Synthetic Vision Systems: The Effects of Guidance Symbology, Display Size, and Field of View Amy L. Alexander, Christopher D. Wickens, and Thomas J. Hardy, University of Illinois at Urbana-Champaign, Savoy, Illinois Two experiments conducted in a high-fidelity flight simulator examined the effects of guidance symbology, display size, and geometric field of view (GFOV) within a synthetic vision system (SVS). In Experiment 1, 18 pilots flew highlighted and lowlighted tunnel-in-the-sky displays, as well as a less cluttered follow-me aircraft (FMA), through a series of curved approaches over rugged terrain. The results revealed that both tunnels supported better flight path tracking and lower workload levels than did the FMA because of the availability of more preview information. Increasing tunnel intensity had no benefit on tracking and, in fact, degraded traffic awareness because of clutter and attentional tunneling. In Experiment 2, 24 pilots flew a lowlighted tunnel configured according to different display sizes (small or large) and GFOVs (30° or 60°). Measures of flight path tracking and terrain awareness generally favored the 60° GFOV; however, there were no effects of display size. Actual or potential applications of this research include understanding the impact of SVS properties on flight path tracking, traffic and terrain awareness, workload, and the allocation of attention.
INTRODUCTION Synthetic vision systems (SVSs) are being developed for the display of information needed by the pilot in order to safely and efficiently navigate under challenging terrain or low-visibility conditions (Prinzel et al., 2004; Schnell, Kwon, Merchant, & Etherington, 2004; Scott, 2001; Wickens, Alexander, & Hardy, 2003). Such systems provide an artificial, real-time presentation of terrain and other hazards to enhance situation awareness, particularly traffic and terrain awareness, combined with a depiction of the planned trajectory and augmented symbology to support guidance and control. The primary flight display (PFD) is one component of SVS intended to provide guidance information, although important design issues exist concerning its appropriate format. The overall purpose of the research reported in this paper is to guide development of the best format of the PFD within an SVS context.
Although many features may be used to define the optimal PFD format, we focus on two major issues in two experiments: how should primary flight guidance be provided to the pilot (Experiment 1), and how does display size and geometric field of view affect performance (Experiment 2)? In our first experiment, the 3-D perspective flight guidance system is based on both prediction (a predicted aircraft state) and preview (a command input), the latter represented as either a single follow-me aircraft (FMA; Beringer, 1999) or the more frequently examined tunnel in the sky (Beringer, 2000; Beringer & Ball, 2001; Fadden, Ververs, & Wickens, 2001; Haskell & Wickens, 1993; Jensen, 1981; Williams, 2002). An FMA is a 3-D perspective symbol providing course guidance to the pilot, whereas a tunnel in the sky provides preview of the desired flight path. Alternative intensity versions of the tunnel – lowlighted versus highlighted – are also considered in light of an overarching goal to minimize clutter. Because these features of guidance
Address correspondence to Christopher D. Wickens, University of Illinois, Aviation Human Factors Division, 1 Airport Rd., Savoy, IL 61874;
[email protected]. HUMAN FACTORS, Vol. 47, No. 4, Winter 2005, pp. 693–707. Copyright © 2005, Human Factors and Ergonomics Society. All rights reserved.
694 impose differing amounts of visual noise or clutter, we examine their implications for that aspect of SVS-hosted information that might be expected to be most vulnerable: traffic that could be hidden behind more and denser “strokes” inherent to a highlighted tunnel. Only a study by Beringer (1999) has compared the FMA with a tunnel in the sky. (Williams, 2002, also examined guidance symbology, but an FMA was used in conjunction with a tunnel display rather than compared with it.) Beringer (1999) found that using the FMA allowed for superior flight path tracking, although this was at the expense of increased control activity and mental workload. The major issue of clutter in comparing guidance symbologies was not examined specifically by Beringer (1999) but will be investigated in the current research in terms of decreasing the intensity of the tunnel symbology (i.e., lowlighting), removing that symbology altogether (the less cluttered FMA), and measuring traffic awareness (i.e., detection of traffic that may lie behind the guidance symbology). In predicting the effects of clutter (imposed by tunnel strokes) and intensity (of those strokes) on the awareness of traffic within the same display, one can turn first to the host of studies that have documented the costs of added “visual noise,” or clutter, to target detection in applied visual search tasks (e.g., Kroft & Wickens, 2003; Remington, Johnston, Ruthruff, Gold, & Romera, 2000; Yeh & Wickens, 2001), particularly for unexpected traffic on head-up displays (HUDs; Fadden et al., 2001; Wickens & Long, 1995). Added nontarget items in such a task require additional visual inspections to determine that they are not targets when the search is serial, and they may perceptually mask the target if they overlay. Ververs and Wickens (1998) also found that expected traffic was more difficult to detect behind a cluttered than a decluttered HUD. Although no study has compared the detection of traffic embedded on “single-point” tracking displays (e.g., the FMA) versus spatially distributed tracking displays (e.g., the tunnel), the study of HUD traffic detection by Fadden et al. (2001) offers some relevant data. They found that traffic depicted in a scene overlaid on a tunnel display was detected more slowly, but also
Winter 2005 – Human Factors more accurately, than that overlaid by a two-line instrument landing system display; they attributed the difference in accuracy to the greater narrowing of attention required by pilots to focus on the single point (intersection of glide slope and localizer) that represented error. They attributed the difference in detection speed to the initial clutter problems imposed by the tunnel, which had more marks overlaying the center of the display, where the traffic was first visible. Thus, on the basis of the collective results of applied visual search studies and HUD studies, there is some reason to believe that there will be a traffic detection advantage for the less cluttered FMA, but that such an advantage may be offset if this display induces attentional narrowing to the “single-point” follow-me airplane, particularly for traffic appearing in the periphery. With regard to the effects of lowlighting (i.e., decreasing stimuli intensity), there is some evidence in the literature that targets can be found more rapidly when other information on the display (in the current case, the tunnel) is of lower intensity (e.g., Fisher, Coury, Tengs, & Duffy, 1989; Johnson, Liao, & Granada, 2002; Wickens, Alexander, Martens, Ambinder, 2004; Wickens, van Offlen, Muthard, Alexander, & Podczerwinski, 2003). Such lowlighting allows preattentive segregation of a large class of items known to be nonrelevant, and therefore the pilot can eliminate them from the serial search process (Wickens, Alexander, Martens, et al., 2004). However, this effect does not always appear, as Yeh and Wickens (2001) found few benefits for searching for items in a highlighted set when those items (map features) were already discriminable from dimmer items by spatial features. In perhaps the closest analog to the current research, Ververs and Wickens (1998) failed to find that reducing the intensity of HUD stroke symbology improved detection of traffic beyond that found with head-down displays. Of importance, however, is that they also found that a reduction in HUD stroke intensity did not disrupt the performance of flight path tracking using that reduced-intensity information. Objectives and Hypotheses The present research, involving two highfidelity flight simulations, examined the effects of
SYNTHETIC VISION SYSTEMS changes to the PFD (guidance symbology, display size, and geometric field of view) on flight path tracking performance, control activity, situation awareness (traffic and terrain awareness), and subjective mental workload. Across both experiments, pilots flew curved, step-down approaches to a runway according to command guidance on the PFD. The specific tasks beyond basic flying varied by experiment. We will now turn to the details and hypotheses of Experiment 1. In Experiment 1, we considered the differences between an FMA, a highlighted tunnel in the sky, and a lowlighted tunnel with a particular emphasis on traffic awareness (i.e., traffic detection). We offer two primary hypotheses, one represented in each of the contrasts: between lowlighted tunnel and FMA, and between lowlighted and highlighted tunnel. With each hypothesis, we also pair an experimental question, the outcome of which is quite uncertain and does not allow us to hypothesize an expected direction of effect. Hypothesis 1a: We hypothesize that the lowlighted tunnel, by virtue of its strokes and curves, will offer more effective preview (Mulder, 2003) and will therefore support better flight path tracking than the FMA, particularly in turns. We are uncertain, however, as to the direction of effect on traffic detection, with the reduced clutter of the FMA suggesting possibly better detection, but the single-point source of tracking information for the FMA also possibly leading to attentional narrowing that may inhibit detection, relative to the more broadly distributed tunnel information. In terms of workload, we hypothesize that mental workload ratings will be lower with the tunnel than the FMA because the flight path tracking task would be perceived as being easier with the tunnel present, given its more effective preview. Hypothesis 1b: We hypothesize that the lowlighted tunnel, by virtue of the lower intensity of the overlying strokes, will support better detection of the traffic than the highlighted tunnel. Less certain, however, is the extent to which the reduced intensity might harm flight path tracking, based on the reduced salience of that stroke information. The only study reviewed that examined this issue appeared to reveal no effect of lowlighting on tracking (Ververs & Wickens, 1998).
695 EXPERIMENT 1 Method Participants. Eighteen pilots (16 men, 2 women) from the Institute of Aviation at the University of Illinois flew a sequence of six flight scenarios designed to compare three guidance symbology formats: highlighted tunnels, lowlighted tunnels, and the FMA. Pilots ranged in age from 20 to 26 years (M = 22 years) with a mean number of 503 total flight hours. All pilots had normal or corrected-to-normal vision and were paid $8/hr for their participation. Simulation. This experiment was conducted on a high-fidelity, full mission Frasca Model 142 dual-control flight simulator, approved by the Federal Aviation Administration and configured as a Piper Archer III single-engine aircraft (see Wickens, Alexander, et al., 2003, for details). The fixed-base, yoke-controlled simulator was positioned in front of an approximately 180° view of the outside world. Evans & Sutherland simFUSION image generators powered three projectors with 1280 × 1024 pixels of resolution displayed onto three separate 7.5- × 10-foot (2.29- × 3.05-m) screens. The real-time Yosemite National Park terrain image was run by MultiGen-Paradigm Vega simulation software. The cockpit LCD SVS display was a 14.1- × 11.25-inch (35.7- × 28.5-cm) screen with a resolution of 1280 × 1024 pixels. The distance from the pilot viewpoint to the display was approximately 26.5 inches (67.3 cm) and was held constant for all display conditions. The geometric field of view (GFOV) was 45° horizontal × 36° vertical. Displays. All display formats overlaid a computer-generated terrain. As shown in Figure 1, a small 2-D electronic map was placed in the upper right corner of the SVS display, representing the navigation display. The pilot’s path was represented on the navigation display in green with a magenta arrow representing ownship heading and position along the path. Ownship was represented in the large SVS display as a green W (the bore sight), and a white 3-D perspective predictor portrayed the pilot’s estimated position 5 s ahead of ownship. Airspeed was fixed at 100 knots such that this predictor was always 5 s ahead of ownship. Both the bore sight and the predictor behaved as
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(a)
(b)
(c)
Figure 1. Displays used: (a) highlighted tunnel in the sky (note runway incursion – this was used to instigate a missed approach); (b) lowlighted tunnel in the sky; and (c) FMA illustrating an upcoming left turn. The red FMA turning to the left appears black in the present monochrome figure.
SYNTHETIC VISION SYSTEMS moving-horizon attitude indicators. The predictor’s position in space was generated based on ownship’s current X and Y position, altitude, heading, airspeed, rate of turn, and vertical speed. The predictor always maintained an attitude (pitch and roll) corresponding to ownship. Altitude and airspeed were presented as round dials on the right and left of the screen, respectively. A horizon line was provided, and the exact heading of ownship was displayed directly above the bore sight. Ownship’s vertical speed was presented on the tape to the right of the bore sight. The tunnel displays (see Figures 1a and b) were depicted by a series of connected 200- × 75-foot (61.0- × 22.9-m) green boxes 300 feet (91.4 m) apart in depth. Pilots maintained ownship position in the center of the path by keeping the predictor in the center of the tunnel. Lowlighting was achieved by narrowing the stroke width from 2.4 feet (0.73 m) used in the highlighted tunnel to 1.2 feet (0.37 m) and adding a transparent material with an alpha (blending coefficient) of .5. The FMA (see Figure 1c) was a red, 3-D perspective, aircraft-like symbol positioned in the center of the now-invisible tunnel, 5 s ahead of ownship. Pilots maintained ownship position in the center of the path by keeping the predictor on the FMA. Task and experimental design. Pilots flew a series of six 8- to 10-min flights in simulated visual meteorological conditions, following curved paths over rugged terrain to an airport, with each of the three guidance symbologies. The flight paths and landing runway used in this experiment did not correspond to actual real-world approaches. The scenarios were created for experimental purposes to be relatively low to the ground and to fly over different sections of terrain within Yosemite National Park so as to provide a terrain-challenging environment with numerous mountains and valleys. Each flight path consisted of 16 to 18 legs, of which 9 or 10 were straight and the remainder were curved. Each flight required pilots to detect airborne hazards (i.e., blimps) visible against the computergenerated imagery of sky by pressing the left push-to-talk button on the yoke and reporting their true azimuth and elevation angle from ownship (e.g., “traffic, two o’clock high”). There were three blimps per trial entering the forward field of view; these were either close enough to the
697 flight path to be portrayed behind the tunnel symbology or peripheral enough to be in clear view. Out of the 18 total blimps requiring detection, half of them appeared in the middle of the display and half appeared toward the periphery. All blimps remained in a static position relative to the flight path. Airspeed was fixed at 100 knots until the final approach leg. Participants were responsible only for controlling airspeed and staying on the flight path down to the runway on the final approach leg. A within-subjects, counterbalanced manipulation of display type was used such that each pilot experienced each guidance symbology twice. Unexpected event. One final event, at the end of the last trial, required the pilot to fly a missed approach because of a large aircraft turning onto the active runway (see Figure 1a). The aircraft was visible in the outside world and represented by a 3-D perspective icon in the SVS display. The SVS recognized the impending conflict and automatically reconfigured the path to guide the pilot along the missed approach path. Unbeknownst to the pilot, this missed approach path led the aircraft into a serious conflict situation with another aircraft. This aircraft was “transponder-off” in the sense that it could not be recognized by the SVS system generating the command path, and it was therefore depicted in the outside world but not on the cockpit SVS display. As with all other aircraft, pilots were instructed to detect and avoid midair collisions. Pilots who did not notice the rogue aircraft flew directly into it, but they were not informed by the experimenter or by the simulation itself that this had occurred. The purpose of the unexpected event was to examine the attentional tunneling hypothesis, which predicts that pilots will be so engaged with the tasks inherent to the SVS display, given its compelling nature, that they will fail to notice events occurring outside the display, perhaps in the outside world. Procedure. The experiment was conducted in the Flight Simulation Laboratory in the Beckman Institute at the University of Illinois. Pilots completed an informed consent form and a brief questionnaire regarding their previous flight experience, and then they read experimental instructions explaining the task and were shown illustrations while the experimenter read descriptions of the SVS guidance symbology. Pilots
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were instructed to fly the path as efficiently as possible while detecting traffic, as described earlier, and to land on the runway if clear. Pilots were not informed of the missed approach or rogue aircraft that would occur during the last trial, but they were told in the instructions that the SVS display could be used in the event of a missed approach and that they should remain cognizant of the outside world throughout the experiment. Pilots then flew two practice trials (one with the highlighted tunnel, one with the FMA) to familiarize themselves with the flight dynamics, task, and guidance symbology. Once practice sessions were successfully completed, pilots began the experimental session as specified earlier, flying six trials. Subjective mental workload ratings were collected using the NASA Task Load Index after each experimental trial. Results Less than 5% of the data were removed as outliers greater than ±3 standard deviations from the mean. The flight path deviation data (vertical and lateral deviation) were skewed; therefore, log transformations were performed in order to produce more normally distributed data sets. We adopted p < .05 as our criterion for significance. However, because of the importance of avoiding Type II statistical errors in applied human factors research, we refer to effects of .10 > p > .05 as “approaching significance” (Wickens, 1998). Effect-size correlation r was
used for all significant and approaching significant effects. Flight path performance. In the following analyses, 2 (guidance symbology) × 2 (leg type: straight or curved) repeated measures analyses of variance (ANOVAs) were first conducted to compare the lowlighted tunnel with the FMA and then to compare the two tunnel conditions. Vertical deviation data are shown in Table 1, Item a. Results revealed that the lowlighted tunnel supported better vertical tracking than did the FMA, F(1, 17) = 7.63, p < .05, r = .56. There was no effect of leg type, nor was there an interaction in comparing the lowlighted tunnel with the FMA (both ps > .15). There were no effects in vertical tracking performance between the lowlighted and highlighted tunnels (all ps > .15). Regarding lateral tracking performance, as shown in Table 1, Item b, there was no difference between the lowlighted tunnel and the FMA (p > .15), although lateral tracking performance overall was better on straight than curved legs, F(1, 17) = 77.8, p < .01, r = .91. There was no Guidance Symbology × Leg Type interaction (p > .15). In a comparison of the two tunnel displays, a main effect of leg type, F(1, 17) = 57.7, p < .01, r = .88, revealed that lateral deviations from the flight path were greater on curved than on straight legs. A significant Guidance Symbology × Leg Type interaction, F(1, 17) = 10.1, p < .01, r = .61, revealed that lateral tracking performance was better with the lowlighted than with the highlighted tunnel only on curved legs.
TABLE 1: Experiment 1 Flight Path Performance and Control Activity Results (Means and SDs) by Guidance Symbology and Leg Type Tunnel in the Sky Variable (a) Vertical deviations (m) Straight legs Curved legs (b) Lateral deviations (m) Straight legs Curved legs (c) Elevator control (°) Straight legs Curved legs (d) Aileron control (°) Straight legs Curved legs
FMA
Lowlighted
Highlighted
5.50 (0.70) 5.19 (0.37)
4.27 (0.28) 4.17 (0.23)
4.37 (0.44) 4.01 (0.24)
5.57 (0.43) 9.74 (0.91)
6.01 (0.50) 8.78 (0.52)
5.56 (0.33) 10.86 (0.72)
4.15 (0.15) 3.51 (0.14)
4.12 (0.14) 3.59 (0.14)
3.89 (0.13) 3.44 (0.13)
5.59 (0.34) 6.93 (0.40)
5.71 (0.39) 7.92 (0.49)
4.83 (0.29) 7.47 (0.52)
SYNTHETIC VISION SYSTEMS Control activity. Control activity data are shown in Table1, Items c and d. For elevator (vertical) control, there was no difference between the FMA and the lowlighted tunnel (p > .15), but such activity was greater with the lowlighted than with the highlighted tunnel, F(1, 17) = 6.14, p < .03, r = .52. For aileron (lateral) control, activity with the lowlighted tunnel was greater than with the FMA (approaching significance), F(1, 17) = 4.29, p < .06, r = .44. A main effect of leg type revealed that aileron activity was greater on curved than on straight legs, F(1, 17) = 69.0, p < .01, r = .90. A Guidance Symbology × Leg Type interaction, F(1, 17) = 5.57, p < .04, r = .50, stipulated that the increase in aileron control activity with the FMA as compared with the lowlighted tunnel was greatest on curved legs. In a comparison of the two tunnel displays, aileron control activity was greater with the lowlighted than with the highlighted tunnel, F(1, 17) = 9.92, p < .01, r = .61. Aileron activity was again greater on curved than on straight legs, F(1, 17) = 65.7, p < .01, r = .89. The interaction was not significant (p > .15). Traffic awareness. Traffic detection was measured as the time between the aircraft appearing in the forward field of view and when the pilot depressed the appropriate button on the yoke indicating that he or she had seen the traffic. In terms of guidance symbology, as shown in Figure 2, mean traffic detection times were essentially equivalent between the lowlighted tunnel (M = 10.3 s) and the FMA (M = 10.8 s; p >
699 .15). However, traffic detection was approximately 4 s slower with the highlighted (M = 15.6 s, SD = 11.6) than with the lowlighted tunnel, t(17) = 2.47, p < .03, r = .51. Display type had no effect on accuracy (all ps > .15), nor were effects of display type moderated by traffic location (blimps that appeared in the middle of the display so as to be portrayed behind the tunnel symbology versus blimps that appeared to the periphery of the display so as to be in clear view). Mental workload. Subjective mental workload was rated highest with the FMA (M = 8.9), intermediate with the lowlighted tunnel (M = 7.6), and lowest with the highlighted tunnel (M = 6.1) on a generic, composite scale of 0 to 27. Although planned comparisons revealed no difference in workload between the FMA and the lowlighted tunnel (p > .20), there was a significant difference between the lowlighted and highlighted tunnels, t(17) = 2.30, p < .04, r = .49. Unexpected event. The unexpected event (rogue aircraft) occurred only once for each pilot, so the available data were insufficient to allow statistical examination. Therefore, we consider these data in a nonstatistical fashion in stating that only 2 of the 18 pilots in this experiment detected and either avoided or commented on the rogue aircraft on the missed approach path, which was visible only in the outside world. One pilot was flying with the lowlighted tunnel, and the other was flying with the FMA. Both of these pilots took more than 37 s (37.97 s and
Figure 2. Mean traffic detection time by position within the display and display type. The bars in the figure show ±1 standard errors from the mean.
700 39.27 s) to detect the rogue aircraft from the time it first appeared in the outside world. A climbing maneuver was initiated by both pilots to avoid the aircraft. All other pilots flew directly through the aircraft. Discussion Guidance format: Lowlighted tunnel versus FMA. The FMA produced a clear cost to vertical (but not lateral) flight path tracking performance, as compared with the lowlighted tunnel, supporting our Hypothesis 1a, that the lowlighted tunnel would provide useful preview information about the future flight path from the multiple tunnel segments and their connections (Mulder, 2003), a strategy prevented with the single-point FMA guidance. Explicit presentation of this preview improved performance as compared with the FMA, although the tunnel induced greater aileron (lateral) control activity, especially on curved legs. These findings are in contrast to those of Beringer (1999), who found greater tracking error with a tunnel than with an FMA. It is likely that the greater control activity exhibited by Beringer’s (1999) pilots when using the FMA both increased perceived workload (invested effort; Vidulich & Wickens, 1986) and improved performance. Here pilots did not increase control activity with the FMA for either axis, a strategy that hurt vertical flight path tracking. In terms of situation awareness (SA), here most directly addressed by the measure of traffic awareness, there appeared to be little influence of guidance symbology (see Figure 2). Thus the FMA did not appear to narrow the focus of attention in a way that would disrupt detection of more peripheral traffic targets (the absence of such an effect is consistent with the absence of an FMA benefit to flight path tracking). However, the presence of low-intensity peripheral strokes in the lowlighted tunnel did not hinder the detection of those targets, either. It is possible that these two influences may have offset each other. Tunnel intensity: Lowlighting versus highlighting. Although the vertical deviation results generally suggested equal proficiency of primary flight path performance across both intensity levels, results revealed better lateral tracking performance on curved legs with the lowlighted than with the highlighted tunnel (an almost 20% er-
Winter 2005 – Human Factors ror reduction; see Table 1). Although these results might seem counterintuitive (in anticipating better tracking performance with a more intense tracking display), they are in fact partially consistent with earlier results obtained by Ververs and Wickens (1998), who also failed to find that increasing intensity improved tracking performance (using a 2-D HUD). We note here that even in the lowlighted condition the intensity was well above threshold, and the spatial distribution of the relevant information presumably mitigated whatever potential cost might have been observed in tracking accuracy when the less intense strokes were used to provide guidance information. Furthermore, it may have been that the distraction of the high-intensity strokes forced pilots to allocate more attention to the now more difficult traffic detection task in order to cope with the distraction at the expense of tracking. In contrast to the muted effects of intensity on tracking performance, intensity effects on the detection of midair targets behind and around the tunnel were as expected. Greater tunnel image intensity significantly disrupted (slowed) the ability to detect traffic targets, by as much as 4 s (see Figure 2). Although these results are consistent with the findings of Wickens, Alexander, Martens, et al. (2004), who found that increasing the intensity of display elements does not improve performance on tasks dependent on that brightened information but does disrupt performance on tasks that depend on the information not highlighted, the results are in contrast to those of Ververs and Wickens (1998), who found no cost of high-intensity HUD information to the detection of midair targets viewed through the HUD. Subjective mental workload ratings revealed an interesting dissociation in which the subjectively easiest (lowest workload) display, the highlighted tunnel, did not support the best performance, as reflected in the flight path tracking and traffic awareness data. Rather, these subjective data were reflective of the amount of control activity generated with each guidance symbology in that the lower workload, highlighted tunnel produced lower elevator and aileron deflections than did the lowlighted tunnel. Finally, we noted that nearly all pilots failed to detect the rogue aircraft on their flight path
SYNTHETIC VISION SYSTEMS when their display-based automation directed them on a missed approach. Although we do not have eye-tracking data to confirm this, we infer that the SVS display was sufficiently compelling, particularly when used to support response to an unexpected abnormal event (the runway incursion), that pilots failed to cross-check the outside world. In summary, there was a clear cost to vertical flight path tracking with the FMA, with no offsetting benefit for traffic detection. In comparing the two tunnel formats, we found that lateral tracking was better with the lowlighted than with the highlighted tunnel on curved legs. Furthermore, the clutter invoked by the highlighted tunnel disrupted traffic detection by as much as 4 s, as compared with the lowlighted tunnel. Overall, the lowlighted tunnel enhanced traffic awareness without sacrificing flight path tracking, and it appeared to be the best of the three configurations, with the implication that intense stroke symbology for tunnel guidance is certainly not necessary and, possibly, not desirable.
701 EXPERIMENT 2 The goal of Experiment 2 is to determine the optimal combination of display size and geometric field of view (GFOV) for the primary flight display. Varying display size and GFOV yields different combinations of geometric effects. The combination of a large display size and a narrow GFOV represents the maximum degree of magnification. The combination of a small display size and a wide GFOV represents the maximum degree of minification or “compression” (i.e., reduction in size of elements represented within a given display space). This compression factor can be defined as the inverse of the display gain, as the latter is defined by the number of pixels per meter or ratio of the visual angle of the display to the visual angle of the world (VAD/VAW). This ratio (calculated for the four conditions examined, in the caption for Figure 3), which will almost always be less than 1, is directly analogous to the measure of the map scale as conventionally applied to 2-D maps. Note that the display size/
Figure 3. Flight path performance: mean absolute vertical deviation by display gain (diamonds and solid lines) and mean absolute lateral deviation by display gain (squares and dashed lines). The gains, from smallest to largest expressed by the ratio VAD/VAW, are created by the small/60° (0.4), large/60° (0.5), small/30° (0.77), and large/30° (1.0) conditions. The bars in the figure show ±1 standard errors from the mean.
702 GFOV combination with the maximum magnification is a special case that yields a gain of approximately 1.0, a unity gain. If such a display were superimposed on an HUD, it would provide conformal imagery (Weintraub & Ensing, 1992); that is, the symbology would overlay and move in consort with its far-domain counterparts. The ratio of VAD/VAW (as affected by both size and GFOV) might hurt flight path tracking at very small ratios because of the low display resolution at which the guidance symbology would be presented. A lower display resolution, portraying tracking error with a smaller number of pixels, has been shown in some studies to induce a lowered sense of urgency, and therefore lowered aggressiveness, in correcting that error as compared with a higher resolution depiction of the same information (Boeckman & Wickens, 2001; Doherty & Wickens, 2001; Stelzer & Wickens, in press; Onstott, 1976). In considering the effects of display size and GFOV separately, one would expect a smaller display to benefit traffic surveillance, given that fewer eye movements would be required to scan the small display area as compared with a larger display area, although one study has shown that pilots strategically compensate for display enlargements by adaptively altering their scan patterns (Stelzer & Wickens, in press). However, this surveillance benefit might be offset by clutter costs, given that the same amount of information shown in a larger display would be more densely packed in less space. Turning to the GFOV, a smaller GFOV showing less of the surrounding environment might produce keyholing, a lack of awareness of peripheral display elements (Woods, 1984), thus degrading SA; however, this cost might also be offset by the reduced clutter, given that less information would be depicted within a given display space. Regarding the observed effects of GFOV, Beringer and Ball (2001) compared conformal versus compressed HUD symbology through use of narrow (22°, conformal) and wide (40°, compressed) GFOVs. Results generally favored the wider GFOV, despite its compression. The wider GFOV essentially served to lower workload and decrease control activity as well as to support superior traffic detection performance, the latter effect pointing to the role of keyholing. Although the conformal HUD provided a unity gain, the
Winter 2005 – Human Factors narrow GFOV reduced the amount of preview available on curved legs. Stark, Comstock, Prinzel, Burdette, and Scerbo (2001) examined the effects of varying both display size and GFOV; they found no effect of size, but they did find that a wider GFOV was associated with an increase in lateral flight path tracking error, possibly the result of compression of tracking error, but also with a reduction in mental workload. Furthermore, pilots rated their subjective SA as being higher with the larger GFOV, although there was no objective measure of SA with which to compare this self-assessment. To add to this inconsistent pattern of results, both Wickens and Prevett (1995) and Doherty and Wickens (2001) varied GFOV in an exocentric and egocentric flight path tunnel display, respectively. Both found that the lower gain (high-GFOV) compressed display helped control in one axis but hurt it in the other. In contrast, Comstock, Glaab, Prinzel, and Elliott (2001) examined the additive effects of display size and GFOV and found no significant effects of display size and GFOV on flight path tracking performance, although pilots generally preferred the smaller GFOVs, especially for landing. It is important to note that these studies did not include any objective or subjective measures of SA. Given that SA is one issue at the heart of SVS research, we have sought to include objective measures of terrain awareness. Given the results of Experiment 1, we took the lowlighted tunnel in the sky as the “best” display and manipulated the way in which display distances represented world distances by varying the display size (small or large) and GFOV (magnifying, 30°, or minifying, 60°) of the world representation. Rather than focusing on traffic awareness, which was key in Experiment 1 because of the issue of clutter, in Experiment 2 we assessed terrain awareness by having pilots estimate landmark locations in the outside world, based on their representation on the display. Both display size and GFOV affect the ratio of the visual angle of the display to the visual angle represented in the world (VAD/VAW), which amounts to an expression of display gain. On the basis of our literature review, we hypothesized that higher display gains (smaller GFOVs; larger displays) would produce a greater sense of urgency in reducing flight path tracking
SYNTHETIC VISION SYSTEMS error (Stark et al., 2001), resulting in improved tracking performance (Hypothesis 2a); and that the smaller GFOV, presenting less depiction of the world, would contribute to a keyholing loss of SA (Hypothesis 2b; Beringer & Ball, 2001; Stark et al., 2001). Method Participants. Twenty-four pilots (21 men, 3 women) flew a sequence of eight flight scenarios designed to compare the four display size by GFOV formats. Twelve of these pilots had participated in Experiment 1, although prior experience had no effect on any of the dependent measures. Pilots ranged in age from 20 to 44 years (M = 24 years) with 639 mean total flight hours. All pilots had normal or corrected-tonormal vision and were paid $8/hr for their participation. Simulation. The simulation was the same as that used in Experiment 1. Displays. A lowlighted tunnel-in-the-sky display, similar to that used in Experiment 1, was configured according to different display sizes (small: 8 × 6.5 inches [20.3 × 16.5 cm]; large: 10 × 8 inches [25.4 × 20.3 cm]) and GFOVs (30° horizontal × 24.4° vertical or 60° horizontal × 48.8° vertical). For the four displays in question, gain values (VAD/VAW) ranged from 0.4 to 1.0, with the unity gain (maximum magnification) represented in the large 30° horizontal GFOV format and the 0.4 value (maximum compression) represented in the small 60° horizontal GFOV format. Task and experimental design. The task was similar to that used in Experiment 1, except that the focus was now on terrain awareness memory probes and each scenario was flown mostly in instrument meteorological conditions. Terrain awareness was assessed through the use of memory probes presented during simulation freezes. Eight colored square patches, easily visible, were placed on the displayed terrain throughout each scenario, and four of these patches were associated with a simulation freeze, which queried the location of that patch. During the simulation freezes the display would blank out and the outside world would turn black, such that a white ball was all the pilots could see. Pilots were required to move the white ball in the outside world screen to where they projected the colored patch
703 to be, based on where it was on the SVS display. No targets were presented during the final approach leg. The same unexpected event used in Experiment 1 (rogue aircraft on a missed approach path) was implemented in Experiment 2. Airspeed was again fixed at 100 knots until the final approach leg. A within-subjects, counterbalanced manipulation of display size and GFOV was used such that pilots experienced each of the four display size/GFOV combinations twice. Procedure. Pilots were instructed in the same manner as they were in Experiment 1. Pilots then flew two practice trials (one with the small display size 30° GFOV, one with the large display size 60° GFOV) and then the eight experimental trials, each of which was 8 to 10 min in length. Results The data were analyzed according to a withinsubjects repeated measures design. Less than 5% of the data were removed as outliers greater than ±3 standard deviations from the mean. Graphical analysis of the flight path deviation data (vertical and lateral deviation) revealed skewed distributions; therefore log transformations were performed on the flight path deviation data in order to produce more normally distributed data sets. Flight path performance. Lateral and vertical flight path errors, shown in Figure 3, were subject to 2 (display size) × 2 (GFOV) × 2 (leg type) repeated measures ANOVAs. Analysis of the vertical deviation data revealed that vertical deviations were smaller on curved (M = 4.41 m) than on straight (M = 4.88 m) legs, F(1, 23) = 7.99, p < .01, r = .51 (note that command path altitude changed only on straight legs). There were also main effects, approaching statistical significance, of both display size, F(1, 23) = 3.19, p < .09, r = .35, and GFOV, F(1, 23) = 3.28, p < .09, r = .35, such that vertical error was less with the small (M = 4.53 m) than with the large (M = 4.77 m) display and less with the 60° (M = 4.49 m) than with the 30° (M = 4.80 m) GFOV. The small size of these effects are such that they may be of limited practical significance. There were no significant interactions (all ps > .15). For lateral tracking, curved legs induced significantly larger deviations from the flight path than did straight legs (M = 10.6 vs. 5.92 m,
704 respectively), F(1, 23) = 84.8, p < .001, r = .89. This was expected, given that turns require the pilot to maneuver within the lateral dimension, whereas straight path segments do not. As with vertical tracking, lateral deviations were again less with the 60° GFOV (M = 6.89 m) than with the 30° GFOV (M = 9.58 m), F(1, 23) = 36.1, p < .001, r = .78. Although display size did not affect lateral error (p > .15), a significant Display Size × GFOV interaction, F(1, 23) = 11.1, p < .01, r = .57, stipulated that the benefit to performance of increasing GFOV was amplified with the larger display as compared with the smaller one. Terrain awareness. As discussed in the Method section, pilots were asked to indicate the location of certain highlighted terrain locations, which had been on the PFD, by positioning a cursor on the 180° outside world display panel. Overall, 11.4% of the probes were missed, and there was no effect of display condition on miss rate (all ps > .15). Judgment errors were determined by comparing the signed vectors between the location where pilots estimated terrain probes to be and the actual locations of those probes, expressed in degrees of visual angle of the outside world. In every display condition, pilots tended to estimate terrain locations as more toward the center of the display than was the true position of the terrain element, as if the SVS display representation of that element in the display (smaller when compared with the measured extent of the viewing screen) led them to bias their estimate inward. Examining the separate effects of display size and GFOV through a repeated measures ANOVA revealed a significant effect of GFOV, such that terrain probe estimation errors were greater (more inward) with the 30° (M = –14.5°) than with the 60° (M = –10.6°) GFOV, F(1, 23) = 21.1, p < .01, r = .69. Analyses revealed that this cost to the 30° GFOV was reflected in the mean absolute error as well, F(1, 23) = 4.86, p < .04, r = .42. There was no effect of display size, nor was there an interaction in either the signed or absolute errors (all ps > .15). Unexpected event. Only 7 of 24 pilots detected and maneuvered to avoid the rogue blimp visible only in the outside world. Of these 7 pilots, 4 had participated in the first study and 3 had not. The distribution of pilots who detected
Winter 2005 – Human Factors the rogue blimp was generally spread across display conditions. Discussion In Experiment 2 we manipulated the way in which display distances represented world distances in two ways: by varying the display size and by changing the GFOV (magnifying, 30°, or minifying, 60°) of the world representation. The purest form of the “urgency” hypothesis, presented as Hypothesis 2a, can be evaluated by comparing tracking error when the four display conditions are arranged along a display gain axis, as they are in Figure 3 (see page 701). The data clearly contradict the hypothesis that a larger gain would yield lower tracking error and that the “compression” of the smallest gain would increase error by reducing the urgency. Indeed, the trend in error is consistently in the opposite direction. More compression, in the form of a larger GFOV across both axes, and also in the form of a smaller display size in the vertical dimension, improved flight path tracking performance. On the one hand, the lack of a cost for compressed displays suggests that pilots were effectively able to compensate for the reduced display scale. These results are consistent with those of Beringer (2000), who also found less tracking error with a nonconformal, compressed display than with a conformal configuration. Pilots were, in essence, tracking aircraft position in real space, rather than tracking a symbol on display space; this behavior is appropriate and optimal. On the other hand, the actual degradation of flight path tracking with the least compressed display requires further explanation, as follows. In our initial urgency hypothesis, we had assumed that pilots were attending to (and minimizing) the deviation between ownship and the center of the tunnel. Therefore, the smaller the deviation (in pixels or visual angle), the less likely it would be corrected. Equivalently, the reduced aircraft symbol motion on the smaller scale would be less likely to be perceived as an error increase needing a correction. However, an alternative explanation, suggested in comments made by some of our participants, is that pilots were exercising control by attending to (and maximizing) the deviation between ownship’s position and the edge of the tunnel – when this deviation was perceived as small, control
SYNTHETIC VISION SYSTEMS was exercised. In this case, the opposite effect would be predicted: A smaller deviation from the tunnel’s edge (produced by the displays with lower gain) would be perceived as more urgent and would therefore be more likely to be corrected. One pilot commented that with the largerappearing tunnel (30° GFOV condition), he became somewhat “complacent” in thinking he had a lot of distance between ownship and the edge of the tunnel. Stated in other terms, the higher gain served to increase the apparent target size and hence induced less accurate positioning in the lateral dimension. Terrain awareness. Our terrain awareness response device essentially mimicked direct pointing to inferred locations in the outside world of display-depicted elements. Across all displays, pilots tended to point more toward the center of the screen than was the true position of the terrain element, as if the representation of that element in the “small” display (compared with the 180° measured extent of the viewing screen) led them to bias their estimate inward. However, contrary to our hypothesis that the greater compression from unity would further distort terrain probe estimation, we actually found an effect approaching significance in the opposite direction. The unity display was never better, and in fact both 30° GFOV displays showed significantly poorer performance than did the 60° GFOV displays, even though the former had less distorting compression. In interpreting this effect, we infer that a unity scale provides no benefit for a nonoverlaid display (e.g., a headdown display). This finding is consistent with that of Wickens and Long (1995), who observed conformal, unity gain benefits in other tasks, but only with a head-up display. Furthermore, reducing the amount of terrain viewable (small GFOV) produces the same sort of keyholing that, as we saw in the flight path tracking data, disrupts the ability to maintain position and spatial orientation. It seems that the larger GFOV supports a greater, more continuous calibration of the display locations with outside world locations, as more points in the terrain may be available to cognitively link the two views through some form of visual momentum (Woods, 1984), a finding consistent with recent work by Wang and Milgram (2003). To summarize, the collective results of Ex-
705 periment 2 allow us to reject the hypothesis that “bigger is better” (see also Stelzer & Wickens, in press; Wickens, van Offlen, et al., 2003), and, within the range of GFOVs and display sizes examined here, to conclude that smaller displays are at least as good as, if not sometimes better than, large ones. This conclusion holds across both variables manipulated here: smaller physical size displays and displays that decrease the physical representation size via compression with a large GFOV when presented head down. In fact, the data generally support the benefits of the wide GFOV display. This conclusion, however, is obviously constrained by the range of sizes (or display gains) considered here. Our current work examined display gains from only 0.4 to 1.0. We would assume that extremely small, minified displays could impose difficulties with legibility and clutter created by many closely located symbols (Kroft & Wickens, 2003). GENERAL DISCUSSION In general, the results pointed to an overall advantage for lowlighted tunnels (Experiment 1) presented with a larger GFOV with no cost for a relatively small display (Experiment 2). To summarize, flight path tracking was poorest and most variable with the single-point FMA as compared with two tunnel displays in Experiment 1. A tunnel display contains important perceptual properties supporting guidance (Mulder, 2003) – namely, flight path preview inherent to the multiple tunnel segments — whereas such preview is missing from the FMA. In particular, our findings reveal that there is value in presenting the extra “strokes” defining the tunnel information as long as it is done at a low intensity when the SVS display is also used to host traffic information. Experiment 2 provided no clear evidence for the role of a size-mediated urgency function in flight path tracking within the particular display sizes examined, adding to the ambiguous set of results from other studies, of which some have shown improved tracking performance with larger displays but others have not. (Note that these sizes are larger than displays found on current commercial aircraft but are within the range of sizes proposed for SVS; Prinzel et al., 2004.) These differences in size-mediated urgency effects
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are worthy of further investigation. In terms of GFOV, flight path tracking within both dimensions was better with the larger 60° GFOV. Furthermore, evidence for a keyholing effect on maintaining SA was found in that the estimation of terrain element position was least accurate with the two larger display gain conditions defined by the 30° GFOV. Limitations of the current studies include the lack of a control condition in which no tunnel guidance was provided. However, although current data trends do not indicate whether or not cognitive tunneling would have been observed without the tunnel guidance, converging evidence reveals that such tunneling might not be seen in the absence of tunnel guidance (Wickens, Alexander, Thomas, et al., 2004). In one such case, a comparison of tunnel versus no tunnel showed that those pilots who failed to detect a rogue aircraft were flying with a tunnel, whereas successful detection was achieved by all those flying without a tunnel. Another limitation of the current studies is that caution should be exercised in generalizing the findings of this laboratory-based simulation to the anticipated circumstances of using SVS displays in an actual cockpit. Furthermore, although all pilots were either certified flight instructors or engaged in instructor training, they had relatively few flight hours as compared with commercial or corporate aviation pilots; this also could have implications when generalizing these results to other pilot populations. ACKNOWLEDGMENTS This material is based upon work supported by NASA Langley under Grant NASA-NAG-102071, for which Lawrence Prinzel was the scientific/technical monitor. Grant NASA-NAG1-03014 from NASA Ames provided funding for the development of the SVS simulation. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of NASA. Special thanks to Ron Carbonari, Roger Marsh, Jonathan Sivier, and Sharon Yeakel for their help in programming; to Don Talleur for his expertise in designing the flight paths; and also to Robert Bernard for his help in running Experiment 2.
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707 Wickens, C. D., & Prevett, T. T. (1995). Exploring the dimensions of egocentricity in aircraft navigation displays. Journal of Experimental Psychology: Applied, 1, 110–135. Wickens, C. D., van Offlen, P. J., Muthard, E. K., Alexander, A. L., & Podczerwinski, E. S. (2003). The influences of display highlighting and size and event eccentricity for aviation surveillance. In Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting (pp. 149–153). Santa Monica, CA: Human Factors and Ergonomics Society. Williams, K. (2002). Impact of aviation highway-in-the-sky displays on pilot situation awareness. Human Factors, 44, 18–27. Woods, D. D. (1984). Visual momentum: A concept to improve the cognitive coupling of person and computer. International Journal of Man-Machine Studies, 21, 229–244. Yeh, M., & Wickens, C. D. (2001). Attentional filtering in the design of electronic map displays: A comparison of color-coding, intensity coding, and decluttering techniques. Human Factors, 43, 543–562.
Amy L. Alexander is a cognitive scientist in the Cognitive Science and Engineering Group at Aptima, Inc., Woburn, Massachusetts. She earned her Ph.D. in psychology from the University of Illinois at UrbanaChampaign in 2005. Christopher D. Wickens is a professor of psychology at the University of Illinois at Urbana-Champaign. He earned his Ph.D. in psychology from the University of Michigan in 1974. Thomas J. Hardy is a flight instructor at the University of Illinois at Urbana-Champaign. He earned his B.S. in psychology and aviation human factors from the University of Illinois at Urbana-Champaign in 2003. Date received: December 1, 2003 Date accepted: February 21, 2005
