To effectively use a virtual environment (VE) for applications such as training and design evaluation, a good sense of orientation is needed in the VE. “Natural” human geographical orientation, when moving around in the world, relies on visual as well as proprioceptive feedback. However, the present navigation metaphors that are used to move around in the VE often lack proprioceptive feedback. To investigate the possible consequences this may have, an experiment was conducted on the relative contributions of visual and proprioceptive feedback on path integration in VE. Subjects were immersed in a virtual forest and were asked to turn specific angles under different combinations of visual, vestibular, and kinesthetic feedback (pure visual, visual plus vestibular, visual plus vestibular plus kinesthetic, pure vestibular, and vestibular plus kinesthetic). Furthermore, two visual conditions with different visual flows were tested: normal visual flow and decreased visual flow provided by a 60% zoom. Results show that kinesthetic feedback provides the most reliable and accurate source of information to use for path integration, indicating the benefits of incorporating this kind of feedback in navigation metaphors. Orientation based on visual flow alone is most inaccurate and unreliable. In all conditions, subjects overestimated their turning speed and subsequently didn't turn far enough. Both the absolute errors and the variation in path integration increase with the length of the path.
A simulator experiment was conducted to determine the potential benefits of path prediction on the navigational performance of channel-bound vessels. Channel pilots had to sail an approach channel under critical conditions in a deep-draught vessel. For the navigation task, basic radar information was used, supplemented by three different path predictors. Predictor (a) was based on an accurate fast-time hydrodynamic model of the vessel and showed the exact future path of the vessel. Both other path predictors were less accurate, relatively simple extrapolators; predictor (b) was based on a speed and rate of turn extrapolator and showed a curved representation of the future path; predictor (c) was based on a linear speed and course extrapolator and showed the ground velocity vector. Navigational performance was determined in terms of deviation from the planned route. The results indicate that the relatively simple extrapolator (b) supported the navigational task as effectively as the highly accurate path predictor (a). In comparison with the linear extrapolator (c), the navigational accuracy increased by a factor of two. It is concluded that support in anticipating the vessel's rate of turn is essential for accurate navigation. Implications of the use of path prediction for ship control are discussed.
When moving around in the world, humans can use the motion sensations provided by their kinesthetic, vestibular, and visual senses to maintain their sense of direction. Previous research in virtual environments (VEs) has shown that this socalled path integration process is inaccurate in the case that only visual motion stimuli are present, which may lead to disorientation. In an experiment, we investigated whether participants can calibrate this visual path integration process for rotations; in other words, can they learn the relation between visual ow and the angle that they traverse in the VE? Results show that, by providing participants with knowledge of results (KR), they can indeed calibrate the biases in their path integration process, and also maintain their improved level of performance on a retention test the next day.
In the present study we investigated how monitoring and fault management in a ship control task are affected by complexity and a priori probability of disturbances. Participants were required to supervise four independent shipping subsystems and to adjust the subsystems whenever deviations occurred. However, in order to apply the correct action, they first had to diagnose the cause of the deviation by requesting further subsystem information. Complexity and a priori probability were manipulated by varying the number of disturbances occurring simultaneously and the disturbance rates over subsystems. In general, the results indicate that the participants ignored the monitoring function when they were diagnosing a disturbance. Results also show evidence for “cognitive lockup”: Despite the possibility of stabilizing additional system faults and, consequently, increasing their time for diagnosis, participants tended not to interrupt an ongoing fault-finding process. Still, large individual differences were found in both the selected strategy and reasoning abilities.
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