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Abstract

A supporting investigation of human operator errors is discussed. Existing classification systems (taxonomies) are mostly used to analyze the accident reports, and not for investigating the accidents themselves. These systems provide appropriate taxonomy primarily for Reason's latent conditions and not so much for active errors. A model incorporating the active error characteristics of underlying cognitive sources along with the classification system for them is presented. It describes a human operator error as a group of frames adjusted to the activity of different operators, such as pilot or air traffic controller. Our model of active error and its classification system, combined with existing latent conditions classification systems, constitute a powerful tool – a decision support system for investigating human errors. Additionally, our model can be used as a basis for defining algorithms to analyze human performance in complex man-machine systems.

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Toward a System Approach to Human Error Investigation

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