29 research outputs found
PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 48th ANNUAL MEETING—2004 2111 A CLOSED-LOOP, ACT-R APPROACH TO MODELING APPROACH AND LANDING WITH AND WITHOUT SYNTHETIC VISION SYSTEM (SVS) TECHNOLOGY
imulation models as a routine part of design. (This has been argued in more detail elsewhere; e.g., Byrne & Gray, 2003). The focus of this research is on the evaluation of a new technology for the commercial airline cockpit (Foyle, et al., 2003). One of the factors that has long limited aviation is visibility; poor visibility conditions can substantially change the task of piloting an aircraft. However, with extensive and accurate computer-based geographic information systems, it is possible to generate the view of known terrain as long as the location of the observer is known. Modern GPS systems make it possible to know the location of an airplane with high accuracy. Thus, the combination of the two systems makes it possible to render on a computer display the terrain that may not be visible due to adverse environmental conditions (e.g. fog, rain). This is the basis for NASA's Synthetic Vision System or SVS. That is, an SVS is essentially a computer generated display designed to prov
The Effect of Information Analysis Automation Display Content on Human Judgment Performance in Noisy Environments
Exploring sequential data: Commentary on Bowers, Jentsch, Salas, and Braun (1998)
In an investigation intended to determine training needs of night crews, Bowers et al. (1998, this issue) report two studies showing that the patterning of communication is a better discriminator of good and poor crews than is the content of communication. Bowers et al. characterize their studies as intended to generate hypotheses for training needs and draw connections with Exploratory Sequential Data Analysis (ESDA). Although applauding the intentions of Bowers ct al., we point out some concerns with their characterization and implementation of ESDA. Our principal concern is that the Bowers et al. exploration of the data does not convincingly lead them back to a better fundamental understanding of the original phenomena they are investigating