{"id":"https://openalex.org/W7160844400","doi":"https://doi.org/10.3390/make8050126","title":"Knowledge Graphs in Autonomous Driving: Construction, Integration, and Real-Time Reasoning","display_name":"Knowledge Graphs in Autonomous Driving: Construction, Integration, and Real-Time Reasoning","publication_year":2026,"publication_date":"2026-05-11","ids":{"openalex":"https://openalex.org/W7160844400","doi":"https://doi.org/10.3390/make8050126"},"language":"en","primary_location":{"id":"doi:10.3390/make8050126","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8050126","pdf_url":"https://www.mdpi.com/2504-4990/8/5/126/pdf?version=1779256556","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/8/5/126/pdf?version=1779256556","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087026980","display_name":"Patrik Viktor","orcid":"https://orcid.org/0000-0002-8689-2753"},"institutions":[{"id":"https://openalex.org/I103356709","display_name":"Obuda University","ror":"https://ror.org/00ax71d21","country_code":"HU","type":"education","lineage":["https://openalex.org/I103356709"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Patrik Viktor","raw_affiliation_strings":["Department of Marketing, Management and Methodology, Keleti K\u00e1roly Faculty of Business and Management, Obuda University, 1034 Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0002-8689-2753","affiliations":[{"raw_affiliation_string":"Department of Marketing, Management and Methodology, Keleti K\u00e1roly Faculty of Business and Management, Obuda University, 1034 Budapest, Hungary","institution_ids":["https://openalex.org/I103356709"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135864877","display_name":"G\u00e1bor Kiss","orcid":"https://orcid.org/0000-0002-0447-9376"},"institutions":[{"id":"https://openalex.org/I103356709","display_name":"Obuda University","ror":"https://ror.org/00ax71d21","country_code":"HU","type":"education","lineage":["https://openalex.org/I103356709"]}],"countries":["HU"],"is_corresponding":true,"raw_author_name":"G\u00e1bor Kiss","raw_affiliation_strings":["Institute of Safety Science and Cybersecurity, Obuda University, 1034 Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0002-0447-9376","affiliations":[{"raw_affiliation_string":"Institute of Safety Science and Cybersecurity, Obuda University, 1034 Budapest, Hungary","institution_ids":["https://openalex.org/I103356709"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5135864877"],"corresponding_institution_ids":["https://openalex.org/I103356709"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56852456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"5","first_page":"126","last_page":"126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6370000243186951,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.6370000243186951,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.09309999644756317,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0608999989926815,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.6565999984741211},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5293999910354614},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.47519999742507935},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.46639999747276306},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46230000257492065},{"id":"https://openalex.org/keywords/knowledge-integration","display_name":"Knowledge integration","score":0.4510999917984009},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4318999946117401},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4207000136375427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6728000044822693},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.6565999984741211},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5293999910354614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.499099999666214},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46230000257492065},{"id":"https://openalex.org/C56289545","wikidata":"https://www.wikidata.org/wiki/Q6423376","display_name":"Knowledge integration","level":3,"score":0.4510999917984009},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4318999946117401},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4207000136375427},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.35760000348091125},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3546999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34389999508857727},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C234837","wikidata":"https://www.wikidata.org/wiki/Q1420493","display_name":"Conceptual graph","level":3,"score":0.3343999981880188},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C102993220","wikidata":"https://www.wikidata.org/wiki/Q387196","display_name":"Description logic","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C84685590","wikidata":"https://www.wikidata.org/wiki/Q1540472","display_name":"Knowledge engineering","level":2,"score":0.26170000433921814}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make8050126","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8050126","pdf_url":"https://www.mdpi.com/2504-4990/8/5/126/pdf?version=1779256556","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:03292b996de846ee90480ff5c0a51af8","is_oa":true,"landing_page_url":"https://doaj.org/article/03292b996de846ee90480ff5c0a51af8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 8, Iss 5, p 126 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/make8050126","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make8050126","pdf_url":"https://www.mdpi.com/2504-4990/8/5/126/pdf?version=1779256556","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.774158775806427,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7160844400.pdf","grobid_xml":"https://content.openalex.org/works/W7160844400.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,35],"systems":[2],"require":[3],"the":[4],"integration":[5,96,120],"of":[6,28,121],"heterogeneous":[7],"sensor":[8],"data,":[9],"distributed":[10],"V2X":[11,61],"communication,":[12],"and":[13,18,38,70,103,118],"safety-critical":[14,107],"decision-making":[15],"into":[16],"coherent":[17],"interpretable":[19],"world":[20],"models.":[21],"This":[22],"review":[23],"provides":[24],"a":[25,41,49,84],"systematic":[26],"analysis":[27],"knowledge":[29,62],"graph":[30],"(KG)-based":[31],"approaches":[32],"in":[33,83,106],"autonomous":[34],"between":[36],"2015":[37],"2025,":[39],"following":[40],"PRISMA-aligned":[42],"methodology.":[43],"The":[44],"literature":[45],"is":[46],"organised":[47],"along":[48],"perception":[50],"\u2192":[51,53,55],"representation":[52],"reasoning":[54,68],"decision":[56],"taxonomy,":[57],"covering":[58],"traffic":[59],"ontologies,":[60],"integration,":[63],"dynamic":[64],"KG":[65],"updates,":[66],"real-time":[67,113],"architectures,":[69],"benchmark":[71],"datasets.":[72],"A":[73],"clear":[74],"shift":[75],"from":[76],"static":[77],"representational":[78],"ontologies":[79],"toward":[80],"predictive":[81],"and,":[82],"smaller":[85],"subset,":[86],"closed-loop":[87],"validated":[88],"neuro-symbolic":[89],"architectures.":[90],"Knowledge":[91],"graphs":[92],"emerge":[93],"as":[94],"semantic":[95],"layers":[97],"that":[98],"improve":[99],"contextual":[100],"reasoning,":[101,114],"explainability,":[102],"rule":[104],"compliance":[105],"environments.":[108],"Key":[109],"challenges":[110],"include":[111],"scalable":[112],"standardised":[115],"evaluation":[116],"frameworks,":[117],"safety-aligned":[119],"learning-based":[122],"components.":[123]},"counts_by_year":[],"updated_date":"2026-06-19T15:47:20.252518","created_date":"2026-05-12T00:00:00"}