The performance of a navigating officer in critical situations is uncertain and has to be considered in a probabilistic framework, since this may provide an in depth insight in the human - machine interaction. Such a systematic approach will have the objective to understand, to predict and to minimize the role of the human as a causal factor for a casualty in terms of the time sequence needed to perform particular tasks during collision or grounding avoidance activities. By employing the exponential law, it is possible to quantify the cognitive processes of information acquisition, analysis, categorization, decision making and action implementation. Consequently, the minimum required time where an automated system may intervene is determined. In this way, it is expected that it is plausible to prevent the occurrence of a close encounter that could escalate in an accident. Albeit to the lack of an available and appropriate data set, the proposed concept is examined through the small sample results of a published simulation study.