"activity":[21],"involves":[22],"several":[23],"factors":[24],"dimensions":[26],"that":[27,114,125],"influence":[28],"driver's":[30],"behavior.":[31],"However,":[32],"driver":[34],"may":[35,37],"or":[36],"not":[38],"need":[39],"to":[40,85,142],"adopt":[41],"particular":[43,117],"pattern":[45],"for":[46],"every":[47],"distinct":[48,122],"conditions.":[51,98],"In":[52],"this":[53],"paper,":[54],"we":[55],"statistically":[56],"investigate":[57],"the":[58,66,87,104],"impact":[59],"various":[61],"conditions":[64],"on":[65],"prediction":[68],"recognition":[71],"stochastic":[74,131],"driver-behavior":[75,132],"models.":[76],"We":[77],"employed":[78],"Dirichlet":[80],"process":[81],"mixture":[82],"modeling":[83],"framework":[84],"capture":[86],"underlying":[88],"distributions":[89],"observed":[91],"parameters":[93],"under":[94,115],"different":[95],"Experimental":[99],"validation":[100],"was":[101],"conducted":[102],"using":[103],"on-the-road":[105],"car-following":[106],"sixty-four":[109],"drivers.":[110],"results":[112],"showed":[113],"two":[116],"conditions,":[119],"drivers":[120],"demonstrated":[121],"characteristics":[124],"could":[126,139],"be":[127,140],"efficiently":[128],"recognized":[129],"by":[130],"models,":[133],"yet,":[135],"some":[136],"context-specific":[137],"models":[138],"exploited":[141],"predict":[143],"other":[147],"contexts.":[149]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"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"}