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Explaining Traffic Situations – Architecture of a Virtual Driving Instructor

Sandberg, Martin K. Hoel; Rehm, Johannes; Mnoucek, Matej; Gundersen, Odd Erik; Reshodko, Irina
Peer reviewed, Journal article
Accepted version
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Sandberg (Locked)
URI
https://hdl.handle.net/11250/2673750
Date
2020
Metadata
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  • Institutt for datateknologi og informatikk [4881]
  • Publikasjoner fra CRIStin - NTNU [26591]
Original version
10.1007/978-3-030-49663-0_15
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.
Publisher
Springer Verlag
Journal
Lecture Notes in Computer Science (LNCS)

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