{"id":"https://openalex.org/W3114451347","doi":"https://doi.org/10.1109/itsc45102.2020.9294473","title":"Using Sum-Product Networks for the Generation of Vehicle Populations On Highway Sections","display_name":"Using Sum-Product Networks for the Generation of Vehicle Populations On Highway Sections","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3114451347","doi":"https://doi.org/10.1109/itsc45102.2020.9294473","mag":"3114451347"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5015689148","display_name":"Stefan Jesenski","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Stefan Jesenski","raw_affiliation_strings":["Robert Bosch GmbH, Corporate Research, Renningen, Germany"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073338171","display_name":"Jakob Jonas Rothert","orcid":null},"institutions":[{"id":"https://openalex.org/I95793202","display_name":"Otto-von-Guericke University Magdeburg","ror":"https://ror.org/00ggpsq73","country_code":"DE","type":"education","lineage":["https://openalex.org/I95793202"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jakob Rothert","raw_affiliation_strings":["Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany"],"affiliations":[{"raw_affiliation_string":"Otto von Guericke Universit\u00e4t Magdeburg, Magdeburg, Germany","institution_ids":["https://openalex.org/I95793202"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071122808","display_name":"Nils Tiemann","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nils Tiemann","raw_affiliation_strings":["Robert Bosch GmbH, Corporate Research, Renningen, Germany"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Corporate Research, Renningen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060028048","display_name":"J. Marius Z\u00f6llner","orcid":"https://orcid.org/0000-0001-6190-7202"},"institutions":[{"id":"https://openalex.org/I143379178","display_name":"FZI Research Center for Information Technology","ror":"https://ror.org/04kdh6x72","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I143379178"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"J. Marius Zollner","raw_affiliation_strings":["Research Center for Information Technology (FZI), Karlsruhe, Germany"],"affiliations":[{"raw_affiliation_string":"Research Center for Information Technology (FZI), Karlsruhe, Germany","institution_ids":["https://openalex.org/I143379178"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015689148"],"corresponding_institution_ids":["https://openalex.org/I889804353"],"apc_list":null,"apc_paid":null,"fwci":0.2013,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.56070509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994000196456909,"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":0.9994000196456909,"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/T10524","display_name":"Traffic control and management","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/computer-science","display_name":"Computer science","score":0.7052284479141235},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.694261372089386},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6580542922019958},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5809365510940552},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5086075067520142},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5016045570373535},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4931949973106384},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.49199315905570984},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3992161154747009},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3705105185508728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3482474088668823},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3477741777896881},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1285298466682434},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.0906079113483429}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7052284479141235},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.694261372089386},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6580542922019958},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5809365510940552},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5086075067520142},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5016045570373535},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4931949973106384},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.49199315905570984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3992161154747009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3705105185508728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3482474088668823},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3477741777896881},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1285298466682434},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0906079113483429},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1895727713","https://openalex.org/W1948031799","https://openalex.org/W1965455100","https://openalex.org/W2089080831","https://openalex.org/W2095841525","https://openalex.org/W2159687189","https://openalex.org/W2394620536","https://openalex.org/W2438413413","https://openalex.org/W2511072509","https://openalex.org/W2525936901","https://openalex.org/W2561003639","https://openalex.org/W2562282355","https://openalex.org/W2580495915","https://openalex.org/W2758811412","https://openalex.org/W2783103637","https://openalex.org/W2786235498","https://openalex.org/W2786294823","https://openalex.org/W2788951710","https://openalex.org/W2896642734","https://openalex.org/W2910209909","https://openalex.org/W2964022907","https://openalex.org/W2970180825","https://openalex.org/W2991144479","https://openalex.org/W4230519770","https://openalex.org/W4249261707","https://openalex.org/W4288638869","https://openalex.org/W4295700171","https://openalex.org/W6683309385","https://openalex.org/W6711925463","https://openalex.org/W6745381014","https://openalex.org/W6757629120"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"The":[0,87],"importance":[1],"of":[2,8,61,77,80,103,113],"simulation-based":[3,33],"approaches":[4,93],"for":[5,27,36],"the":[6,32,37,53,75,78,101,111,117,126],"development":[7],"automated":[9,29,63],"driving":[10,30],"functions":[11],"has":[12],"strongly":[13],"increased":[14],"in":[15],"recent":[16,92],"years.":[17],"Since":[18],"current":[19],"validation":[20,38],"methods":[21],"probably":[22],"will":[23],"not":[24,56],"be":[25],"feasible":[26],"highly":[28],"functions,":[31],"techniques'":[34],"relevance":[35],"procedure":[39],"is":[40,47,89,98,108],"also":[41],"increasing.":[42],"In":[43],"this":[44,68],"context,":[45],"it":[46],"a":[48,71],"large":[49,58],"challenge":[50],"to":[51,100,121,125],"simulate":[52],"huge":[54],"if":[55],"infinitely":[57],"parameter":[59],"space":[60],"an":[62],"vehicle's":[64],"(AV)":[65],"surrounding.":[66],"Therefore,":[67],"paper":[69],"presents":[70],"model":[72,88],"which":[73],"allows":[74],"modeling":[76],"statistics":[79],"traffic":[81],"scenes":[82],"on":[83],"straight":[84],"highway":[85],"sections.":[86],"based":[90],"upon":[91],"using":[94],"Bayesian":[95,127],"networks":[96,105],"and":[97],"adapted":[99],"usage":[102],"sum-product":[104],"(SPNs).":[106],"It":[107],"shown,":[109],"that":[110],"use":[112],"SPNs":[114],"can":[115],"enhance":[116],"sampling":[118],"speed":[119],"up":[120],"36":[122],"times":[123],"compared":[124],"network":[128],"baseline.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}