PROCEEDINGS OF THE HUMAN FACTORS SOCIETY-3lst ANNUAL MEETING-1987 STEP ‘l’lUCKING SHRlNKlNG TARGETS

Four models describing how people might acquire targets that dynamica l l y vary i n s i z e were examined; two that described movement speed a s a simple funct ion of target s i z e ( e i ther i n i t i a l or f i n a l ) and two that described movement speed a s a function of the predicted s i z e o f the targets a t a f i xed time i n the fu ture (one was referenced to the beginning of the reaction time phase, and the other to the end of t h i s phase). I t was found that movement time was best described as a funct ion o f a s i z e prediction made a t the end, rather than the s tart , o f the reaction time phase. Subjective workload ratings primarily re f lec ted the total amount o f time needed to acquire the targets rather than the time pressure imposed by the diminishing s i z e o f these targets . The objective of this research was to examine step tracking performance using a laboratory task that creates a time-pressured environment similar to that encountered by gunners. Typically step tracking analyses have examined the relationship between movement time (MT) and the Fitt’s index of difficulty (ID), but only for targets of a fixed size. In general this relationship has shown MT to be linearly related to ID, or: MT = C + B * Log2(2*A/W) (1) where Log2(2*A/W) is the ID, A is distance to the target, W is target size, and C and I! are constants. This is the Basic step tracking model. However, in many operational situations, the target size and/or distance changes with time. This, in turn, yields a dynamically changing ID. Jagacinski, Repperger, Ward, and Moran (1980) examined the case where amplitude changes with time and found that a modified form of Fitt’s law applied. However, little is known about cases where the visible target width changes with time, such as might occur when a target is moving away, and therefore presents an increasingly smaller profile. In this situation the tracker must try to capture the target while it is still a reasonable size. However, if a movement is too fast, then accuracy may decrease making it take longer to finally capture the target. On the other hand, if the movement is too slow, then the gain in movement accuracy may be offset by an increase in required accuracy (since the target continues to shrink) and, again, it will take longer to capture the target. In any case, a version of Fitt’s Law based upon target width at time of capture may predict the time needed to capture shrinking targets if 1) the operator perfectly scales movement speed, or 2) if the effect of target size in Fitt’s Law is predominantly determined by the size of the target near the time of capture rather than near the start of the initial movement. In either case MT would be a linear function of the Fitt’s ID at the time of target acquisition, or: MT = C + B * log2(2*A/WC) (2) where Kc is the target width at time of target acquisiTion. model. This is the Balanced step tracking On the other hand, subjects may not choose (or be able) to use methods generating such a balance between movement time and final target size. Instead, they may rely upon more approximate methods which ensure capturing the target while it is a reasonable size, but do not result in, or require, this exact balance. In particular, it is reasonable to suppose that people would select some nominal amount of time in which they assume they could capture all targets. They could then aim at all targets based on an estimate of predicted size at this amount time in the future. Thus, if a time horizon of 2 sec was adopted, the tracker would move at a speed that would capture a target of the size expected 2 sec in the future, even though this might result in a completed capture sooner or later than the nominal time. Selection of such a time horizon would constitute a compromise between a perfect balancing of movement time and movement accuracy (Equation 2), and no balancing at all (Equation 1). In this study a design requiring the capture of shrinking targets was used to contrast two versions of an approximate prediction model with the Basic and Balniircd step tracking models. One prediction modr.1, the Imnediate Prediction PROCEEDINGS OF THE HUMAN FACTORS SOCIETY-3lsf ANNUAL MEETING--1987 model, assumes that a prediction is made at the beginning of the trial (at the start of the reaction time (RT) phase, Equation 3). This model (in which is shrink rate and 1 is the time horizon used) reflects the possibility that, for familiar targets and target dynamics, predictions and movement scaling may occur at the start of a trial. MT = C + B * log2(2*A/(Wo r*(T))) The second version, the Delayed Prediction model, assumes that movement speed is scaled at the end of the reaction time phase (just prior to the movement phase, Equation 4). This model reflects the possibility that predictions and movement scaling occur only after motion dynamics, future size estimates, and other important information are perceptually extracted. (3) MT = C + B Ji log2(2*A/(Wo r*(RT + T))) (4) In addition to examining these behavioral models, the influence of time pressure upon subjective workload ratings was also examined. Some investigators have proposed that workload, and workload ratings, vary primarily as a function of the rate at which work must be performed, i.e. time pressure (LeMay & Hird, 1986). These investigators have usually measured time pressure as the amount of time needed to accomplish a task relative to the time allowed. While this approach implicitly assumes that time needed reflects the amount of work, the separate influence that time pressure and total work may have on work load ratings has not been explicitly evaluated . This is an important distinction since subjective workload ratings may tend to track either quantity. In this study timepressure, (measured as the proportion of the available time used to capture a target) and total work (measured as the total time taken to capture a target) were examined to determine how well each could account for the obtained ratings. A step tracking task was used in which subjects were required to sequentially capture 14 adjacent targets represented by small, medium, or large circles in a grid of 35 potential targets. Time pressure and task difficulty were manipulated in three ways. First, target size either remained static or decreased at one of two rates. Thus, subjects had to move more quickly to capture shrinking targets, especially with fast shrink rates and/or small initial sizes. In addition, three different types of information were used to indicate which of the 35 potential targets were the correct 14 targets: 1 ) target circles were a different color than non-target circles; 2) the direction of the next target (North, South, East, and West) was displayed at the start of each step; and 3) subjects had to compute the next compass direction by adding two numbers at the start of each step. where all targets were located when the targets were a different color, while directional information in the Direction and Heading conditions could not be decoded until the beginning of each step. This, in turn, caused the duration and workload of the RT phase to vary from low load/ low difficulty (color coding) to high load/ high difficulty (Heading information). This design allowed time pressure to be varied by manipulating available time (target duration when shrinking), and required time (time needed to decode the direction and capture the target). As a result subjects knew in advance