Effects of Luminance, Contrast, Hold Time, Angular Velocity, and Pitch, on Simulated Aircraft Identification Range

Charles J. Lloyd, DeForest Joralmon, Ryan Amann,
Chi-Feng Tai, and William Morgan
L-3 Communications, Link Simulation & Training

Logan Williams, Byron Pierce
711 HPW/RHA, Air Force Research Laboratory

Effects of Luminance, Contrast, Hold Time, Angular Velocity, and Pitch, on Simulated Aircraft Identification Range Effects of Luminance, Contrast, Hold Time, Angular Velocity, and Pitch, on Simulated Aircraft Identification Range

Abstract

This paper summarizes the findings from the second of two human factors evaluations conducted as part of the Immersive Display Evaluation and Assessment Study (IDEAS) program. In this evaluation experienced USAF F-16 pilots discriminated and positively identified distant fighter-sized aircraft. On each trial the ownship rapidly approached a pair of aircraft, one “friend” and one “foe,” and the observers designated the foe as quickly and accurately as they could.

The first evaluation focused on the variables expected to be primary determinants of motion-induced blurring (e.g., hold time and angular velocity) for sample-and-hold display systems. This second evaluation filled out the data set required to validate a more complete model of the design variables expected to mediate task performance for very high resolution display systems. In this evaluation, task performance was measured as a function of 200 combinations of five practical display system design variables including: display luminance, display contrast, pixel hold time, angular velocity of the image, and pixel pitch (resolution).

Prior to conducting the evaluation, a computational model was prepared and used to make quantitative predictions of the effects of these design variables. The correlation between the model predictions and the results of this evaluation was high (e.g., R2 = 0.91, p < 0.001, 199 df). The model parameters have not yet been optimized to the data collected in this evaluation.

A significant benefit provided by the model is the quantification of the interactions among the design variables. Thus, the model is useful for examining the impact of design trades among the variables that affect task performance.

A summary of this evaluation was published at the IMAGE 2011 conference. The present report contains more of the details of the evaluation and a table of the mean response data for the 200 experimental conditions.