Color and Visual 

Factors in ATC 

Displays 

Jing Xing

Civil Aerospace Medical Institute

Federal Aviation Administration

Oklahoma City, OK 73125

June 2006

Final Report

DOT/FAA/AM-06/15

Office of Aerospace Medicine

Washington, DC 20591
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of the U.S. Department of Transportation in the interest 

of information exchange. The United States Government 

assumes no liability for the contents thereof.

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Technical Report Documentation Page 

1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. 

DOT/FAA/AM-06/15 

4. Title and Subtitle 5. Report Date 

Color and Visual Factors in ATC Displays June 2006

6. Performing Organization Code 

 

7. Author(s) 8. Performing Organization Report No. 

Xing J 

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 

FAA Civil Aerospace Medical Institute 

P.O. Box 25082 11. Contract or Grant No. 

Oklahoma City, OK 73125 

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Office of Aerospace Medicine 

Federal Aviation Administration 

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Work was accomplished under approved task AM-HRRD522 

16. Abstract 

Computer displays are one of the major sources of information for air traffic controllers to control traffic. 

Because the existing display technologies make it so easy to render color on computer monitors, color is being 

extensively used in air traffic control (ATC) displays. At present, the Federal Aviation Administration has no 

requirement for how color should be used in ATC displays. While the advantages of color may be apparent, 

many display designs suggest that ATC technology developers have not used basic human factors and color 

principles to optimize the advantages of color use in complex scenes such as those in the ATC environment. In 

addition, technology developers create their own unique color schemes. The lack of consistency in color use can 

be confusing. Moreover, little attention has been devoted to the potential negative effects of color use on 

controllers’ task performance. In this study, we investigated color use in ATC facilities to understand the ways 

color is being used, the associated benefits, and its influence on task performance. We found that, while color use 

has some advantages for information processing, such as reducing workload and saving time, it also has 

disadvantages and may introduce negative effects on task performance. We identified the benefits of color use 

and provided rationales for how to use color properly to optimize those benefits. We also analyzed the negative 

effects of color use with respect to associated cognitive factors. Finally, we derived two checklists that evaluate 

advantages and negative effects of color use in ATC displays. These checklists can be used for design prototypes 

and acquisition evaluation. 

 

17. Key Words 18. Distribution Statement 

 

 

Color, Air Traffic Control, Displays, Evaluation, Design, 

Human Factors

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Defense Technical Information Center, Ft. Belvior, VA 

22060; and the National Technical Information 

Service, Springfield, VA 22161 

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price 

Unclassified Unclassified 22 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 

iii

ACKNOWLEDGMENTS

We sincerely thank Keith Gunnell for coordinating facility visits for us. This project could not 

be done without his help. We also express our appreciation for the support from the following ATC 

facilities: ZDC, ZNY, ZNC, PHL tower, DCA tower, SFO tower, New York TRACON, Potomac 

TRACON, and PHL TRACON. We appreciate the FAA reviewers and editors whose efforts greatly 

improved this report.

1

Color and Visual Factors in ATC Displays

INTRODUCTION

During the past decade, the introduction of new 

technologies and automation tools in the air traffic 

control (ATC) environment has involved the increasing 

use of color displays. Many ATC facilities introduced 

new computer-based automation tools and replaced old 

monochromatic computer monitors with new ones. The 

new monitors have the capability of displaying a wide 

range of color. As the result, color is used in many new 

ATC technologies and is being added to existing displays. 

Moreover, some ATC displays allow users to customize 

the colors. Consequently, the same automation tool may 

use different color-coding schemes across facilities or 

even within the same facility. For example, the Enhanced 

Traffic Management System (ETMS) was designed to accommodate users’ color preference, and the Information 

Display System (IDS) allows personnel at each facility to 

determine their own color schemes. 

The presence of color in visual displays can be used 

to attract attention, compare objects, or even convey 

emotion messages (Cole, 2004). Accumulated visual 

studies have shown that color is superior to achromatic 

visual attributes in many tasks such as searching for 

targets and organizing complex visual scenes (Christ, 

1975). A fundamental mechanism for the superiority of 

color is that the human visual system processes color and 

achromatic forms separately through different anatomic 

pathways (Kaiser & Boynton, 1996). Only at the higher 

levels of brain information processing are signals about 

color and forms integrated. Therefore, while achromatic 

visual cues (such as luminance, shape, and text) are used 

to convey detailed information, color can be used as a 

distinctive dimension to organize achromatic information. 

Moreover, because color usually conveys less information 

than achromatic attributes, color-coded information can 

be apprehended faster and more easily. For example, 

many ATC displays use red texts for warning and alert 

messages. Thus, a controller can perceive an alert with a 

quick glance at the color instead of spending additional 

time reading the text.

While the advantages of using color in ATC displays 

seem apparent, its drawbacks are less apparent. For 

example, the sudden onset of a colored shape is useful 

to capture a user’s attention (Yantis & Jonides, 1996). 

However, observers may miss other changes that occur 

simultaneously in the visual field, a phenomenon called 

“inattentional blindness” (Simons, 2000). Consequently, 

a controller may not notice the symbol of an aircraft 

entering into the displayed airspace if, at the same time, 

a color is onset (to signal another event) in the same display. Although situations like this might be infrequent, 

and the resulting performance errors may not occur on 

a daily basis, safety is a priority for ATC; thus, any use 

of color in ATC displays must consider both the benefits 

as well as the potential risks. 

At present, the Federal Aviation Administration (FAA) 

has not established any formal requirement for color use in 

displays or systematic methods to evaluate the benefits vs. 

drawbacks of color use. Many existing guidelines for color 

use provide computer engineers and interface designers 

with some principles (Cardosi & Hannon, 1999; HFSTD-001, 2003). However, most guidelines have some 

shortcomings. The typical shortcomings include: 

1) The guidelines often use visual and human factors 

terms that are unfamiliar to engineers and designers; 

2) the guidelines usually emphasize how to optimize the 

advantages of colors but provide little information 

about their drawbacks; and 

3) the guidelines are largely concerned with the perception of color instead of the effects of color on task 

performance. 

These shortcomings have limited the application of 

the guidelines in display design and evaluation.

To understand the current status of color use in ATC 

displays, we conducted site visits to nine ATC facilities: 

three Air Traffic Control Towers, three Terminal Radar 

Approach Control facilities, and three En Route Traffic Control Centers. At each of these ATC facilities, 

we performed the following activities: 1) Learned how 

controllers used computer displays in the facility through 

briefings given by facility managers, supervisors, and 

technical staff; 2) observed how controllers used color 

information to perform tasks; 3) identified color usages 

and their relevance to ATC tasks; and 4) determined the 

purposes of color use and potential problems associated 

with color. In addition, we discussed with the facility 

representatives issues associated with the advantages and 

drawbacks of using colors in displays. The discussions 

significantly contributed to our task of identifying color 

and visual factors that might negatively affect ATC task 

performance. 

To ensure that the use of color in ATC displays enhances 

task performance and does not introduce any undesirable 
2

safety risk, it is necessary to have a systematic method 

to assess the benefits and potential negative effects of 

color use. Through the facility visits, we identified color 

and visual factors that were pertinent to controllers’ task 

performance. In this report, we classified those factors 

into two major categories: 

1) factors that make the use of color effective for given 

task purposes; and 

2) factors that might negatively affect task performance. 

For each factor, we present examples identified in ATC 

displays and the rationale in the scope of cognitive and 

visual research. 

Finally, we developed two checklists that would allow a 

quick evaluation of color use in ATC displays. We studied 

the literature to provide rationales for the development 

of the color-use checklists. Thus, the checklists are based 

on basic research findings and adapted for engineering 

applications.

We need to point out several limitations of this report. 

First, due to the limited time at each facility, we were unable to systematically collect data about the color use from 

all the ATC displays. Therefore, this report is limited to 

qualitative descriptions of the facts learned through our 

facility visits. Second, while we cited many experimental studies in the literature to provide rationales for the 

checklists, we did not intend to perform a comprehensive 

literature review of color information processing. Third, 

we did all the analysis of color use for personnel with 

normal color vision; the issue of color vision deficiencies 

was beyond the scope of this report. 

RESULTS

Color and visual factors that contribute to the effectiveness of color use

Task purpose of color use in ATC displays

Previously, Xing and Schroeder (2005) reported that 

color in ATC displays was primarily used for one of 

three task purposes: 1) To draw attention. Colors are 

often used to encode information that needs to be attended to instantly, such as an alert or emergency. 2) To 

identify certain types of information so that searching 

for the information in complex scenes can be done more 

efficiently. In this application, each color is associated 

with a distinctive meaning. For example, a controller 

may use yellow to outline a restricted airspace on the 

display; the distance of an aircraft to that airspace can 

be subsequently displayed in yellow text. 3) To organize 

information by segmenting a complex scene into visual 

objects so that controllers can easily appreciate what and 

where objects are. For example, the functional menus 

of a display may appear as dark green; thus, they are 

visually segmented from other materials on the display. 

In this kind of application, color is not associated with 

any specific meaning. Accordingly, Xing and Schroeder 

classified task purposes of color use in ATC displays into 

three categories: attention, identification, and segmentation. In this section, we present the benefits of color use 

and the factors that enable color to achieve the benefits 

for each category.

Attention

Controllers need to instantly detect critical information in ATC displays without serially searching complex 

scenes, so the target that represents critical information 

should immediately become obvious to capture attention. 

This phenomenon is called “pop-out” in vision research 

(Treisman & Gelade, 1980). Pop-out is especially useful when targets need to be detected in large displays, 

because targets located in the peripheral visual field can 

be quickly brought to the fovea for detailed inspection. 

For example, a typical radar display such as the Display 

System Replacement (used by controllers in En Route 

Traffic Control Centers) includes a central area for current flight situations and one or several menu bars along 

the sides of the display. Controllers spend a great deal of 

time scanning the flight situation area. However, an alert 

message that appears in the left-top corner of the display 

may require immediate detection. Because a controller 

does not often look at the corners, that message may go 

unnoticed, unless the message pops out and captures the 

controller’s attention.

The pop-out effect depends on the difference between 

the target and other displayed materials (called distractors) 

within the surrounding visual field that typically spans 

a view angle of 20~40 degrees. Because achromatic attributes are used in the form of text, shape, graphics, and 

shades to represent detailed information, color appears 

as a distinctive dimension to create conspicuous differences between a target and distractors. Thus, pop-out of 

color-coded information in complex scenes is extremely 

efficient and desirable (Treisman & Gelade, 1980). Several 

studies compared the effectiveness of various visual cues 

in pop-out and concluded that color was next to flicker 

and brightness but superior to shape and size in drawing attention (Christ, 1975). While flicker is the most 

effective visual cue to capture attention, its use should be 

limited because it produces tunnel vision, during which 

the observer focuses on one target and ignores other 

objects in the visual field. A great deal of visual research 

has been devoted to studying the conditions under which 

pop-out could be reliably induced. We summarized the 

important results as follows:

1) Color can effectively draw attention when a colored 

target is brighter than distractors, and the size of 

the target is equivalent to, or larger than, most 
3

distractors (Nagy & Sanchez, 1992; Treisman & 

Souther, 1985). 

2) A color can be specified by two factors: luminance and 

chromaticity. Either luminance difference between the 

target and distractors or chromaticity difference can 

induce pop-out. The threshold luminance difference 

is about 20cd /cm2 for small stimuli (0.5~1.5 degree 

view angle) in large displays (Nagy & Sanchez, 1992). 

The threshold color difference is about 60 times that of 

the color discrimination threshold, at which two filled 

areas placed side-by-side can be discriminated. The 

discrimination threshold varies with the wavelength of 

colors and illuminant conditions (Wyszecki & Fielder, 

1971). Nevertheless, industrial applications typically 

take the threshold as 0.004 in CIE color difference 

coordinates (see Appendix A for CIE chromaticity). 

By this standard, we estimated that the threshold color 

difference for attention is 60 *0.004=0.24.

3) Color is effective in inducing pop-out when other 

materials of comparable or larger sizes in the view field 

are composed of no more than two or three colors. 

With increasing variation of distractors, target salience 

decreases and the pop-out effect diminishes (Treisman 

& Gelade, 1980).

Identification

While our sensory system can perceive a large volume 

of information in an analog manner, our cognitive system 

can only process a few pieces of information at a time. 

Therefore, an effective way to reduce cognitive workload 

is to organize information in complex visual scenes into 

categories and denote the categories with visual attributes 

that can be easily identified. Such tasks are called identification. One example is the representation of precipitation in 

ATC displays. Although precipitation varies continuously, 

it is categorized into six levels in the ATC environment: 

Levels 1-2 for light weather, Levels 3-4 for moderate heavy 

weather, and Levels 5-6 for severe weather. Controllers 

make decisions by identifying the weather levels instead 

of the precise value of the precipitation. 

Color is often used denotatively to identify an object. 

The task of using color for identification is essentially 

the task of color naming in which observers can associate targets with specific color names. In the example of 

weather precipitation, the six levels are displayed with 

different colors. Seeing some areas filled with red, a 

controller can immediately recognize the presence of 

severe weather. 

In the ATC environment, identification of two 

stimuli is usually performed at separate spatial locations 

and times. Typically, a controller remembers the color 

by its name and searches for the target identified by 

the color. Thus, such color-based identification tasks 

involve the use of memory. Several studies demonstrated 

that color is much more effective than in identification tasks where memory is required. Moreover, color 

becomes increasingly more effective as recall of memorized items is delayed (Sachtler & Zaidi, 1992; Young 

& Nagy, 2003). For example, when used to identify 

information such as aircraft shapes, geometric shapes, 

and alphanumeric signs, color was significantly better 

in terms of accuracy than size, brightness, shape, and 

text (Christ, 1975). Also, the superiority of color to 

achromatic cues is more evident as the visual scenes 

became more complex or the difficulty of identification tasks increased. 

Next, we summarized the results in the literature about 

how to effectively use color for identification.

1) Basic colors are more effective than others for identification tasks because they are maximally segregated in the 

color space and can be named reliably and consistently 

across subjects. The basic colors include red, green, 

yellow, blue, purple, brown, orange, pink, and three 

achromatic colors, black, white, and gray. (Boynton 

& Olson, 1990; Smallman & Boynton, 1990).

2) For non-basic colors, the minimal color difference is 

about 9-10 times the color discrimination threshold to 

effectively identify information (Boynton, MacLaury, 

& Uchikawa, 1989). 

3) The maximum number of colors that can effectively 

identify information is 6 or 7. Beyond that limit, 

color has no advantage over achromatic cues (Carter, 

1982).

Segmentation

The human visual system organizes complex scenes 

into meaningful objects. To appreciate what and where 

particular objects are present, the visual input is organized 

by a filtering procedure that has been termed segmentation

(Pinker, 1984). Segmentation is crucial when using an 

automation system with a cluttered display and varying 

task demands. For example, a controller can spatially 

segment the aircraft situations area from the menu areas 

in a radar display. Thus, when controllers need to find a 

command in the menu bars, they can direct their attention 

to the menu area instead of searching the entire display. 

Since ATC displays are usually very complex, segmentation is necessary to reduce controller workload.

Segmentation is based on uniformity and consistency 

of elements. An area composed of uniform elements 

can be easily segmented from its surroundings. Since 

the human visual system processes color separately from 

achromatic visual features, color is one of the ways to segment a display into separate regions. In complex scenes 

like those of ATC displays, color is more effective and is 

processed faster than achromatic cues for segmentation 
4

because achromatic cues are usually used with explicit 

meaning (Nothdurft, 1993). 

Segmentation tasks include regional segmentation 

and pattern segmentation. Regional segmentation involves segmenting a spatially continuous region from 

its surrounding materials. For instance, a terminal radar 

display called Standard Terminal Replacement System 

(STARS) uses a circle or polygon filled with beige to segment a restricted airspace from non-restricted airspace. 

Specifically, Yamagishi and Melara (2001) demonstrated 

that chromaticity information is more effective than luminance in regional segmentation. On the other hand, 

pattern segmentation involves integrating some spatially 

discontinuous patterns into one class and segmenting 

them from other patterns. For example, another terminal 

radar display, called Automated Radar Terminal System 

(ARTS) Color Display (ACD), represents datablocks of 

aircraft owned by a controller in white and those of unowned aircraft in green. By doing so, the owned aircraft 

and unowned datablocks are visually segregated. These 

two types of segmentation tasks have different requirements for color use. 

Below are some tips from extensive visual studies of 

segmentation:

1) A region consisting of two or more colors is likely to be 

confused with other regions made up of many colors 

(Julesz, 1965); thus, it may not be reliably segmented 

from others.

2) Both chromaticity and luminance differences between 

regions or patterns can result in segmentation; however, 

chromaticity is more effective than luminance. For 

regional segmentation, the threshold color difference 

is equivalent to the discrimination threshold, at which 

two filled areas placed side-by-side can be reliably discriminated. For pattern segmentation, the threshold 

color difference is about 3~5 times the discrimination 

threshold. The luminance factor in segmentation is 

determined by the ratio of the luminance difference to 

the baseline luminance of the object to be segmented. 

The threshold ratio is about 5% segmentation of 

uniform areas placed side-by-side and 15~20% for 

patterns. (McIlhagga, Hine, Cole, & Snyder, 1990). 

A checklist of color-use effectiveness

Based on the observed task purposes of color use in 

ATC displays and the rationale described in the preceding section, we developed a checklist of the color and 

visual factors that are essential to ensure the effectiveness 

of color, as shown in Table 1. The checklist is organized 

with respect to task purposes. The elements in the table, 

from left to right, are task purposes, factors contributing 

to the effectiveness of color use, conditions with which 

color use is effective for the purpose, and checkboxes 

that would be filled with “Yes” if a condition is met or 

“No” otherwise. To use this checklist, one first needs to 

determine the task purpose of a color. For each purpose, 

several factors contribute to the effectiveness of color use. 

When all the conditions for a given purpose are met, the 

use of color is effective for the purpose. 

An example of the application of the checklist

We use the color scheme of ACD datablocks as an 

example to describe how to use the checklist. ACD is 

a display for operational controllers at Terminal Radar 

Approach Control (TRACON) facilities to acquire the 

current traffic situation and control aircraft. The display 

contains a traffic situation area occupying the central part 

of the computer screen and a menu bar on the top of 

the screen. The traffic situation area graphically displays 

aircraft symbols and datablocks, superimposed with 

maps, sector boundaries, weather, and range rings. While 

controllers can adjust the background color of the screen 

at their own preference from complete dark to 60% blue, 

most controllers set their screen background very dark. 

A datablock is composed of several short lines of text. 

Four text colors are used. White is used for datablocks 

of those aircraft owned by a controller; green is used for 

datablocks of aircraft that are not owned by the controller. Yellow is used for “point-out” datablocks. A “pointout” datablock means that a controller can point out a 

datablock that might be interesting to another controller 

by making the datablock yellow on the other controller's 

display. When an aircraft is in a potential conflict, the red 

alert text “CA” (Collision Alert) or “LA” (Low Altitude 

Alert) appears on the top of its datablock. The alert text 

blinks until the controller acknowledges it. The red text 

remains until the conflict is solved. 

The red text “CA” or “LA” on the top of a datablock 

is intended to capture the controller’s immediate attention. Thus, we identified the purpose of the blinking 

red as attention. Here the colored target to be attended 

to is the red text, and the main distractors are green and 

white datablocks. Yellow datablocks are present only occasionally and momentarily, so they are not considered 

as major distractors. According to Table 1, three conditions have to be met for red to be effective in attention: 

1) Luminance  the luminance of the red text is lower 

than the luminance of green and white datablocks, so the 

condition is not met; 2) luminance and chromaticity difference  the chromaticity differences between red and 

white is 0.29, and the difference between red and green 

is 0.36 (both are greater than 0.24), so the condition is 

met; and 3) number of distractor colors  There are two 

main distractor colors, white and green, so the condition 

is met. Each of the three conditions must be met for the 

color to be effective. These results are listed in Table 2. 
5

Table 1: A checklist of the effectiveness of color use in ATC displays. 

Task purpose Color and 

visual factors 

 Conditions for color-use being effective Yes 

/ No

Luminance The luminance of the color-coded target is greater 

than or equal to that of distractors (i.e., other 

materials displayed in the visual field). 

Luminance 

and

chromaticity 

The luminance difference between the colorcoded target and distractors is greater than 

20cd/cm2 regardless of the chromaticity 

difference. Alternatively, the chromaticity 

difference between the color-coded target and 

distractors should be greater than 0.24 in CIE 

chromaticity coordinates. 

Attention

Number of 

distractor 

colors

The number of distractor colors should be less 

than 3~4 (The number of colors of the distractors 

with a size greater than or equivalent to that of 

the target should be minimized). 

Color naming The colors used for identification can be named 

uniquely and consistently.

Chromaticity The chromaticity differences between the colors 

are greater than 0.036. 

Luminance The luminance differences between colors are 

less than 20cd/cm2.

Identification 

Number of set 

colors

The number of colors is less than 7. 

Luminance or 

Chromaticity 

For regional object segmentation, the 

chromaticity difference between the object and its 

surrounds is greater than 0.004. Alternatively, the 

luminance ratio, defined as the absolute 

luminance difference between the object and 

surrounds divided by the luminance of the object, 

is greater than ~5%.

For pattern segmentation, the color difference 

between the pattern and its surrounds is greater 

than 0.02. Alternatively, the luminance ratio is 

greater than 15~20%.

Segmentation 

Number of 

object colors 

The number of colors of the object to be 

segmented is less than 2 unless the object is 

composed of a regularly patterned texture of 

different colors.
6

The elements in Table 2, from left to right, are purpose 

of color use, conditions, and evaluation (Yes /No). Table 

2 shows that one of the conditions for the purpose “Red 

for attention” is not met; we conclude that the red alert 

text is not effective for attention. In real operations, 

controllers typically rely on the blinking signal rather 

than the color to detect such alerts. 

White, green, and yellow are to distinguish datablocks 

associated with owned, unowned, and pointed-out 

aircraft. The purpose of these colors is identification. In 

addition, the red alert text is also used to identify datablocks of aircraft in conflict after the blinking signal is 

stopped. According to Table 1, three conditions should 

be met for the colors to be effective in identification: 1) 

Color naming - the four colors are basic colors and can be 

named reliably, so the condition is met; 2) Chromaticity 

- the chromaticity difference of any pair of the four colors 

is greater than 0.036, so the condition is met; and 3) 

Number of colors - the number of colors for identification 

is four (less than seven), so the condition is met. These 

results are listed in Table 2. Overall, this set of colors is 

effective for identification since all the conditions are 

evaluated as “Yes.” 

Color and visual factors that negatively affect task 

performance

The previous section described the benefits of color 

use and how to achieve them. Unfortunately, the benefits 

of color use are often accompanied by some negative effects. We observed a number of situations where color use 

could be troublesome for task performance. Moreover, 

controllers and supervisors acknowledged that in some 

circumstances color use might have the potential of leading to operational errors. We identified and classified the 

cognitive and visual factors in those situations. In this 

section, we first describe some typical color factors that 

may negatively affect ATC task performance and provides 

a rationale for those factors based on the results of many 

visual studies in the literature. Next, we present a checklist 

of potential drawbacks of color use based on the factors 

and the rationale. Finally, we present an example of how 

to apply the checklist to ATC displays.

Negative factors 

Distraction and inattentional blindness

Attention implies withdrawal from some information 

to effectively deal with other information. Since the human ability to attend to stimuli is limited, attending to a 

salient target in a complex scene acts as a distraction for 

other materials in the scene. Therefore, the perception of 

other stimuli is reduced. Hence, what facilitiates attention 

is also the source of distraction. In extreme circumstances, 

the pop-out of certain targets can induce a phenomenon 

known as “inattentional blindness,” which means when 

observers focus their attention on a salient object, they 

often fail to notice other salient objects or events. An 

example in the ATC environment is the situation where 

a controller may fail to notice a blinking datablock that 

is being handed-off between sectors if a conflict alert 

occurs at the same time. The causes for inattentional 

blindness have been studied by many researchers. It was 

demonstrated that the sudden onset of color was capable 

of inducing inattentional blindness in visual displays 

(Schmidt, Vogel, Woodman, & Luck, 2002). 

For ATC tasks, operational controllers need to be 

continuously aware of on-going information in the radar 

display. Stein (1992) reported that the best eye movement 

pattern for controllers was to scan the radar display continuously. However, the onset of color targets can interrupt 

the smooth scan and reduce controllers’ awareness of the 

overall air traffic situation. DiVita, Obermayer, Nugent, 

and Linville (2004) reported that inattentional blindness 

negatively affected operators’ task performance in detecting critical events on a combat information display and 

Table 2: Evaluation of the effectiveness of color use in ACD datablocks 

Purpose of color use Conditions Evaluation 

Luminance No 

Luminance and 

chromaticity difference 

Yes

Red for attention 

Number of distractor colors Yes 

Color naming Yes 

Chromaticity difference Yes 

White, green, 

yellow, and red for 

identification 

Number of colors Yes 
7

had the potential to cause performance errors. Therefore, 

the application of color for attention should be limited 

and done with caution. If other important changes may 

occur simultaneously with color onsets for attention, 

then additional redundant cues should be provided to 

controllers to ensure their situational awareness. 

Uncertainty in identification

Christ (1975) reviewed color use in visual displays 

and concluded that the advantage of color could be 

significant only when color was highly correlated with 

the information it denoted; if color was only partially 

correlated with the content of information, then a user 

could not use color as the unique selection criterion 

for decision-making, and color had no advantage over 

achromatic attributes. For example, Jeffrey and Beck 

(1972) used color to encode types of aircraft in a simulated flightdeck display, and they had subjects identify 

potential conflicts between aircraft. However, they did 

not find any improvement in task performance. One 

reason was that each color represented multiple aircraft 

types with some common features, while subjects needed 

information about other features to perform the task. 

Moreover, such color-coding could cause performance 

errors because of the uncertainty it introduced. By the 

theory of signal detection, increasing uncertainty of the 

selection criterion leads to a higher probability of decision 

errors. In addition, it took users more time to identify 

targets with irrelevant color-coding.

Color-coding uncertainty occurs in some ATC displays. 

While manufacturers assume some selection criteria for 

controllers to perform tasks, controllers may use other 

criteria or break down the criteria in real operations. For 

example, some displays encode aircraft delay time by color, 

such as green for delays less than five minutes and yellow 

for longer delays ranging from 10 to 15 minutes. However, 

controllers need the precise time when dealing with aircraft 

delay. Here colors are only partially correlated with the 

delay time, and they cannot be used as the appropriate 

selection criterion for the task. In such cases, controllers 

tend to ignore colors. When asked about the meanings 

of colors, many controllers were not aware of the answers 

because “colors are of no use anyway.” Nevertheless, even 

though controllers may ignore color-coding, colors still 

distract them during task performance. 

Loss of integration

Color-coding has dual-effects on the information 

processing in the brain: integrating pieces of information 

with the same color and segregating information with 

different colors. Segregation and integration are like the 

opposite ends along an axis: A higher level of segregation 

is always accompanied with a lower level of integration, 

and vice versa. In particular, because color and achromatic 

signals are processed separately in the visual system, the 

brain has to make an extra effort to integrate information 

represented by color and achromatic attributes. Therefore, 

when using colors to categorize information, the brain 

tends to process different colors separately and is less 

likely to associate the pieces of information displayed in 

different colors. This can pose a risk to tasks in which 

different types of information have to be considered 

together simultaneously.

Next, we use an example to describe the potential 

risk of loss of integration due to color use in ATC displays. ACD displays use white to represent datablocks 

of aircraft owned by a controller and green for those 

not owned by the controller. This scheme could cause 

integration problems. In this particular example, the task 

of maintaining aircraft separation requires that information about owned and unowned aircraft be considered 

together to avoid confliction between them, especially 

for those aircraft near sector boundaries. However, the 

application of color weakens information integration of 

the two types of aircraft ownership. Thus, controllers may 

have a lowered probability of detecting potential conflicts 

between owned and unowned aircraft. 

Color-coding interference

From the cognitive point of view, when people use color 

displays they build a mental model of the display in which 

colors are associated with certain categories of information. 

When several sets of color-coding are used in a display, 

users’ cognitive workload is significantly increased due to 

switches between the coding schemes. Moreover, multiple 

color schemes often lead to the following situations: (a) 

one color has multiple meanings in a display; and (b) 

several colors are assigned the same meaning. 

If the relationship between a color and the assigned 

information is not unique, then the mental model of 

color use could not be reliably established. Furthermore, 

different sets of color-coding may interfere with each 

other. Colors in one coding set become irrelevant to 

other sets and potentially harmful, as they can lead to an 

incorrect distraction for the task at hand. For instance, 

they can become detrimental to a search task if a lot of 

non-targets are in the target color (Poulton & Edwards, 

1977). Therefore, errors may occur in the process of 

inferring the meanings of color. Many studies have 

demonstrated this contention. In particular, Yuditsky et 

al. (2002) tested color-coding of (a) aircraft destination 

airport, (b) overflights, and (c) special-use air space in an 

air traffic control display. The results showed that while 

each individual color-coding might improve controller 

performance and efficiency, there was no benefit when 

all three sets of color-codes were used.
8

Multiple color-coding is a common phenomenon 

in ATC displays. Perhaps due to the complex nature of 

ATC tasks, nearly all color displays use more than one set 

of color schemes. For example, red is used at least three 

times with different meanings in the Traffic Management 

Advisor to indicate: 1) aircraft delay time longer than 15 

minutes; 2) rush time of an airport; and 3) the capacity boundary in the aircraft load graph. The problem is 

complicated by the fact that individual controllers usually 

work with multiple displays. 

Figure 1 illustrates the confusing color-coding used 

in ATC displays. The information represents the analysis 

of color use in four displays in terminal facilities. Those 

include Standard Terminal Automation Replacement 

System (STARS), ACD, Traffic Management Advisor (TMA), and Integrated Terminal Weather System 

(ITWS). The upper, middle, and bottom panels correspond to attention, identification, and segmentation, 

respectively. The vertical axis represents the number of 

times that a color is used for a given purpose in the four 

displays. The horizontal axis represents colors. The top 

panel indicates that many colors are used for attention. 

Therefore, controllers cannot just rely on a single color 

to distinguish critical messages from non-critical ones. 

Furthermore, most basic colors are used for all three 

purposes. Notice that in the bottom panel four colors 

(red, green, yellow, and blue) are predominately used for 

segmentation, which introduces interference with the 

colors used for attention and the ones for identification. 

For example, red could mean a windshear warning, yet 

it could also mean nothing special. In such situations, 

controllers have to rely on additional visual features to 

identify critical information. 

At present, we are not aware of any study that explored 

the maximum number of color schemes a user can process 

in a display. Fortunately, we informally collected some 

preliminary data from five controllers through the discussions conducted during our facility visits. We found 

that four of five controllers preferred no more than 2 or 

3 color schemes in a display, and one controller did not 

express any preference. While it might be difficult for 

display designers to keep the rule of “one color for one 

meaning,” a less-restricted compromise is that one color 

should be used for one type of task purpose: attention, 

identification, or segmentation. In particular, colors used 

for attention should not be used for segmentation. 

Text readability

ATC tasks involve a great deal of text reading because text 

comprises a relatively large part of the materials presented 

on displays. Therefore, ATC operations require that text 

should be read effortlessly and in an error-free manner. A 

great deal of research studied text readability, which is the 

property that permits an observer to read text easily on a 

screen irrespective of meaning (Legge, Rubin, & Luebker, 

1987). Readability is primarily determined by the luminance 

contrast between text and its background colors. Luminance 

contrast can be calculated as the luminance difference 

Figure 1: Number of times that each color is used in four terminal 

displays for a given type of task purposes. The top, middle, and 

bottom panels are for the purposes of attention, identification, and 

segmentation, respectively.
9

between the text and background divided by the sum of 

the luminance. Therefore, zero contrast means that the 

text and background have the same luminance, and 100% 

contrast means the maximum luminance contrast (the one 

produced by the combination of white and black). Several 

experimental studies demonstrated that readability decreases 

linearly with luminance contrast. Below 20~30% contrast, 

readability deteriorates significantly and decreases with 

contrast much more rapidly (Legge et al., 1987; Scharff & 

Ahumada, 2002). Thus, in industrial applications, a 20% 

to 30% luminance contrast is often taken as the threshold 

contrast for text reading. Furthermore, Krebs, Xing, and 

Ahumada (2002) found that the minimum text size for error-free reading varied with contrast when the contrast was 

less than 20%; the minimum size was a constant for a given 

monitor within the contrast range of 20-100%. 

Coloring text can degrade text reading. Color use can 

result in low text readability. When people choose colors 

for text, they are typically concerned with the chromaticity, 

not the luminance of a color. For instance, we observed 

some situations where the background of a text box was 

highlighted with color to indicate a different status of the 

text; however, the luminance of the highlighting colors 

was very close to that of the text, so users experienced 

difficulty in reading the text. 

Below are some sample combinations of text and 

background colors in ATC displays that result in low 

text readability:

Red vs. black

Yellow vs. white

Yellow vs. green

Green vs. cyan

Blue vs. brown

Gray vs. green

Gray vs. cyan

Orange vs. green

Text readability can be assessed by determining the 

luminance of text and background colors. Appendix B 

in this report describes how to calculate luminance from 

the rgb values of a color, where r, g, and b are the digital 

values for the phosphor channels (red, green, and blue) 

of a computer display to generate a color. If the monitor 

parameters of color calibration are not available, luminance 

can be estimated with the following equation: Lum= 

(Lr *r/255)gamma + (Lg *g/255)gamma + (Lb *b/255)gamma,

where Lr, Lg, and Lb are the maximum luminance for the 

red, green, and blue channels, i.e., the luminance measured 

at rgb values: (255, 0, 0), (0 255, 0), and (0, 0, 255). 

The typical default values are Lr= 21.3389, Lg=70.6743, 

and Lb=7.98680. The parameter gamma describes the 

nonlinearity of luminance response for a given monitor. 

It typically varies from1.8 to 2.5 for most monitors with 

a default value of 2.2 (Berns, 2000). We calculated the 

contrasts for the text-background combinations of 14 

colors that are frequently used in ATC displays. Appendix B describes the calculation method, rgb values of the 

colors, and the calculated luminance contrasts. 

Experience interference

Imagine that you see a set of words of color names 

printed in different colors. For example, the word “red” 

is printed in green ink, and the word “green” is printed 

in yellow ink. When you look at one of the words, you 

see both its color and its meaning (from experience). If 

those two pieces of information conflict, you have to 

make a choice. 

The meaning attached to a word or color is learned 

through experience. Since access to word meaning becomes automatic and effortless (Stroop, 1935), when 

meanings of the word and color come into conflict, 

interference occurs even when one tries to pay attention 

to colors. This effect can result in misinterpretation of 

color-coded information. Thus, such interference should 

be avoided in visual displays. 

There are some general conventions about color use 

in ATC displays, and controllers have acquired those 

conventions through experience. If a color use conflicts 

with the conventions, what is in the experience and 

the perceived information may interfere with each 

other, and the perceived information can be biased by 

experience. For example, red is usually the top choice 

to convey warning and alert messages. Controllers 

would naturally infer that a red code conveys urgent 

information, and the attention to red reduces awareness of other information. Problems arise when the 

color is used to encode an aircraft’s destination even 

though the destination of that aircraft is no more 

important than that of any other aircraft. When two 

meanings are associated with the same color code (e.g. 

urgency, destination), the brain has to exert extra effort to suppress one meaning to correctly interpret the 

meaning of that code. During our discussions at the 

ATC facilities, some controllers complained that such 

color-coding did not help their tasks at all but added 

distraction. Generally speaking, when designing a new 

ATC display, color schemes should follow the conventions so that color use is compatible across all displays 

in the ATC environment. As Cardosi (2003) pointed 

out, compatibility is crucial between new and existing 

ATC tools for controllers to adapt to a new tool. For 

more information about color use conventions, a good 

reference is the color use guidelines of ATC displays 

developed by Cardosi and Hannon (1999). 
10

The following instance demonstrates the importance 

of compatibility between color schemes and experience. 

We observed an interesting way that controllers used 

Remote-ACDs in air traffic control towers. RemoteACD offers two versions: The nighttime version uses 

the same color schemes as those used in ACDs (with a 

dark background); the daytime version has a bright blue 

background, and some colors are different from those in 

the nighttime version. Theoretically, the daytime version 

suits the eyes better for daytime illumination. However, 

we observed that controllers chose to use the nighttime 

version even during the daytime because “the colors in 

the nighttime version look natural” (quoted from several 

controllers). “Look natural” implies that the color scheme 

is more consistent with controllers’ experience. 

Below is a list of some color use conventions that we 

observed in current ATC displays:

• Red for warning and alert;

• Yellow and orange-red for messages that need some 

attention but not as urgent as those in red;

• Green and white for normal status;

• Dark blue or black for background. 

Color-naming inconsistence

Human eyes can identify at least a million possible 

color samples, no two of which would match if placed 

side by side and viewed in a normal viewing condition. 

However, certainly there are not as many color names. 

Human categorizes colors using a limited number of 

names. The criteria for color categorization vary among 

people between and within cultures. The majority of 

distinguishable colors could be named differently across 

people, except for the 11 basic colors (red, green, blue, 

yellow, purple, orange, pink, brown, black, white, gray) 

that can be named easily and consistently (Boynton & 

Olson, 1990). Therefore, the manipulation of the consistency of color-naming may change performance in tasks 

where categorization and identification by color name are 

important. Indeed, Guest and Van Larr (2002) found 

that highly “nameable” color led to better performance 

in identification tasks than metrically equivalent but 

less categorically distinct color sets when they measured 

response times, confidence ratings, and response accuracy. Another concern is that color-naming inconsistency 

may negatively affect the communication of color-coded 

information in controller teamwork. 

Throughout our facility visits, we identified many situations where a color was named differently by controllers. 

For instance, the graphical tool in DSR provides four colors 

for controllers to use. We asked controllers and supervisors 

to name these colors at all the three En Route facilities 

we visited. The colors were named inconsistently among 

the staff within and between facilities. For example, one 

of the colors was named red, pink, white-red, or reddish 

pink. Another color was named green, yellow, or yellowish 

green. However, the good news is that for all such cases 

we identified, controllers acknowledged that inconsistent 

color-naming was not a problem for them. While they 

used colors to perform tasks, they exchanged information by the operational meanings of colors, not color 

names per se. Nevertheless, inconsistent color-naming 

has the potential to cause communication errors. That 

is not desired for ATC tasks, especially those involving 

attention capture and identification. 

View-angle intolerance

In recent years, the FAA has begun to replace the older 

CRT monitors with new LCD monitors. Unfortunately, a 

common problem with LCD monitors is their view angle 

intolerance. That is, due to the nature of liquid crystal 

molecules, polarized light entering a liquid crystal material 

off axis is treated differently than light entering along the 

optical axis. The electrooptic transfer function of LCDs 

tends to be angular-dependent. In addition, liquid crystal 

molecules operate differently on different wavelengths of 

light when responding to off-axis light, so different view 

angles cause significant variations in displayed colors, and 

colors are usually washed off toward white if viewed from 

large off-axis angles. Therefore, when viewed from off-axis 

angles, text and graphs displayed on LCDs have a loss 

of luminance contrast and undesirable variations in hue. 

This can be seen from the example in Figure 2. 

 0 15 35 55 75 0

50

100

150

200

250

300

350

400

View angle (degree)

Maximum contrast ratio (Lmax-Lmin)/Lmin

Figure 2: View angle intolerance of a General 

Digital monitor. The horizontal axis is view 

angle, and the vertical axis is the maximum 

contrast ratio, calculated as (Lmax-Lmin)/Lmin, 

where Lmax and Lmin are the maximum and 

minimum luminance for a color measured from 

a given view angle. 
11

Figure 2 illustrates the view-angle dependence of 

displayed colors for a General Digital monitor that is 

currently used in many ATC facilities. The horizontal 

axis represents the view angle, and the vertical axis 

represents the luminance contrast of colors. The result 

indicates that the contrast decreased rapidly as the view 

angle increased beyond 35 degrees, implying that target 

detection, discrimination, and text reading at large view 

angles could be very difficult.

View-angle intolerance can be a potential problem for 

controllers using color displays. The following two situations are typical in ATC facilities: 1) One controller uses 

several computer monitors, and some monitors have to be 

viewed from off-axis angles. In particular, tower controllers spend a significant time looking out of the window 

and need to walk around frequently, so it is inevitable 

for them to view displays from off-axis angles. 2) Two 

or more controllers share the same monitor. ATC tasks 

often require teamwork. In particular, in Centers two 

controllers (referred as R-side and D-side) usually work 

together. While the R-side controller sits in front of the 

radar display, the D-side controller, whose typical view 

angle to the display is about 45-60 degrees, also needs to 

acquire information from the radar display. We noticed in 

the facilities that controllers tried to solve the view-angle 

problem by turning the monitor back and forth between 

them. When asked why they were turning the monitor 

around, controllers stated that they might miss crucial 

information due to off-axis view angles. 

A checklist of color-use drawbacks

We developed a checklist to summarize the drawback 

factors described in this section, as shown in Table 3. The 

first column of the table lists the pertinent perceptual and 

cognitive issues involved in color use. The second column 

lists the color and visual factors associated with the issues. The third column lists some possible consequences 

associated with the factors. The last column consists of 

checkboxes that can be filled with “yes” if a factor described 

in the second column is involved in the use of color and 

“no” otherwise. This checklist and the checklist of color 

effectiveness in Table 1 provide a method for a quick 

evaluation of color use in ATC displays.

An application example of the checklist

Once again, we use the color scheme of ACD datablocks 

as an example to describe how to apply the checklist. 

Among the drawback factors listed in Table 3, the first 

six evaluate individual color. For each color used in 

ACD datablocks, we evaluated the first six factors and 

classified the result as “Yes” or “No.” “Yes” means that 

the drawback factor exists, so the color usage has the 

potential of negatively affecting task performance; “No” 

means that the factor does not exist for the given color 

usage. In addition, we used “NA” to refer to situations 

where a drawback factor is not applicable to the color 

usage. The evaluation results are presented in Table 4. 

The order of the elements in the table (from left to right) 

is color, purpose, and six drawback factors. We used the 

following symbols to represent the six factors: “dis” for 

distraction, “unc” for coding uncertainty, “int” for loss 

of integration, “mul” for multiple color schemes, “read” 

for text readability, and “exp” for experience interference. 

In the column “task purpose,” we also used “Att” for 

attetnion, “Iden” for identification, and “Seg” for segmentation. Each row in the table is for one color usage. 

Next, we describe the evaluation of every color usage in 

ACD datablocks. 

As mentioned earlier, ACD datablocks use blinking 

red text for alerts. They also use white, green, yellow, 

and non-blinking red to distinguish different types of 

aircraft.

Drawbacks for using blinking red:

• Distraction. When the red alert text blinks and captures 

a controller’s attention, the controller may miss other 

salient visual stimuli occurring at the same time, such 

as a blinking datablock that indicates an aircraft handing-off. Therefore, the factor is evaluated as “Yes.”

• Coding uncertainty. Red is precisely correlated with 

the meaning “alert.” The factor is thus evaluated as 

“No.”

• Loss of integration. The datablocks of all the aircraft 

that are under conflict are indicated with the same red 

color, so there is no loss of integration. The factor is 

evaluated as “No.”

• Multiple coding. Red is only used for the alert text in 

ACDs, so the factor is “No.”

• Text readability. The luminance contrast between the 

red text and the dark background is about 11%, less 

than the threshold (20%) contrast for error-free reading. Thus, the factor is evaluated as “Yes.”

• Experience interference. The use of red in alert texts is 

consistent with the color use convention that red is 

reserved for alert or emergent information. The factor 

is thus evaluated as “No.”

To avoid tedious description, we will only describe the 

factors evaluated as “yes” for non-blinking red, white, 

green, and yellow. Non-blinking red has one drawback: 

It results in low text readability on a dark background. 

White is used to distinguish datablocks of owned aircraft 

from green datablocks of unowned aircraft. It has two 

potential drawbacks: distraction and loss of integration. 

Since white datablocks are much brighter than green 

datablocks, they automatically draw controllers’ attention, 
12

Table 3: A checklist of potential drawbacks of color use in ATC displays. 

Perceptual and 

cognitive issues 

Color and visual factors Possible consequences Yes 

/ No

Distraction Multiple colored targets for 

attention are onset 

simultaneously within the 

view field. 

Only one of the targets 

captures attention; others 

could be ignored. 

Coding

uncertainty 

 Messages (text or symbols) 

identified by colors do not 

have a unique meaning; thus, 

color cannot serve as the 

selection criteria. 

Slower and less accurate in 

identification compared to 

using text or symbols alone. 

Loss of 

integration 

Color-segmented messages 

need to be considered together 

simultaneously for task 

performance. 

Less chance to associate 

pieces of information that are 

color segmented. 

1) More than 3 sets of colorcoding in a display. Increasing chances of missing 

information; users tend to 

ignore color-coding.

Multiple color 

schemes 

2) One color is used for 

multiple purposes, or multiple 

colors are used for the same 

purpose.

Increasing cognitive 

workload; slower in 

interpreting information; 

increasing chances of 

misinterpreting information. 

Experience

interference

Color use differs from 

controllers’ experience (such 

as red for non-critical 

information). 

Increasing chances of 

misinterpreting information. 

Text readability The luminance contrast 

between the text and 

background colors is less than 

the threshold contrast 

(20~30%) for error-free 

reading.

Reducing reading speed; 

increasing reading errors. 

Color-naming 

consistence

Color cannot be named 

consistently among users. 

Increasing communication 

difficulty in teamwork. 

View-angle

intolerance 

Hue and luminance contrast of 

colors are largely washed off 

when viewed from large offaxis angles in LCD monitors.

Color-coding becomes 

ineffective. 
13

which decreases their perception of datablocks in other 

colors. Moreover, green and white colors segregate the 

owned and unowned aircraft in a controller’s mental representation of the traffic situation. Hence, the integration 

between owned and unowned aircraft is reduced. However, 

ATC tasks require controllers to consider owned and 

unowned aircraft together to ensure aircraft separation. 

This is especially important for those aircraft near sector 

boundaries. Due to the color-coding, controllers are less 

likely to detect conflicts between owned and unowned of 

aircraft. Therefore, application of the white color to owned 

datablocks has the potential to cause performance errors. 

The evaluation of yellow is the same as that for white, as 

described above. Fortunately, in ATC operations, yellow 

is used infrequently and momentarily, so the operational 

effect of the two drawback factors associated with yellow 

may not be as severe as that associated with white. 

DISCUSSION

In this report, we described the benefits of color use 

in ATC displays. We also derived a rationale for how to 

achieve these benefits based on accumulated vision and 

cognitive research. We also identified several drawbacks 

of color use in ATC displays and presented the potential 

consequences of inappropriate use of colors in the domain 

of perceptual and cognitive information processing. While 

systematic data were not available from our limited facility visits, those drawbacks were commonly observed in 

the ATC facilities. Also included in the report are two 

checklists that we developed to evaluate color use in ATC 

displays: “A checklist for color-use effectiveness” and “A 

checklist of color-use drawbacks.” The first checklist 

was intended to address the concern, “Can the use of 

color achieve the intended task purposes?” The second 

checklist was designed to answer the question, “May 

the use of color on ATC displays introduce any risk to 

task performance?” While these two lists may not cover 

all color factors, they are pertinent to ATC displays, so 

they can serve as a baseline to qualify the use of color in 

ATC. Manufacturers and human factors practitioners are 

encouraged to use these checklists in interface design and 

acquisition evaluation of ATC displays. The checklists 

should also be applied to the process of customizing color 

schemes of some ATC products for given facilities.

Subjective vs. objective assessment of the usefulness 

of colors

Color is something that everyone with normal color 

vision can perceive easily. Unfortunately, the neural 

mechanisms of color processing are not readily apparent. In many ways, the brain processes color information differently from the physical properties of color. 

For example, the neurons in the visual system respond 

monotonically to the increasing of luminance, so the 

brain encodes luminance information in a similar way as 

we see it. However, although colors can also be described 

as continuous variables along chromaticity coordinates, 

researchers have failed to find neural mechanisms that 

would encode continuous chromaticity variables. Hence, 

it is not surprising that subjective opinions about the effect of color can sometimes be quite different from (or 

even opposite to) objective assessments. 

One reason for using colors in displays is that users 

prefer them, despite their being remarkably inaccurate 

in task performance, compared with their performance 

using achromatic displays (Narborough-Hall, 1985). In 

fact, several studies showed that the use of colors made 

subjects’ tasks somewhat easier but not more effective 

(Christ, 1975). Sometimes, subjects feel more secure with 

color-coding. While no significant differences in response 

latencies to colored or achromatic displays (alphanumeric 

and graphic) were found, subjects reported greater satisfaction with colored displays (Tullis, 1981). Moreover, other 

experiments demonstrated that, while subjects believed 

that color improved their ability to detect details, color 

did not improve target detection or identification (Jeffrey & Beck, 1972). Hence, subjective assessments of the 

effect of color use are not sufficient for assessing displays 

of human-computer automation systems. 

Table 4: Evaluation of potential drawbacks of color use in ACD datablocks. 

Color Purpose dis unc int mul exp read 

Blinking

red

Attention Yes No No No No Yes 

white Identification Yes No Yes No No No 

green Identification No No No No No No 

yellow Identification Yes No Yes No No No 

red Identification No No No No No Yes 

“dis” distraction ; “unc” coding uncertainty ; “int” loss of integration; “mul” multiple color 

schemes; “read” text readability; “exp” experience interference. 
14

The more color, the better?

A trend in ATC displays is that more colors are being used in newly developed displays. For example, the 

Standard Terminal Automation Replacement System is 

a newer radar display for terminal facilities. It uses more 

colors than the ACD that was developed earlier. Another 

trend is that colors are being added to existing displays. 

For example, a magenta box was added to a part of the 

datablock on En Route radar displays. There seems to 

be a general belief that more colors lead to more efficient 

information processing. However, that is not always true. 

While we showed that several factors contributed to 

advantages of color use for each task purpose (attention, 

identification, and segmentation), a common factor for all 

the three task purposes is that the effectiveness of color 

use deteriorates with an increase of the number of colors 

on a display, as described in Table 1. Moreover, color use 

has some inevitable disadvantages, such as reducing text 

readability and increasing visual fatigue. Therefore, we 

suggest that color use in ATC displays should be limited, 

and a color should be used only when it is proven to 

1) benefit task performance and 2) have no significant 

disadvantage on task performance. 

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A1

Appendix A: 

CIE (International Committee of

Illumination) Color Coordinates

A computer monitor generates a color through three phosphor channels: red, green, and blue. The amount of 

phosphors emitted from a channel is specified with 8-bit digital values of the channels: r, g, and b, each for red, green, 

and blue phosphors. Computer programmers use these three numbers to specify a color on displays. For example, 

rgb values of (255, 0, 0) are for red, and (255, 255, 0) are for yellow. While rgb values specify the physical attributes 

of a color on a monitor, they do not tell how viewers perceive the color. 

The International Committee of Illumination (CIE) defined color chromaticity coordinates to describe human 

color perception. In this definition, a color can be specified by three variables: L, x, and y, where L is the luminance 

of a color while x and y determine the hue. x and y vary between 0 and 1. For example, the typical values for white 

in a computer monitor are x=0.3300 and y=0.3515; the values for red are x=0.6340 and y=0.3337. The xyL values 

of a color surface can be measured with a colorimeter. 

The relationship between rgb and xyL values can be specified with a nonlinear transformation and a 

linear matrix transformation, as described by the following equations:

R=(r/255)gamma

G=(g/255)gamma

B=(b/255)gamma 

Where the parameter gamma describes the nonlinearity of luminance response for a given monitor. It usually varies 

in a range of 1.8-2.5 for CRT monitors, with a typical default value of 2.2. The transformation between RGB values 

and CIE chromaticity coordinates (xyL) are determined by the following equations:

 

X=40.9568*R + 35.5041*G + 17.9167*B;

Y=21.3389*R + 70.6743*G + 7.98680*B;

Z=1.86297*R + 11.4620*G + 91.2367*B;

And, 

x=X/(X+Y+Z)

y=Y/(X+Y+Z)

L=Y

Notice that the parameters in these transformations vary from monitor to monitor. The parameter values used 

here are typical default values for CRT displays. The process of determining the parameters of the transformations 

for a given monitor is called color calibration.

One of the greatest disadvantages of the CIE chromaticity systems is that visually they are not spaced equally. 

Thus, distortions occur in attempting to relate perceived colors to locations of the CIE chromaticity diagram. Based 

on the xyL systems, the CIE adopted the Lu ́v ́ coordinates that were more nearly uniformly spaced with respect to 

color perception. Therefore, the chromaticity difference between two colors can be computed as ((∆u ́) 2 + (∆v ́) 2)

1⁄2.

The values of u ́ and v ́ can be computed from x and y through two non-linear equations: 

 u ́ = 4x / (-2x+12y+3)

 v ́ = 9y / (-2x+12y+3)

B1

Appendix B: 

Calculation of Text Readability on Visual Displays

Text readability is determined by luminance contrast of the text and background colors. The contrast threshold 

for error-free reading is typically taken as 20~30%.

1. Definition of contrast

Without specified otherwise, when text contrast is mentioned in the literature, it means the Michelson contrast, 

defined as (Lt - Lb) / (Lt + Lb), where Lt is the text luminance and Lb is the background luminance. The contrast varies 

between 0 and 1.

2. Color specification

Here lists the typical rgb values of 14 frequently used colors. Notice that the values used in ATC displays for these 

colors may vary slightly, depending on manufacturers and monitors. 

Red:..................... (255 0 0)

Green:.................. (0 255 0)

Yellow ................. (255 255 0)

Blue: ................... (0 0 255) 

Purple: ................ (102 0 153)

Brown ................. (153 75 0)

Orange ................ (255 165 0)

Pink .................... (255 192 203)

Cyan ................... (0 255 255)

Magenta .............. (255 0 255)

Black ................... (25 25 25)

White ................. (255 255 255)

Medium gray ...... (192 192 192)

Yellowish green .... (153 204 51)

3. Luminance computation

The luminance of a color can be computed with the following equation:

Lum= (Lr *r/255) gamma + (Lg *g/255) gamma + (Lb *b/255) gamma, 

Where Lr, Lg, and Lb are luminance measured at rgb values: (255, 0, 0), (0 255, 0), and (0, 0, 255). gamma is 

the non-linearity parameter of a monitor. These parameters vary from monitor to monitor. We used the following 

default values:

Lr = 21.3389

Lg =70.6743

Lb =7.98680

gamma= 2.2
B2

Table B-1 shows the calculated contrasts (in percentages) for all the text-background combinations of the 14 colors. 

When both the text and background luminance are less than 10 cd/cd2, the contrast was trimmed to zero because 

those combinations produce very low readability. 

Table B-1: Estimated text contrast for 14 color combinations. 

Red Gre Yel Blue Pur Bro Oran Pink Cyan Mag Black White Gray YG 

Red 0 53 62 45 59 29 38 49 57 15 76 64 43 40

Green 53 0 13 79 85 71 18 4 5 41 92 17 13 16

Yellow 62 13 0 84 88 77 30 17 7 51 94 4 26 29

Blue 45 79 84 0 0 0 71 77 81 57 0 85 74 72

Purple 59 85 88 0 0 0 79 84 87 68 0 89 81 80

Brown 29 71 77 0 0 0 61 69 74 42 0 79 64 62

Orange 38 18 30 71 79 61 0 13 23 24 89 34 5 1

Pink 49 4 17 77 84 69 13 0 10 37 91 21 8 11

Cyan 57 5 7 81 87 74 23 10 0 45 93 11 18 21

Magenta 15 41 51 57 68 42 24 37 45 0 82 54 29 26

Black 76 92 94 0 0 0 89 91 93 82 0 94 90 89

White 64 17 4 85 89 79 34 21 11 54 94 0 30 32

Gray 43 13 26 74 81 64 5 8 18 29 90 30 0 3

Yellowgreen 40 16 29 72 80 62 1 11 21 26 89 32 3 0