Attentional Models of Multitask Pilot Performance Using Advanced Display Technology

Abstract

In the first part of the reported research, 12 instrument-rated pilots flew a high-fidelity simulation, in which air traffic control presentation of auditory (voice) information regarding traffic and flight parameters was compared with advanced display technology presentation of equivalent information regarding traffic (cockpit display of traffic information) and flight parameters (data link display). Redundant combinations were also examined while pilots flew the aircraft simulation, monitored for outside traffic, and read back communications messages. The data suggested a modest cost for visual presentation over auditory presentation, a cost mediated by head-down visual scanning, and no benefit for redundant presentation. The effects in Part 1 were modeled by multiple-resource and preemption models of divided attention. In the second part of the research, visual scanning in all conditions was fit by an expected value model of selective attention derived from a previous experiment. This model accounted for 94% of the variance in the scanning data and 90% of the variance in a second validation experiment. Actual or potential applications of this research include guidance on choosing the appropriate modality for presenting in-cockpit information and understanding task strategies induced by introducing new aviation technology.

Dual-Task Performance Consequences of Imperfect Alerting Associated With a Cockpit Display of Traffic Information

“…The context for our evaluation of these four factors is the cockpit display of traffic information (CDTI), a system proposed within future cockpits to provide pilots with a traffic display that is partially redundant with the air traffic controller's display and may, in some future airspace plans, allow pilots to monitor their course for conflicts and to initiate the choice to make route changes (Johnson, Battiste, & Bochow, 1999;Thomas & Wickens, 2005;Wickens, Helleberg, & Xu, 2002;Wickens, Goh, Helleberg, Horrey, & Talleur, 2003). Indeed, it has been proposed that such systems be coupled with discrete alerts (Thomas & Rantanen, 2006;Xu et al, 2007), paralleling similar alerting systems for air traffic control (Metzger & Parasuraman, 2005) and for more emergency airborne conflicts (the Traffic Alert and Collision Avoidance System [TCAS]).…”

Revealing Differences in Designers’ and Users’ Perspectives

“…MIDAS is a system developed by NASA [15], which uses cognitive models to analyze tasks and interfaces in the aerospace domain. It simulates visual attention distribution similar to CASCaS, but uses the SEEV model of Wickens et al [6] instead of the AIE model. Both models are strongly related, but differ in some aspects [7].…”

“…Second, the user fills out a relevance matrix specifying the relevancy R for each IS and each task (cf. [6]). ( , ) = 0 states, that IS is not relevant for task , ( , ) = 0.5 defines that supports , but is not mandatory for t, and ( , ) = 1 means, that is mandatory for .…”

“…With the HEE predictions can be performed by a cognitive human operator simulation in a very early design phase where only HMI design images or sketches of future interfaces are available. The HEE uses the Adaptive Information Expectancy model (AIE model) [5], which is based on the SEEV model [6] and is a dynamic simulation model of attention distribution.…”

Assessment of the SEEV Model to Predict Attention Allocation at Intersections During Simulated Driving

“…Value refers to an objective measure of the value or cost of processing or failing to process information in a particular AOI and is represented as the product of Relevance and Priority (R*P). Equation 1 below illustrates the SEEV model in prescriptive terms (Horrey, Wickens, & Consalus, 2006;Wickens, Goh, Helleberg, Horrey, & Talleur, 2003;Wickens, et al, 2001).…”