Conference Proceeding
Author: Matthew Romoser (University of Massachusetts - Amherst, Amherst, MA)
An intelligent tutoring model for use in a driving simulation training platform is proposed. Driving simulators by themselves cannot teach and staffing driving simulators with live trainers limits their ability to reach a wide audience. Research has shown that customized feedback, coupled with active practice in a simulator is very effective in changing a driver’s behavior for the better. A driving simulation training program which utilizes an intelligent tutoring system (ITS) can diagnose driver errors, tailor feedback to the student’s specific needs, determine when a student has mastered a specific skill set and can provide remediation as necessary. A brief discussion of basic ITS architecture is provided. An ITS model that has been successful in teaching individual skills in other domains (such as mental rotation) is applied to driving simulator instruction. The various critical components of the ITS, including the domain model, student model and tutoring model, are discussed in detail and a working example provided.
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How to Cite: Romoser, M. (2011) “An Autonomous Intelligent Driving Simulation Tutor for Driver Training and Remediation: A Concept Paper”, Driving Assessment Conference. 6(2011). doi: https://doi.org/10.17077/drivingassessment.1438