Head-Up Display for Current Force Vehicles 

by Jessie Y. C. Chen and Razia V. Nayeem 

ARL-TR-5167 May 2010 

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ARL-TR-5167 May 2010 

Head-Up Display for Current Force Vehicles 

Jessie Y. C. Chen and Razia V. Nayeem 

Human Research and Engineering Directorate, ARL 

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14. ABSTRACT 

The Scalable Embedded Training - Mission Rehearsal Army Technology Objective of the U.S. Army Research, Development, and 

Engineering Command Simulation and Training Technology Center is developing an innovative prototype visual imaging system, the 

switchable vision block, for embedded vehicle driver training, mission rehearsals, and mission operations. The effort will focus on 

current force combat vehicle vision blocks and night driving sensors. U.S. Army Research Laboratory researchers are designing a 

head-up display (HUD) that can overlay driving-related information (e.g., speed, fuel, engine feedback) on the vision blocks as well as 

provide situational awareness and C4 information to the driver. Drivers of Bradley and Stryker vehicles at Ft. Benning, GA, and U.S. 

Army Tank-automotive and Armaments Command were surveyed, and their recommended design features of the HUD were 

incorporated in the prototype HUD. HUDs have been found to be an effective means to enhance pilot situational awareness by 

making information more accessible to the pilot. However, past research has also shown that large amounts of information, while 

helpful in reducing the operator’s scanning effort by providing more data in a centralized area, can create visual clutter and degrade 

the operator’s information processing due to cognitive overload. Additionally, overlaying information on the vision blocks can

potentially lead to attentional narrowing, as an operator’s attention can be captured by the overlaid data while important 

elements/developments in the environment might be overlooked. Therefore, the display design tradeoffs between adding information 

to the vision blocks and the potential attentional narrowing effects need to be systematically evaluated. A study was conducted to 

evaluate differences in performance using a HUD vs. a traditional head-down display (HDD). Results showed that for objective 

driving performance, the HUD actually results in slightly worse performance and produces an attentional narrowing effect. However, 

on self-report measures, participants preferred the HUD to the HDD. 

15. SUBJECT TERMS

head-up display, driving performance, user interface design, attention 

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Jessie Y. C. Chen 

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iii 

Contents 

List of Figures v

List of Tables vi

Acknowledgments vii

1. Introduction 1

1.1 Background .....................................................................................................................1

1.2 Head-Up Display (HUD).................................................................................................2

1.3 Driver Surveys .................................................................................................................4

1.3.1 Additions to the Current HDD Design ................................................................4

1.3.2 Distractions to Driving With the Current HDD Display .....................................5

1.3.3 Layout of the Future HUD Design ......................................................................6

1.3.4 HUD Design ........................................................................................................6

1.4 Current Study ..................................................................................................................7

2. Method 8

2.1 Participants ......................................................................................................................8

2.2 Apparatus.........................................................................................................................8

2.2.1 Simulator .............................................................................................................8

2.2.2 Head-Up Display .................................................................................................9

2.2.3 Head-Down Display ............................................................................................9

2.3 Surveys and Tests ............................................................................................................9

2.4 Experimental Design .....................................................................................................10

2.5 Procedure .......................................................................................................................10

2.6 Measures ........................................................................................................................11

3. Results 11

3.1 Driving Performance .....................................................................................................11

3.2 IED Identification ..........................................................................................................12

3.3 Gauge Anomaly Clearing ..............................................................................................12

3.4 Perceived Workload and Performance ..........................................................................13
iv 

3.5 Sickness Symptoms .......................................................................................................13

3.6 Map Reading Test Correlations .....................................................................................13

3.7 Participant Preference ....................................................................................................13

4. Discussion 14

5. Conclusions 15

6. References 16

Appendix A. Demographic Questionnaire 19

Appendix B. Map Reading Test 21

Appendix C. NASA-TLX Questionnaire 23

Appendix D. Simulator Sickness Questionnaire 27

List of Symbols, Abbreviations, and Acronyms 31

Distribution List 32 
v 

List of Figures 

Figure 1. Stryker vehicle interior. ...................................................................................................1

Figure 2. SVB concept. ...................................................................................................................2

Figure 3. HUD projected onto background.....................................................................................7

Figure 4. Collimated display viewing box and simulated driving equipment. ...............................8

Figure 5. Sample route used in an experimental scenario. .............................................................9

Figure 6. Number of vehicle collisions, stop signs run, number of times the vehicle driving 

off road, and speed by condition. .............................................................................................12

Figure 7. Number of IEDs missed, distance to IED identification, and response times for 

gauge anomalies clearing by condition. ...................................................................................13
vi 

List of Tables 

Table 1. Additions to the current HDD design. ..............................................................................5

Table 2. Distractions to driving with the current HDD design. ......................................................5

Table 3. Layout of the future HUD design. ....................................................................................6

Table 4. Operator task performance and subjective assessments. ................................................11 

Table D-1. Baseline (pre) exposure symptom checklist. ..............................................................29

Table D-2. Post 00 minutes exposure symptom checklist. ...........................................................30
vii 

Acknowledgments 

This project was funded by the U.S. Army Scalable Embedded Training - Mission Rehearsal 

Army Technology Objective. The authors would like to thank the U.S. Army Research, 

Development, and Engineering Command Simulation and Training Technology Center, in 

particular, Mr. Angel Rodriguez and Ms. Bonnie Eifert, for sponsoring this research. 

The authors would also like to thank Dr. Roger Hamilton for his help in collecting surveys from 

Bradley and Stryker drivers and the survey participants for their time and information. 
viii 

INTENTIONALLY LEFT BLANK. 
1 

1. Introduction 

1.1 Background 

The Scalable Embedded Training - Mission Rehearsal (SET-MR) Army Technology Objective 

(ATO) of the U.S. Army Research, Development, and Engineering Command (RDECOM) 

Simulation and Training Technology Center (STTC) is developing a new prototype visual 

imaging system called a switchable vision block (SVB) to be used for embedded vehicle driver 

training, mission rehearsals, and mission operations (see figure 1 for the interior of a Stryker 

vehicle). A vision block is a solid, periscope-like apparatus that allows the crew inside a fighting 

vehicle to see the outside through a series of mirrors inside a box, one side of which is facing the 

outside environment and the other side of which the operator looks through. An SVB is a way to 

extend the capability of a regular vision block system with different operating modes—normal 

optical view, combined view (similar to a head-up display [HUD]), and a synthetic image for 

displaying additional information such as vehicle status (see figure 2 for a depiction of the SVB 

[Montoya et al., 2007]). 

Figure 1. Stryker vehicle interior. 
2 

Figure 2. SVB concept (Montoya et al., 2007). 

One of the key advantages to using an SVB is it gives the crew a common interface for both 

training and operating the vehicle. Additionally, extra elements can be displayed on the screen, 

such as maps, enemy/friendly information, or even relevant training elements, which can be 

helpful in training as well as operation. Added benefits include giving the crew the ability to 

maintain their vehicle position and orientation, giving the crew the ability to maintain position 

relative to friendly and enemy forces, giving the crew the ability to detect very close entities, and 

being easily compliant with several different vehicles. The SET-MR ATO of RDECOM-STTC 

is currently developing an SVB system that utilizes a collimated optical display, which is widely 

used in aircraft HUDs, for the overlayed symbology to appear to be at an optically infinite 

distance from the operator (Montoya et al., 2007). The advantage of such collimated displays is 

reduced visual misaccommodation for the operator since the overlayed images are displayed at 

the same optical depth as the outside world (Crawford and Neal, 2006). As part of the SVB 

effort, the U.S. Army Research Laboratory - Human Research and Engineering Directorate 

designed a HUD for the current force vehicles (see section 1.3 on the design process) that could 

be used in operational (i.e., driving) settings, in addition to its purposes for training and mission 

rehearsal. The following section briefly reviews the advantages and disadvantages associated 

with HUDs reported in the literature, followed by a summary of surveys of current-force vehicle 

drivers and the design process of our HUD. Section 2.5 reports a simulation experiment to 

investigate the effectiveness of the HUD and potential operator performance issues. 

1.2 Head-Up Display (HUD) 

HUDs are being increasingly used in aviation and have started being used in automobile driving 

and racing (BMW, 2009; Microvision, 2009; Sportvue, 2009). Some studies suggest that HUDs 

in automobiles are not that useful for things such as speed, tachometer, etc., but are mostly useful 

for directions and navigation (CNN, 2009). Most of the research in HUDs has been conducted in 

aviation, but there are studies conducted in ground vehicles, and many of the aviation findings 

can be extrapolated to ground vehicles. In aviation, HUDs are being used to increase situation 
3 

awareness (SA) for pilots in all segments of flight, including takeoff and landing, which are 

typically the most difficult times of a flight. While HUDs that project pathways have been 

shown to cause a slight decrement in vertical tracking, they also cause an improvement in event 

detection, horizontal tracking, and navigation on the ground (i.e., taxiing) (Crawford and Neal, 

2006; Fadden et al., 2001; French et al., 2006; Hooey and Foyle, 2006). These findings would 

likely extend to automobiles since the environment is very similar to taxiing an aircraft 

(Crawford and Neal, 2006). 

The main advantages of HUDs (as compared to head-down displays [HDDs]) include the 

following: (1) reduced scanning distance between instrumentation and the outside world, 

(2) increased SA of the external environment due to more visual attention to the outside world 

and less head-down time, and (3) the location gives a longer focal distance so the focal transition 

is easier for users (i.e., less visual misaccommodation) (Crawford and Neal, 2006; MartinEmerson and Wickens, 1997; Tufano, 1997). Horrey and Wickens (2004a) found that HUDs are 

typically superior to HDDs because they utilize both the ambient visual system (peripheral 

vision) and the focal visual system. They showed that, while ambient vision can support some 

aspects of driving, such as vehicle control, this lessens as display separation increases, such as in 

HDDs. Additionally, they found that ambient vision cannot adequately support hazard 

awareness, so drivers are likely to miss obstructions in roadways when looking down at gauges 

in an HDD that they might otherwise notice in a HUD. 

One area in which HUDs are particularly useful is when the outside environment is poor, such as 

rain or fog, because high-quality HUD images (typically collimated in the aviation domain) 

make the user focus further out which reduces visual accommodation problems (Crawford and 

Neal, 2006). However, very high-quality HUDs have been shown to capture attention too well 

and can divert attention away from other sources (Crawford and Neal, 2006). There is also some 

evidence that collimation does not always pull the operator’s visual focus outward to optical 

infinity and, in some cases, visual misacommodation may become worse due to collimated 

displays (Crawford and Neal, 2006). 

Although there are many advantages associated with HUDs, past research has shown various 

human performance issues that can be induced by HUDs. One study showed that HUDs resulted 

in a faster reaction time to obstructions in the roadway than with HDDs, but that was only true of 

expected objects—with unexpected objects, such as a pedestrian running into the roadway, the 

reaction time was slower with a HUD (Tufano, 1997). Another study showed that HUDs can 

cause users to completely miss targets, whereas HDDs did not, and the difference in missed 

targets was statistically significant (Crawford and Neal, 2006). However, the findings in the 

literature are not always consistent. For example, Horrey and Wickens (2004a) demonstrated 

that there was no increase in hazard detection time with a HUD vs. an HDD in a simulated 

driving task. Nevertheless, HUDs may create a false sense of awareness in users because, 

typically, users give HUDs a high rating and believe they are seeing all the pertinent information 
4 

because it is being presented in their visual fields, but they do not realize there could be other 

information they are neglecting to attend to (Crawford and Neal, 2006). 

While some studies have found clutter to be an issue with overlayed HDDs, Horrey and Wickens 

(2004b) found no differences between superimposed HUDs and adjacent HUDs with respect to 

driving performance and secondary task performance. Additionally, vehicle control is largely 

achieved by the ambient visual system, which is less affected by clutter than the focal system. 

The success of HUDs in automobiles will largely depend on the usefulness of the information 

displayed to the driver by the HUD; therefore, the information displayed will have to provide a 

larger advantage to the driver than the disadvantages seen (Tufano, 1997). 

The current research investigated the quantifiable performance differences in drivers using 

HUDs and HDDs to determine performance differences between the two displays for Bradley 

and Stryker fighting vehicles. 

1.3 Driver Surveys 

To understand how drivers use displays when performing various job tasks, 35 Bradley and 

Stryker drivers from Ft. Benning, GA, and from the Tank-automotive and Armaments Command 

completed surveys about using their current displays and potential HUDs. The most relevant 

data collected for designing a HUD are as follows and will be used for display recommendations 

in both platforms. The main categories are additions to the current HDD design, distractions to 

driving with the current HDD design, layout of the future HUD design, and the actual HUD 

design. 

1.3.1 Additions to the Current HDD Design 

Drivers were asked “Given any information in the vehicle (i.e., situation awareness, command, 

control, communication, and computer information), what would you like to see on the screen?” 

and “What information might other crew members have that you currently don’t have convenient 

access to, which would you like to have?” Of the 35 respondents, 31 (88.6%) said they would 

add components to the current HDD design. The most popular answers to the question can be 

seen in table 1 as well as how many respondents reported each item. 

As shown in table 1, most of the components drivers wanted to be added were indicators and 

gauges, with only four items related to other mission elements, such as situation awareness. 

These were outside camera views, inside camera views, weather, and wider range of view. As 

such, one might conclude that drivers have very little additional need for situation awareness aids 

but need more information about basic components of the vehicle so they can drive effectively. 
5 

Table 1. Additions to the current HDD design.

Item No. Reported 

Digital speedometer 15 

Outside camera views 15 

Grid position/map 14 

Ammunition count/type 14 

Compass/direction of travel 11 

Fuel gauge 11 

Turret position 10 

Oil temperature 9 

Battery life 9 

Water temperature 8 

Oil pressure 8 

FBCB2 8 

1.3.2 Distractions to Driving With the Current HDD Display 

Drivers were asked “Which instruments must you look at a lot now that may briefly distract you 

from your driving?” Of the 35 respondents, 31 (88.6%) said there were components in the 

current HDD design that distracted them while they were driving. The most popular answers to 

the question can be seen in table 2 as well as how many respondents reported each item. 

Table 2. Distractions to driving with the current HDD design.

Item No. Reported 

Speedometer 17 

Oil/engine temperature 17 

Fuel 7 

As shown in table 2, all the components that distracted drivers in the current HDD display are 

functional components. Also, there is overlap between what some drivers want to add to the 

current display and what distracted some. This could be from varying display components 

between the Bradley and Stryker, but could also be from driver preference. Implications of this 

overlap will be discussed later. 
6 

1.3.3 Layout of the Future HUD Design 

Drivers were asked “If we could display the information you would like to see in the new vision 

block, how do you think it should be displayed? For example, which area of the screen, colors 

used, audible alerts, etc.?” Of the 35 respondents, 30 (85.7%) gave suggestions about the layout 

of the display. The most popular answers to the question can be seen in table 3 as well as how 

many respondents reported each item. 

Table 3. Layout of the future HUD design.

Item No. Reported 

Lower part of the screen 15 

Red/flashes for alert 14 

Green for good/ample 13 

Amber 13 

As table 3 shows, most of the responses were in relation to placement of components on the 

screen and color. Also, with respect to color, drivers wanted a traditional color scheme where 

green indicates something good, red indicates something bad, and amber or yellow indicates 

something that could become bad in the near future. 

1.3.4 HUD Design 

Using the information from the surveys, a HUD was developed (see figure 3). Each component 

of the HUD was suggested by drivers. Across the top of the display is a heading indicator with 

turret direction indicated by an arrow. A small map of the surrounding area is displayed in the 

upper left corner, and six gauges are displayed in the upper-right corner, which are fuel, battery, 

ammunition count, oil temperature, oil pressure, and water temperature. An analog speedometer 

is in the bottom middle and has the speed digitally shown at the bottom of the speedometer. 

Additionally, a gear indicator is just right of the speedometer. The bottom corners were left open 

due to comments about the need to search for improvised explosive devises (IEDs) in those 

areas. The HUD was used in the current experiment comparing the HUD to an HDD. With 

respect to the overlapping components, it was decided that since the three most overlapping 

components were critical gauges with mission-relevant information, the risk of not having that 

information when needed was greater than the distraction they might provide, so they were all 

included in the HUD design. 
7 

Figure 3. HUD projected onto background. 

1.4 Current Study 

In this experiment, we compared driving performance on a simulator using a collimated HUD 

(see section 2.2, Apparatus) vs. a traditional HDD. The primary task was driving a 

predetermined route, and the secondary tasks were monitoring the roadways and adjacent areas 

for IEDs and monitoring gauges for anomalies. It was hypothesized that the HUD would result 

in better overall driving performance, as well as subjective self-report measures, than the HDD 

because studies have shown that participants are more successful at driving when information is 

displayed in an integrated fashion rather than in separate displays (Horrey and Wickens, 2004a, 

2004b). Driving performance was comprised of number of collisions, number of stop signs run, 

number of times vehicle left the roadway, and average speed. Subjective workload and 

performance were also measured, as well as subjective sickness symptoms. Secondary task 

performance was comprised of number of IEDs missed, distance to IED when IED was 

identified, number of gauge anomalies cleared, and response time to clear gauge anomalies. 
8 

2. Method 

2.1 Participants 

Twenty participants from the University of Central Florida area were recruited to participate in 

the study. The age range was between 18 and 36, and a valid driver’s license was required for 

participation. Individuals were informed that participation was voluntary and that they could 

withdraw at any time without penalty. Participants were paid $15/h for their participation. 

2.2 Apparatus 

2.2.1 Simulator 

The game engine used in this experiment was ManiaDrive.* This engine is software that can be 

run on any standard computer and is the environment in which participants navigated in the 

simulated driving routes. The driving scene was displayed using a collimated display, which is 

viewed by looking into a display box and appears to be at an optically infinite distance from the 

viewer (Montoya et al., 2007). A Logitech steering wheel and gas and brake pedals were used 

for participants to navigate through the game engine (see figure 4 for the experimental setup) 

Figure 4. Collimated display viewing box 

and simulated driving 

equipment. 

 *

ManiaDrive by Raydium is a free clone of the game TrackMania, a registered trademark of Nadeo Studios. 
9 

2.2.2 Head-Up Display 

The HUD information unit was placed at the top of the viewing box (see figure 4), and its 

imageries were projected onto the driving scene via mirrors in the box (see figure 3). Figure 5 

shows a sample route used in an experimental scenario. 

2.2.3 Head-Down Display 

For this condition, participants still viewed the driving environment through the box as shown in 

figure 4 (using the collimated display), but the imageries were presented in a separate computer 

screen placed below the box (to the left of the steering wheel, see figure 4), simulating how one 

would view the instrument panel in an automobile by looking from the windshield down to the 

panel (i.e., HDD). 

Figure 5. Sample route used in an experimental 

scenario. 

2.3 Surveys and Tests 

Participants first completed an informed consent and a demographics questionnaire 

(appendix A). Participants completed “The Map Reading Test” (appendix B) (Money and 

Alexander, 1966), which required them to follow a route on a map and indicate the direction 

(i.e., right or left) at each turn. The participant’s score was the number of correct responses 

within the time limit of 20 s. 
10 

Participants’ perceived workload was evaluated using the National Aeronautics and Space 

Administration Task Load Index (NASA-TLX) questionnaire (Hart and Staveland, 1988; see 

appendix C). The NASA-TLX is a self-reported questionnaire of perceived demands in the 

following six areas: mental, physical, temporal, effort (mental and physical), frustration, and 

performance. Participants used this questionnaire to evaluate their perceived workload level in 

these areas on 10-point scales as well as completing pairwise comparisons for each subscale. 

The subscale of performance was also analyzed on its own. 

The Simulator Sickness Questionnaire (SSQ) was used to evaluate participants’ simulator 

sickness symptoms (Kennedy et al., 1993; see appendix D). The SSQ consists of a checklist of 

16 symptoms. Each symptom is related in terms of degrees of severity (none, slight, moderate, 

and severe). A total severity score was derived by a weighted scoring procedure and reflects 

overall discomfort level. 

2.4 Experimental Design 

The overall design of the study was a repeated measures design, with each participant 

completing all routes. The independent variable was Display Type, and it had two levels—HUD 

and HDD. The order of presentation for the experimental conditions was determined by a 

Williams Square. 

2.5 Procedure 

Upon arrival to the study, participants were briefed on the purpose of the study, and they signed 

the informed consent form, completed the demographics questionnaire, and had their questions 

answered. Participants then received practice on the driving tasks and familiarized themselves 

with images of IEDs (images were not present when participants completed driving trials) and 

with the gauges that showed anomalies. 

For the experimental trials, participants were asked to drive a predefined route while following 

certain guidelines, such as speed limits, lane-keeping behavior, and stop sign behavior. 

Participants were also asked to monitor the roadway and adjacent areas for IEDs. Participants 

were instructed that if an IED was spotted, they should press a button to acknowledge the IED. 

Additionally, while driving, participants were asked to monitor the gauges on the displays and 

press a button when a gauge had an anomaly to acknowledge it. Participants completed four 

trials using four different, but comparable, driving routes—two trials with the HUD and two with 

the HDD. Trials were counterbalanced using a Williams Square to avoid order effects. After 

each trial, participants assessed their workload and sickness symptoms by using the NASA-TLX 

and SSQ, respectively. There was a 5-min break between trials. After all trials were completed, 

participants were compensated and fully debriefed, having all their questions answered. Each 

trial took ~5 min, and the experiment took ~1 h. 
11 

2.6 Measures 

Driving performance was comprised of number of collisions, number of stop signs run, number 

of times vehicle left the roadway, and average speed. Subjective workload and performance 

were also measured as well as subjective sickness symptoms. Secondary task performance was 

comprised of number of IEDs missed, distance to IED when IED was identified, number of 

gauge anomalies cleared, and response time to clear gauge anomalies. 

3. Results 

Table 4 lists several measures relating to operator driving performance, secondary task 

performance, SSQ, subjective workload, and performance assessments. All tests were 

performed using a statistical program SPSS 16 with an alpha level of 0.05. There were no 

outliers or abnormal data unless otherwise noted. Paired samples t-tests were performed on 

each variable between the HUD condition and HDD condition. Additionally, Pearson’s 

correlations were run between the map reading test and driving performance variables. 

Table 4. Operator task performance and subjective assessments. 

Measures 

Display 

HUD HDD 

Primary (Driving) Task Performance 

Number of collisionsa 0.35 (0.5) 0.05 (0.22) 

Number of stop signs runb 1.05 (0.65) 1.98 (0.51) 

Number of times vehicle leaves roadway 2.28 (1.66) 1.5 (1.84)

Average speed in kphb 26.76 (3.91) 29.8 (3.35)

Secondary Task Performance 

Number of IEDs misseda 4.05 (0.76) 3.6 (0.84)

Distance to IED when identified IED in world units 4.46 (4.42) 5.90 (3.22)

Number of gauge anomalies cleared 0.95 (0.22) 0.93 (0.24)

Response time to clear gauge anomalies in seconds 8.2 (13.91) 13.39 (10.11)

Subjective Assessments 

NASA-TLX overall score 30.85 (6.8) 29.5 (7.1)

Performance score—subscale of NASA-TLX 3.78 (1.45) 4.4 (1.76)

SSQ score 8.41 (9.39) 6.26 (5.95)

Note: Standard deviations are presented in parentheses. 

a

p < .05. b

p < .01. 

3.1 Driving Performance 

Analysis on the number of collisions showed that participants had significantly more collisions 

in the HUD condition than when in the HDD condition, t(19) = 2.26, p = 0.036. The t-test on 

running stop signs showed that participants ran significantly more stop signs in the HDD 

condition than in the HUD condition, t(19) = –8.37, p < 0.000. Analysis on average speed 
12 

showed that participants drove significantly faster in the HDD condition than in the HUD 

condition, t(19) = –4.79, p < 0.000. However, the t-test on number of times the vehicle left the 

roadway did not show a significant difference between the HUD condition and the HDD 

condition, t(19) = 1.88, p = 0.076. It is important to note that the difference in average speed 

might be attributed to the increased number of collisions in the HUD condition and the increased 

number of stop signs run in the HDD condition; thus, participants were stopping more in the 

HUD condition, so that could be why their average speed was higher in the HDD condition. 

Figure 6 shows the four driving-related performance measures. 

Figure 6. Number of vehicle collisions, stop signs run, number of times the 

vehicle driving off road, and speed by condition. 

3.2 IED Identification 

With respect to IED detection, route 2 was taken out of the final analyses. In this route, only two 

participants out of 20 detected any IED, so this condition was treated like an outlier for this 

variable, and the data were removed prior to analysis. For number of IEDs missed, the t-test 

showed that participants missed significantly more IEDs when in the HUD condition than when 

in the HDD condition, t(19) = 2.49, p = 0.022. For distance to IED when IED was identified, the 

analysis also showed there was not a significant difference, t(19) = –0.13, p = 0.209. The overall 

IED behavior can be seen in figure 7. 

3.3 Gauge Anomaly Clearing 

The first analysis of number of gauge anomalies showed there was no significant difference 

between the HUD condition and the HDD condition, t(19) = 1.00, p = 0.33. For the analysis of 

response time to clear gauge anomalies, there was one outlier for both conditions that was 

removed from the data, so the analysis was done on 19 participants rather than 20. The t-test 

showed there was no significant difference in response time to clear gauge anomalies between 

the HUD condition and the HDD condition, t(18) = –1.18, p = 0.255 (figure 7). 

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29.5

30

30.5

0

0.5

1

1.5

2

2.5

HUD HDD

Collisions

Stop Signs Run

Offroad

Speed
13 

Figure 7. Number of IEDs missed, distance to IED identification, and response times 

for gauge anomalies clearing by condition. 

3.4 Perceived Workload and Performance 

The overall NASA-TLX score was analyzed by condition. The analysis showed no significant 

difference between the two conditions, t(19) = 1.86, p = 0.079. In addition to the overall NASATLX workload score, the subscale of performance was analyzed. The analysis showed no 

significant difference between the two conditions, t(19), p = 0.059. 

3.5 Sickness Symptoms 

The analysis showed no significant difference between the HUD condition and the HDD 

condition, t(19) = 1.48, p = 0.156. 

3.6 Map Reading Test Correlations 

There was a negative correlation between participants’ map reading test (MRT) scores and the 

number of times their vehicle was driving off road in the HDD condition, r = – 0.438, p = 0.027. 

Those with lower MRT scores tended to drive off road more frequently than did those with 

higher MRT scores. There was also a significant correlation between the MRT scores and selfassessed performance in the HUD condition, r = 0.457, p = 0.043. Those with higher MRT scores 

tended to assess their own driving performance as better than did those with lower MRT scores. 

3.7 Participant Preference 

At the end of the experiment, the researcher asked participants which display they preferred. 

Sixteen participants (80%) said they preferred the HUD to the HDD. Though they were not 

asked to elaborate on why, several participants said they preferred not having to scan back and 

forth so much between displays. Interestingly, participants’ preferences mostly were not in 

accordance with their performance.

0

2

4

6

8

10

12

14

HUD HDD

IEDs Missed

Distance to IED

Gauge RT
14 

4. Discussion 

As the results indicate, the HUD produced slightly worse driving performance (i.e., more 

collisions and slower driving speed) than the HDD (i.e., more stop signs violations), although 

many of the secondary tasks had no significant differences between the two conditions. One 

significant finding is participants missed more IEDs in the HUD condition than in the HDD 

condition. This result suggests that, when using the HUD, participants tended to pay less visual 

attention to the driving environment than when using the HDD. In other words, the results 

indicate that participants neglected the driving environment and experienced some cognitive 

tunneling of attention, also known as attentional narrowing, when using the HUD, as has shown 

in past research (Crawford and Neal, 2006; Tufano, 1997; Wickens, 2005). The term cognitive 

tunneling most often refers to a broad, overarching concept, including things such as attentional 

narrowing, visual narrowing, spatial narrowing, etc., whereas attentional narrowing specifically 

refers to the tunneling of attention, without any other narrowing factors. Much as Crawford and 

Neal (2006) found, it appears participants had a false sense of security when using the HUD, as 

they rated their performance the same with the HUD and the HDD, although their actual 

performance was sometimes worse with the HUD. This could be from differences in 

metacognitive abilities. It has been shown that people who have lower metacognition often rate 

themselves as performing better than they actually do, but as metacognition increases, people 

rate their performance closer to what it actually is. Thus, if participants had better 

metacognition, such as experts do, they might rate their performance on the displays to be more 

in line with their actual performance (Kruger and Dunning, 1999). One way to potentially 

mitigate this effect would be to measure metacognition and use this as a covariate in future 

studies. 

According to our surveys, Bradley and Stryker drivers are in favor of replacing their current 

displays with a HUD-like display. It is anticipated that the HUD could provide advantages over 

the traditional HDD (e.g., easy access to the map or global positioning system information and 

other driving-related information); however, the attentional narrowing effect of the HUD, as 

demonstrated in the current study and numerous previous studies, needs to be further 

investigated. More research needs to be conducted to mitigate the attentional narrowing effect, 

so HUDs can be more effective. 

It is important to note that the routes used in this experiment were fairly simple and 

straightforward. Had more difficult routes been used, participants likely would have had to 

divert their attention from the driving environment down to the information needed in the HDD 

condition, and the performance for that condition might have been worse. Additionally, the 

routes were not randomized between conditions, so the same two routes were used for every 

participant for the HUD condition, and the same two routes were used for every participant for 
15 

the HDD condition. The routes were organized this way to ensure that each route would be 

completed an equal number of times; however, this could have been a confound in the 

experiment, especially with respect to IED detection, so for future studies, each route should 

have the same chance of being used in the HUD or the HDD condition. Finally, those 

participants with lower map reading test scores drove off road significantly more times than did 

those with higher test scores when the display was HDD. It is reasonable to expect that those 

individuals with poorer map reading skills may have significantly degraded driving performance 

if the routes are more complicated and they need to consult the map more frequently. 

5. Conclusions 

This study supports the notion that using a HUD while driving may lead to attentional narrowing 

and an overall lack of situation awareness, leading to worse driving performance than when 

using a traditional HDD. However, participants thought they did equally well in both conditions, 

which shows they are not aware of their objective performance and might have negative 

implications for driving in the real world. If drivers believe they are performing at a higher level 

than they really are, they may not take necessary precautions and corrective actions, which could 

result in accidents and injury. 

Additionally, participants preferred the HUD to the HDD. This becomes problematic because if 

drivers are in support of using HUDs, they may be implemented without fully investigating the 

driving performance effects associated with the displays. 

Furthermore, performance for detecting unexpected objects along the roadway was poorer when 

using the HUD than when using the HDD, which has implications for using these displays in the 

real world. If drivers do not detect an obstacle, they may not be able to avoid hitting the object, 

which can result in injury and fatalities. However, the caveat to this research is that the routes 

used in the current experiment were fairly simple. 

Future studies should focus on finding ways to mitigate the attentional narrowing effect of the 

HUD. Future studies should also employ routes with various levels of difficulties to determine 

the point at which driving performance associated with HDD becomes significantly worse than 

that with HUD. 
16 

6. References 

BMW. Head-up Display in the BMW X5. http://www.bmw.com/com/en/newvehicles/x5/x5 

/2006/allfacts/ergonomics_hud.html (accessed 12 March 2009). 

CNN. Seven Top Road-Trip Tech Gadgets. http://money.cnn.com/galleries/2008/autos/0805 

/gallery.road_trip_tech/7.html (accessed 12 March 2009). 

Crawford, J.; Neal, A. A Review of the Perceptual and Cognitive Issues Associated With the 

Use of Head-Up Displays in Commercial Aviation. Int. J. Aviat. Psychol. 2006, 16 (1),

1–19. 

Fadden, S.; Ververs, P. M.; Wickens, C. D. Pathway HUDs: Are They Viable? Hum. Factors 

2001, 43 (2), 173–193. 

French, G. A.; Hopper, D. G.; Reising, J. M.; Snow, M. P. Flight Display Integration; AFRLHE-WP-TR-2006-0154; U.S. Air Force Research Laboratory: Wright-Patterson AFB, OH, 

2006. 

Hart, S.; Staveland, L. Development of NASA TLX (Task Load Index): Results of Empirical 

and Theoretical Research. In Human Mental Workload; Hancock, P., Meshkati, N., Eds.; 

Amsterdam: Elsevier, 1988; pp 139–183. 

Hooey, B. L.; Foyle, D. C. Pilot Navigation Errors on the Airport Surface: Identifying 

Contributing Factors and Mitigating Solutions. Int. J. Aviat. Psychol. 2006, 16 (1), 51–76. 

Horrey, W. J.; Wickens, C. D. Focal and Ambient Visual Contributions and Driver Visual 

Scanning in Lane Keeping and Hazard Detection. Proceedings of the Human Factors and 

Ergonomics Society 48th Annual Meeting, New Orleans, LA, 20–24 September 2004a, 

Vol. 48, 2325–2329. 

Horrey, W. J.; Wickens, C. D. Driving and Side Task Performance: The Effects of Display 

Clutter, Separation, and Modality. Hum. Factors 2004b, 46 (4), 611–624. 

Kennedy, R. S.; Lane, N. E.; Berbaum, K. S.; Lilienthal, M. G. Simulator Sickness 

Questionnaire: An Enhanced Method for Quantifying Simulator Sickness. Int. J. Aviat. 

Psychol. 1993, 3, 203–220. 

Kruger, J.; Dunning, D. Unskilled and Unaware of It: How Difficulties in Recognizing One’s 

Own Incompetence Lead to Inflated Self-Assessments. J. Pers. Soc. Psychol. 1999, 77 (6),

1121–1134. 

Martin-Emerson, R.; Wickens, C. D. Superimposition, Symbology, Visual Attention, and the 

Head-Up Display. Hum. Factor 1997, 39 (4), 581–601. 
17 

Microvision. Vehicle Displays: Head-up Displays. http://www.microvision.com/vehicle 

_displays/head_up_displays.html (accessed 12 March 2009). 

Money, J.; Alexander, D. Turner’s Syndrome: Further Demonstration of the Presence of 

Specific Cognitional Deficiencies. J. Med. Genet. 1966, 3, 47–48. 

Montoya, J.; Lamvik, M.; White, J.; Frank, G.; McKissick, I.; Cornell, G. Switchable Vision 

Blocks: The Missing Link for Embedded Training. Proceedings of Interservice/Industry 

Training, Simulation, and Education Conference (I/ITSEC) 2007, Orlando, FL, 

26–29 November 2007. 

Sportvue. http://www.sportvue.com/racing /LT1.php (accessed 12 March 2009). 

Tufano, D. R. Automotive HUDs: The Overlooked Safety Issues. Hum. Factors 1997, 39 (2), 

303–309.

Wickens, C. D. Attentional Tunneling and Task Management. Proceedings of the 13th 

International Symposium on Aviation Psychology, Oklahoma City, OK, 18–21 April 2005.
18 

INTENTIONALLY LEFT BLANK. 
19 

Appendix A. Demographic Questionnaire

 

This appendix appears in its original form, without editorial change. 
20 

Participant # _______ Age ______ Major ________________ Date ___________ Gender ___ 

1. What is the highest level of education you have had? 

Less than 4 yrs of college ____ Completed 4 yrs of college ____ Other ____ 

2. When did you use computers in your education? (Circle all that apply) 

Grade School Jr. High High School 

Technical School College Did Not Use 

3. Where do you currently use a computer? (Circle all that apply) 

Home Work Library Other________ Do Not Use 

4. For each of the following questions, circle the response that best describes you. 

How often do you: 

Drive a car? Daily, Weekly, Monthly, Once every few months, Rarely, Never 

Play computer/video games? Daily, Weekly, Monthly, Once every few months, Rarely, Never 

Use a driving simulator/game? Daily, Weekly, Monthly, Once every few months, Rarely, Never 

Operate a radio controlled vehicle (car, boat, or plane)? 

 Daily, Weekly, Monthly, Once every few months, Rarely, Never 

Play ManiaDrive/TrackMania? 

 Daily, Weekly, Monthly, Once every few months, Rarely, Never 

5. Which type(s) of computer/video games do you most often play if you play at least once every few months? 

6. Which of the following best describes your expertise with computer games and/or driving simulators/games? 

(check √ one) 

_____ Never played any type of driving simulator/game 

_____ Novice 

_____ Good with one type of simulator/game 

_____ Good with several simulators/games 

_____ Expert 

7. Are you in your usual state of health physically? YES NO 

 If NO, please briefly explain: 

8. How many hours of sleep did you get last night? ______ hours 

9. Do you have normal/corrected-to-normal vision? YES NO 
21 

Appendix B. Map Reading Test

 

This appendix appears in its original form, without editorial change. 
22 
23 

Appendix C. NASA-TLX Questionnaire 

 

This appendix appears in its original form, without editorial change. 
24 

NASA-TLX (Part 1) 

Please rate your overall impression of demands imposed on you during the exercise. 

1. Mental Demand: How much mental and perceptual activity was required (e.g., thinking, looking, 

searching, etc.)? Was the task easy or demanding, simple or complex, exacting or forgiving? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 

2. Physical Demand: How much physical activity was required (e.g., pushing, pulling, turning, 

controlling, activating, etc.)? Was the task easy or demanding, slow or brisk, slack or strenuous, restful or 

laborious? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 

3. Temporal Demand: How much time pressure did you feel due to the rate or pace at which the task or 

task elements occurred? Was the pace slow and leisurely or rapid and frantic? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 

4. Level of Effort: How hard did you have to work (mentally and physically) to accomplish your level of 

performance? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 

5. Level of Frustration: How insecure, discouraged, irritated, stressed and annoyed versus secure, 

gratified, content, relaxed and complacent did you feel during the task? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 

6. Performance: How successful do you think you were in accomplishing the goals of the task set by the 

experimenter (or yourself)? How satisfied were you with your performance in accomplishing these goals? 

LOW |---|---|---|---|---|---|---|---|---| HIGH 

 1 2 3 4 5 6 7 8 9 10 
25 

NASA-TLX (Part 2) 

Select the member of each pair that provided the most significant source of workload variation in 

these tasks. 

Physical Demand vs. Mental Demand 

Temporal Demand vs. Mental Demand 

Performance vs. Mental Demand 

Frustration vs. Mental Demand 

Effort vs. Mental Demand 

Temporal Demand vs. Physical Demand 

Performance vs. Physical Demand 

Frustration vs. Physical Demand 

Effort vs. Physical Demand 

Temporal Demand vs. Performance 

Temporal Demand vs. Frustration 

Temporal Demand vs. Effort 

Performance vs. Frustration 

Performance vs. Effort 

Effort vs. Frustration 
26 

INTENTIONALLY LEFT BLANK.
27 

Appendix D. Simulator Sickness Questionnaire 

 

The text in this appendix appears in its original form, without editorial change. 
28 

Developed by Robert S. Kennedy & colleagues under various projects. For additional information 

contact: 

Robert S. Kennedy, RSK Assessments, Inc., 1040 Woodcock Road, Suite 227, Orlando, FL 32803 (407) 

894-5090 

Subject Number: Date: 

PRE-EXPOSURE BACKGROUND INFORMATION 

1. How long has it been since your last exposure in a simulator? days 

How long has it been since your last flight in an aircraft? days 

How long has it been since your last voyage at sea? days 

How long has it been since your last exposure in a virtual environment? days 

2. What other experience have you had recently in a device with unusual motion? 

PRE-EXPOSURE PHYSIOLOGICAL STATUS INFORMATION 

3. Are you in your usual state of fitness? (Circle one) YES NO 

If not, please indicate the reason: 

4. Have you been ill in the past week? (Circle one) YES NO 

If "Yes", please indicate: 

a) The nature of the illness (flu, cold, etc.): 

b) Severity of the illness: Very Mild -----------------------Very Severe 

c) Length of illness: Hours / Days 

d) Major symptoms: 

e) Are you fully recovered? YES NO 

5. How much alcohol have you consumed during the past 24 hours? 

______12 oz. cans/bottles of beer ________ounces wine ________ounces hard liquor 

6. Please indicate all medication you have used in the past 24 hours. If none, check the 

first line: 

a) NONE 

b) Sedatives or tranquilizers 

c) Aspirin, Tylenol, other analgesics 

d) Anti-histamines 

e) Decongestants 

f) Other (specify): 

7. a) How many hours of sleep did you get last night? ______hours 

b) Was this amount sufficient? (Circle one) YES NO 

8. Please list any other comments regarding your present physical state which 

might affect your performance on our test battery. 
29 

Table D-1. Baseline (pre) exposure symptom checklist. 

Instructions: Please fill this out BEFORE you go into the virtual environment. 

Circle how much each symptom below is affecting you right now. # 

Symptom Severity

1. General discomfort None Slight Moderate Severe 

2. Fatigue None Slight Moderate Severe 

3. Boredom None Slight Moderate Severe 

4. Drowsiness None Slight Moderate Severe 

5. Headache None Slight Moderate Severe 

6. Eye strain None Slight Moderate Severe 

7. Difficulty focusing None Slight Moderate Severe 

8a. Salivation increased None Slight Moderate Severe 

8b. Salivation decreased None Slight Moderate Severe 

9. Sweating None Slight Moderate Severe 

10. Nausea None Slight Moderate Severe 

11. Difficulty concentrating None Slight Moderate Severe 

12. Mental depression None Slight Moderate Severe 

13. “Fullness of the head” None Slight Moderate Severe 

14. Blurred vision None Slight Moderate Severe 

15a. Dizziness with eyes open None Slight Moderate Severe 

15b. Dizziness with eyes closed None Slight Moderate Severe 

16. Vertigoa None Slight Moderate Severe 

17. Visual flashbacksb None Slight Moderate Severe 

18. Faintness None Slight Moderate Severe 

19. Aware of breathing None Slight Moderate Severe 

20. Stomach awarenessc None Slight Moderate Severe 

21. Loss of appetite None Slight Moderate Severe 

22. Increased appetite None Slight Moderate Severe 

23. Desire to move bowels None Slight Moderate Severe 

24. Confusion None Slight Moderate Severe 

25. Burping None Slight Moderate Severe 

26. Vomiting None Slight Moderate Severe 

27. Other: 

a

Vertigo is experienced as loss of orientation with respect to vertical upright. b

Visual illusion of movement or false sensations of movement, when not in the simulator, car or aircraft. c

Stomach awareness is usually used to indicate a feeling of discomfort which is just short of nausea. 
30 

Table D-2. Post 00 minutes exposure symptom checklist. 

Instructions: Please fill this out BEFORE you go into the virtual environment. 

Circle how much each symptom below is affecting you right now. #

Symptom Severity

1. General discomfort None Slight Moderate Severe 

2. Fatigue None Slight Moderate Severe 

3. Boredom None Slight Moderate Severe 

4. Drowsiness None Slight Moderate Severe 

5. Headache None Slight Moderate Severe 

6. Eye strain None Slight Moderate Severe 

7. Difficulty focusing None Slight Moderate Severe 

8a. Salivation increased None Slight Moderate Severe 

8b. Salivation decreased None Slight Moderate Severe 

9. Sweating None Slight Moderate Severe 

10. Nausea None Slight Moderate Severe 

11. Difficulty concentrating None Slight Moderate Severe 

12. Mental depression None Slight Moderate Severe 

13. “Fullness of the head” None Slight Moderate Severe 

14. Blurred vision None Slight Moderate Severe 

15a. Dizziness with eyes open None Slight Moderate Severe 

15b. Dizziness with eyes closed None Slight Moderate Severe 

16. Vertigoa None Slight Moderate Severe 

17. Visual flashbacksb None Slight Moderate Severe 

18. Faintness None Slight Moderate Severe 

19. Aware of breathing None Slight Moderate Severe 

20. Stomach awarenessc None Slight Moderate Severe 

21. Loss of appetite None Slight Moderate Severe 

22. Increased appetite None Slight Moderate Severe 

23. Desire to move bowels None Slight Moderate Severe 

24. Confusion None Slight Moderate Severe 

25. Burping None Slight Moderate Severe 

26. Vomiting None Slight Moderate Severe 

27. Other: 

a

Vertigo is experienced as loss of orientation with respect to vertical upright. b

Visual illusion of movement or false sensations of movement, when not in the simulator, car or aircraft. c

Stomach awareness is usually used to indicate a feeling of discomfort which is just short of nausea. 

POST-EXPOSURE INFORMATION 

1. While in the virtual environment, did you get the feeling of motion (i.e., did you 

experience a compelling sensation of self motion as though you were actually moving)? 

(Circle one) YES NO SOMEWHAT 

2. On a scale of 1 (POOR) to 10 (EXCELLENT) rate your performance in the virtual 

environment: 

3. a. Did any unusual events occur during your exposure? (Circle one) YES NO 

b. If YES, please describe 
31 

List of Symbols, Abbreviations, and Acronyms 

HDD Head-down display 

HUD Head-up display 

IED Improvised explosive device 

SA Situation awareness 

SET-MR Scalable Embedded Training - Mission Rehearsal 

SSQ Simulator Sickness Questionnaire 

SVB Switchable vision block 
NO. OF 

COPIES ORGANIZATION 

32 

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NO. OF NO. OF 

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