V3S: A Virtual Environment for Risk-Management Training Based on Human-Activity Models

Abstract

As work situations become more complex, virtual reality has proven to be advantageous for the emerging needs in risk-management training. However, building perfectly realistic simulations of the technical systems is not enough to address complex coactivity situations, where human factors play an important part. There is a need for virtual environments that would put trainees into varied ecological situations, inducing knowledge and competencies that would be put into practice in genuine work situations. The V3S project was proposed to build a generic framework for tailor-made virtual environments that can adapt to different application cases, technological configurations, or pedagogical strategies. This framework relies on the integration of multiple explicit models (domain, activity, and risk model). In order to build ecologically valid virtual environments, these models represent not only the prescribed activity, but the situated knowledge of operators about their tasks, including deviations from the procedures. These models are used both to monitor learners' actions, detecting errors and compromises; and also to generate virtual characters' behaviors, subject to erroneous actions. Moreover, dynamic situated feedback allows for progressive learning scenarios, adapting the complexity of the situations to the learner's activity and level. Evaluations have shown a high satisfaction level and encouraging usability measures. In future work, we propose to extend the possibilities of the simulation through the creation and monitoring of adaptive scenarios, adjusting the behavior of virtual characters able to assist or disrupt the user.1

OpenBIM Based IVE Ontology: An Ontological Approach to Improve Interoperability for Virtual Reality Applications

“…Virtual reality provides a relevant response to the act of training to perform tasks without dangers, train many people from different locations [6] at lower costs, understand abstract concepts or absolve from the language barrier (written or oral), and put into practice.…”

Intelligent Biohazard Training Based on Real-Time Task Recognition

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