Work

The virtual driving instructor: Multi‐agent system collaborating via knowledge graph for scalable driver education

Year: 2024

Type: article

Abstract: This work introduces the design, development, and deployment of a virtual driving instructor (VDI) for enhanced driver education. The VDI provides personalized, real‐time feedback to students in a driving simulator, addressing some of the limitations of traditional driver instruction. Employing a hybrid AI system, the VDI combines rule‐based agents, learning‐based agents, knowledge graphs, and Bayesian networks to assess and monitor student performance in a comprehensive manner. Implemented in multiple simulators at a driving school in Norway, the system aims to leverage AI and driving simulation to improve both the learning experience and the efficiency of instruction. Initial feedback from students has been largely positive, highlighting the effectiveness of this integration while also pointing to areas for further improvement. This marks a significant stride in infusing technology into driver education, offering a scalable and efficient approach to instruction.

Source: AI Magazine

DOI: 10.1002/aaai.12201

Authors: Johannes Rehm, Irina Reshodko, Stian Zimmermann Børresen, Odd Erik Gundersen

Institution: Norwegian University of Science and Technology

Language: English

Topic: Intelligent Tutoring Systems and Adaptive Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $2,400