dc.contributor.author | Sandberg, Martin K. Hoel | |
dc.contributor.author | Rehm, Johannes | |
dc.contributor.author | Mnoucek, Matej | |
dc.contributor.author | Gundersen, Odd Erik | |
dc.contributor.author | Reshodko, Irina | |
dc.date.accessioned | 2020-08-25T06:59:47Z | |
dc.date.available | 2020-08-25T06:59:47Z | |
dc.date.created | 2020-04-16T13:01:11Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | https://hdl.handle.net/11250/2673750 | |
dc.description.abstract | Intelligent tutoring systems become more and more common in assisting human learners. Distinct advantages of intelligent tutoring systems are personalized teaching tailored to each student, on-demand availability not depending on working hour regulations and standardized evaluation not subjective to the experience and biases of human individuals. A virtual driving instructor that supports driver training in a virtual world could conduct on-demand personalized teaching and standardized evaluation. We propose an architectural design of a virtual driving instructor system that can comprehend and explain complex traffic situations. The architecture is based on a multi-agent system capable of reasoning about traffic situations and explaining them at an arbitrary level of detail in real-time. The agents process real-time data to produce instances of concepts and relations in an ever-evolving knowledge graph. The concepts and relations are defined in a traffic situation ontology. Finally, we demonstrate the process of reasoning and generating explanations on an overtake scenario. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer Verlag | en_US |
dc.title | Explaining Traffic Situations – Architecture of a Virtual Driving Instructor | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.journal | Lecture Notes in Computer Science (LNCS) | en_US |
dc.identifier.doi | 10.1007/978-3-030-49663-0_15 | |
dc.identifier.cristin | 1806613 | |
dc.description.localcode | This is a post-peer-review, pre-copyedit version of an article. Locked until 3.6.2022 due to copyright restrictions. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-49663-0_15 | en_US |
cristin.ispublished | false | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |