{"id":"https://openalex.org/W4390045042","doi":"https://doi.org/10.1109/sdf-mfi59545.2023.10361516","title":"Friction and Road Condition Estimation using Dynamic Bayesian Networks<sup>*</sup>","display_name":"Friction and Road Condition Estimation using Dynamic Bayesian Networks<sup>*</sup>","publication_year":2023,"publication_date":"2023-11-27","ids":{"openalex":"https://openalex.org/W4390045042","doi":"https://doi.org/10.1109/sdf-mfi59545.2023.10361516"},"language":"en","primary_location":{"id":"doi:10.1109/sdf-mfi59545.2023.10361516","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/sdf-mfi59545.2023.10361516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI)","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/A5029925456","display_name":"Bj\u00f6rn Volkmann","orcid":null},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bj\u00f6rn Volkmann","raw_affiliation_strings":["Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030912644","display_name":"Karl-Philipp Kortmann","orcid":"https://orcid.org/0000-0002-0472-3316"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karl-Philipp Kortmann","raw_affiliation_strings":["Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039578386","display_name":"Thomas Seel","orcid":"https://orcid.org/0000-0002-6920-1690"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Seel","raw_affiliation_strings":["Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz University Hannover, Institute of Mechatronic Systems, An der Universit&#x00E4;t 1,30823 Garbsen,Germany","institution_ids":["https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114112103"],"apc_list":null,"apc_paid":null,"fwci":0.1019,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.43043902,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.9958999752998352,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.9958999752998352,"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/T14304","display_name":"Transport Systems and Technology","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.970300018787384,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.6428337097167969},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5981881618499756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5615087747573853},{"id":"https://openalex.org/keywords/friction-coefficient","display_name":"Friction coefficient","score":0.5592589974403381},{"id":"https://openalex.org/keywords/vehicle-dynamics","display_name":"Vehicle dynamics","score":0.5243000388145447},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5058073997497559},{"id":"https://openalex.org/keywords/dynamical-friction","display_name":"Dynamical friction","score":0.47563672065734863},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4551023542881012},{"id":"https://openalex.org/keywords/slip","display_name":"Slip (aerodynamics)","score":0.43633797764778137},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.37788790464401245},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24664536118507385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23633942008018494},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.2065415382385254},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16232165694236755},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.12737411260604858}],"concepts":[{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.6428337097167969},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5981881618499756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5615087747573853},{"id":"https://openalex.org/C2989152160","wikidata":"https://www.wikidata.org/wiki/Q82580","display_name":"Friction coefficient","level":2,"score":0.5592589974403381},{"id":"https://openalex.org/C79487989","wikidata":"https://www.wikidata.org/wiki/Q934680","display_name":"Vehicle dynamics","level":2,"score":0.5243000388145447},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5058073997497559},{"id":"https://openalex.org/C3038340","wikidata":"https://www.wikidata.org/wiki/Q1268968","display_name":"Dynamical friction","level":2,"score":0.47563672065734863},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4551023542881012},{"id":"https://openalex.org/C195268267","wikidata":"https://www.wikidata.org/wiki/Q1928883","display_name":"Slip (aerodynamics)","level":2,"score":0.43633797764778137},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.37788790464401245},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24664536118507385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23633942008018494},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.2065415382385254},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16232165694236755},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.12737411260604858},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sdf-mfi59545.2023.10361516","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/sdf-mfi59545.2023.10361516","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2064791460","https://openalex.org/W2072496911","https://openalex.org/W2087202281","https://openalex.org/W2093604883","https://openalex.org/W2115579991","https://openalex.org/W2150235509","https://openalex.org/W2162430285","https://openalex.org/W2340897893","https://openalex.org/W2558027072","https://openalex.org/W2613420840","https://openalex.org/W2770073266","https://openalex.org/W2798987418","https://openalex.org/W2978751956","https://openalex.org/W3006662015","https://openalex.org/W3035564946","https://openalex.org/W3087078861","https://openalex.org/W3105842203","https://openalex.org/W3153970996","https://openalex.org/W3166290131","https://openalex.org/W4206713226","https://openalex.org/W4211194540","https://openalex.org/W4252199061","https://openalex.org/W4285200195","https://openalex.org/W4388903626"],"related_works":["https://openalex.org/W3128072696","https://openalex.org/W2578973671","https://openalex.org/W2215058820","https://openalex.org/W2097663773","https://openalex.org/W1602184117","https://openalex.org/W2413421635","https://openalex.org/W2370145887","https://openalex.org/W2511198839","https://openalex.org/W4381890227","https://openalex.org/W1966557338"],"abstract_inverted_index":{"An":[0],"essential":[1],"factor":[2],"in":[3,60],"ensuring":[4],"driving":[5],"stability":[6],"and":[7,17,109,164],"traffic":[8],"safety":[9],"of":[10,46,63,90,107],"vehicles":[11],"is":[12,67,116,150,158],"knowledge":[13,148],"about":[14],"road":[15,162],"condition":[16,163],"maximum":[18,111],"tire-road":[19],"friction":[20,34,112,165],"potential.":[21],"In":[22],"previous":[23],"research":[24],"systems":[25,48],"that":[26],"either":[27],"measure":[28],"friction-related":[29],"parameters":[30],"or":[31,56],"estimate":[32,161],"the":[33,44,61,88,100,110,126,133,137,151],"coefficient":[35],"via":[36],"a":[37,79,94,121,154],"mathematical":[38],"model":[39],"have":[40],"been":[41],"proposed.":[42],"However,":[43],"performance":[45,127],"these":[47],"can":[49,83,139],"be":[50,84,140],"negatively":[51],"impacted":[52],"by":[53,86,142],"environmental":[54],"factors":[55],"require":[57],"sufficient":[58],"excitation":[59],"form":[62],"tire":[64],"slip,":[65],"which":[66,98],"often":[68],"too":[69],"low":[70],"under":[71,128],"practical":[72],"conditions.":[73,130],"Therefore,":[74],"this":[75,149],"paper":[76],"investigates":[77],"if":[78],"more":[80],"robust":[81],"estimation":[82],"achieved":[85],"fusing":[87],"information":[89,108],"multiple":[91],"sources":[92,106],"using":[93,132],"dynamic":[95,134,155],"Bayesian":[96,135,156],"network,":[97],"models":[99],"statistical":[101],"relationship":[102],"between":[103],"different":[104],"heterogeneous":[105],"coefficient.":[113,166],"The":[114],"algorithm":[115],"applied":[117],"to":[118,124,144,160],"data":[119],"from":[120],"passenger":[122],"vehicle":[123],"demonstrate":[125],"real":[129],"By":[131],"network":[136,157],"error":[138],"reduced":[141],"up":[143],"50%.":[145],"To":[146],"our":[147],"first":[152],"time":[153],"used":[159]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}