Amos TosaTa

NISTIR 88-3894

Evaluation of Colors for Use on

Traffic Control Devices

Belinda L. Collins

U.S. DEPARTMENT OF COMMERCE

National Institute of Standards and Technology

(Formerly National Bureau of Standards)

National Engineering Laboratory

Center for Building Technology

Building Environment Division

Gaithersburg, MD 20899

November 1988

Prepared for:

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101

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£j£'r?0 qj

NISTIR 88-3894 7^

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Evaluation of Colors for Use on

Traffic Control Devices

Belinda L. Collins

U.S. DEPARTMENT OF COMMERCE

National Institute of Standards and Technology

(Formerly National Bureau of Standards)

National Engineering Laboratory

Center for Building Technology

Building Environment Division

Gaithersburg, MD 20899

November 1988

National Bureau of Standards became the

National Institute of Standards and Technology

on August 23, 1988, when the Omnibus Trade and

Competitiveness Act was signed. NIST retains

all NBS functions. Its new programs will encourage

improved use of technology by U.S. industry.

Prepared for:

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101

U.S. DEPARTMENT OF COMMERCE

C. William Verity, Secretary

NATIONAL INSTITUTE OF STANDARDS

AND TECHNOLOGY

Ernest Ambler, Director

Abstract

Color has traditionally been used to convey safety information because of

its ability to attract attention and evoke a rapid response. In the

present report, research on color coding, highway safety color codes,

color deficiency, retroreflective materials, and conspicuity, is reviewed

to evaluate the effectiveness of chromaticity specifications for highway

signs and markings. The current highway specifications are typically for

colors of medium lightness and saturation, which sometimes can appear

quite dark. Data from a study by Collins et al. (1986) are reanalyzed to

compare color appearance data for both ANSI and highway colors viewed

under seven illuminants, including several HID sources. The analysis

demonstrated that the ANSI colors, especially safety yellow, were

identified more accurately in terms of color name, lightness, saturation,

and primary hue than the corresponding highway color. In addition,

selected measurements of the chromaticity of retroref lective materials

were made as background for assessing the feasibility of developing a

nighttime chromaticity specification. Based on the analysis of the

appearance of safety colors under different illuminants, it is

recommended that consideration be given to switching the FHWA

specifications for the chromaticity of colors used on traffic control

devices to the ANSI specifications

Keywords

Chromaticity, CIELAB, color, color code, color vision, color defects,

conspicuity, highway, safety, retroreflectivity

iii
Foreword

This report was prepared under Federal Highway Administration (FHWA)

contract No. DTFH61-87-Y-00073 to the National Bureau of Standards, now

the National Institute of Standards and Technology (NIST) , from June 1987

through October 1988.

Acknowledgements

The author wishes to acknowledge all the people who contributed to this

research project including the manufacturers of retroreflective color

samples who supplied the samples used in this report, the Contracting

Officer's Technical Representative, Mr. Richard Schwab who provided many

helpful insights, Dr. James Worthey and Mr. W.N. Hale who took many of

the retroref lective color sample measurements, and Ms. Belinda Kuo and

Mr. Gary Gillette who did many of the graphs. In addition, Dr. James

Worthey reviewed the final document and provided important contributions,

while Mr. W.N. Hale wrote Appendix A. The final report could not have

been completed without the able assistance of all these people.

Disclaimer

Commercial products and tradenames are provided in this report for

informational purposes only, and do not constitute an endorsement or

recommendation by the National Institute of Standards and Technology or

the Federal Highway Administration.

iv
Table of Contents

Page

1 . Introduction 1

1 . 1 Purpose 1

1.2 Existing Codes and Standards 2

1.3 Introductory Information on Color Research 4

1.3.1 Color Appearance 4

1.3.2 Color Codes 6

2. Background Information on Color Vision 16

2.1 Normal Color Vision 16

2.2 Use of Color Coding to Convey Information 18

2.3 Problems Associated with Defective Color Vision 20

2.3.1 Color Vision Defects 20

2.3.2 Implications of Color Deficiency for Color Coding . . 23

2.3.3 Color Deficiency in the Transport Industry 26

2.4 Problems Associated with Aging and Acquired Color Defects . 29

2.5 Problems Associated with the Viewing Condition 29

2.5.1 Impact of the Illuminant 29

2.5.2 Impact of the Object Color ' 31

2.5.3 Effectiveness of Highway Colors 33

2.6 Other Studies of Highway Sign Colors 56

3. Measurement of Retroreflective Colors 58

3.1 Background on Retroref lection 58

3.2 Measurement of Retroreflective Materials 59

3.3 Comparison of Chromaticity for Retroref lective Color Samples 61

4. Conclusions 71

4.1 Feasibility of Altering Current Highway Color Specifications 71

4.2 Additional Research 71

5 . Recommendations 74

6. Bibliography 75

Appendix A. Feasibility of Nighttime Color Specifications .... 82

Appendix B. CIE x,y and CIELAB Specifications for Highway Colors. 98

Appendix C. Definitions 99

v
List of Figures

Page

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

Figure

1 Chromaticity regions specified by the CIE for ordinary

colors under D65. ...... . . . ........... . 9

2 Chromaticity regions specified by the CIE for

retroreflective colors under D65 ....... ...... 10

3 Chromaticity regions specified by the FHWA for

retroref lective colors under source C . .......... 11

4 Chromaticity regions specified by ANSI Z53.1 for ordinary

surface colors for source C ................. 12

5. Confusion lines for dichromatic observers. ......... 25

6. CIELAB comparison of red samples .............. 35

7. Color naming, lightness and saturation judgements for

ANSI red ........................... 36

8. Color naming, lightness and saturation judgements for

sample #11 (highway red) .................. 37

9. CIELAB comparison data for orange samples. ......... 43

10 Color naming, lightness, and saturation data for

ANSI orange. ........... ........ 44

11 Color naming, lightness, and saturation data for sample

#35 (highway orange) .................... 45

12 CIELAB comparisons for yellow samples ........... 46

13 Color naming, lightness, and saturation data for ANSI

yellow. .......................... 47

14 Color naming, lightness, and saturation data for sample

#21 (highway yellow) ................... 48

15 CIELAB comparisons for green samples. ........... 50

16 Color naming, lightness, and saturation data for ANSI

green 51

17 Color naming, lightness, and saturation data for sample

#25 (highway green) 52

18 CIELAB comparisons for blue samples. ........... 53

vi
Figure 19 Color naming, lightness, and saturation data for ANSI

blue 54

Figure 20 Color naming, lightness, and saturation data for sample

#27 (highway blue) 55

Figure 21 Instrumental comparisons for engineering grade samples. . . 63

Figure 22 Shift from illuminant C to illuminant A for both

retroreflective and 45/0 measuring conditions for

engineering samples 64

Figure 23 Instrumental comparisons for high intensity samples 66

Figure 24 Shift from illuminant C to illuminant A for both

retroreflective and 45/0 measuring conditions for high

intensity samples . 67

Figure 25 Shift from illuminant C to illuminant A for two measuring

conditions for another set of engineering samples 68

Figure 26 Shift from illuminant C to illuminant A for two measuring

conditions for another set of high intensity samples 69

vii
List of Tables

Page

Table 1 Chromaticity Coordinates for National and International

Safety Color Codes. .................... 13

Table 2. Psychophysical Comparisons for ANSI and Highway Color

Samples .......................... 39

viii
1 . INTRODUCTION

Color has traditionally been used to convey safety information, to

organize complex displays, and to create moods (Cole and Vingrys, 1985).

The typical application of color for traffic control devices is that of

coding safety information and directions to allow a motorist to see a

colored sign and respond immediately with the desired action. Thus, red

is used for stop signs, yellow for warning signs, and green for

directional signs on highways in the United States (U.S).

The current specifications for highway colors (American Association of

State Highway and Transportation Officials or AASHTO, M268-84; Department

of Transportation (DOT) Manual on Uniform Traffic Control Devices or

MUTCD, 1986) are for ten highly saturated colors plus black and white.

Detailed specifications for the seven colors in current use are given in

Appendix B. The color specifications given by AASHTO and the MUTCD-*- are

different from those given by the American National Standards Institute

(ANSI) Z53.1 (1979) standards and the Department of Transportation

Hazardous Materials Transport (1973) regulations, and those given in

international standards such as the Commission Internationale de

l'Eclairage or CIE (1983), the International Standardization Organization

.or ISO (1984), and the Deutsches Institut fur Normung or DIN (1970). The

colors specified for U.S. highways are somewhat darker, particularly the

yellow, blue and green, and may not be recognized as accurately as the

colors specified by the ANSI and other systems. In addition, current

specifications for highway red, orange and yellow occupy only a small

region of color space so that orange is too close to both yellow and red,

leading to confusions, especially between yellow and orange.

1 . 1 Purpose

The purpose of the present report is to explore and evaluate the

effectiveness of the chromaticity specifications for colors used on

highway signs and markings. The current specifications are for highly

saturated colors of medium lightness^ - which can result in some colors

which are so dark as to be difficult to recognize accurately. Existing

research on color and highway applications is reviewed in the present

paper to determine the need for changing the chromaticity and luminance

specifications to improve the conspicuity and recognizability of highway

safety colors, both ordinary and retroref lective . Data from a study by

Collins et al . (1986) on the appearance of safety colors are reanalyzed

to compare the appearance of the ANSI colors with those specified for

highway applications.

-*• In subsequent references to color specifications, the term "FHWA"

will be used rather than MUTCD or AASHTO, since the MUTCD is published by

the Federal Highway Administration (FHWA) , and since it references the

AASHTO specifications.

^Except yellow which has high lightness.

1
Another purpose of the present paper is a discussion of ways of measuring

the chromaticity of highway signs including both laboratory and field

methods. Highway signs are usually retroreflective - meaning that they

reflect radiation in directions close to the direction from which the

light came (American Society for Testing and Materials or ASTM E 808-

81) . The current specifications for highway colors require that they

"shall be reflectorized or illuminated to show the same shape and color

both by day and night. All overhead sign installations should be

illuminated where an engineering study shows that reflectorization will

not perform adequately" (MUTCD 1983, p. 2A-7) . Yet, no guidance is given

for determining that the color is the same both by day and night. The

feasibility of measuring the chromaticity of retroreflective signs in

field locations is discussed in Appendix A along with a presentation of a

possible field procedure. Laboratory measurements of the chromaticity of

retroreflective colors, using different measuring geometries and

instruments are presented in section 3.

1 . 2 Existing Codes and Standards

Use of color coding for highway traffic signs evolved only slowly into

the modern code now recommended in the Manual on Uniform Traffic Control

Devices (MUTCD). Thus, according to Robinson (1967), the first highway

color code, developed in 1927, recommended only four colors: white,

black, yellow and green (for rest stations). Red, orange, and blue were

added in various revisions up to 1961, although their use was not always

consistent

.

The process of adding colors to the highway color code did not always run

smoothly. In 1957, the noted colorist Faber Birren commented that:

"To expect average mortals to think continually in the process of

seeing will seem quite contrary to human nature. In industry bright

colors will mark danger spots far more effectively than will signs

containing words and legends. The reason is simple enough, for

visual reaction to color is involuntary, while words require

deliberation" (Birren, 1957, p. 569).

At the time of Birren' s article the suggestion had been made to use black

as a background color for directional or guide signs. Birren objected to

this proposal because black, although affording high contrast with white

lettering

,

"is emotionally negative, holding little visual, mental or

psychologic interest" . . . Green, on the other hand, is "a color

which is second in recognition only to red. And because it is

emotionally tranquil rather than impulsive, it would find a wholly

logical and secondary sequence to red for STOP and yellow for

warning or caution" (Birren, 1957, p.571).

In 1967, extensive revisions were proposed for the highway code by the

National Joint Committee on Uniform Traffic Control Devices, This

committee developed the following criteria for a highway color code: 1)

The code should contain no more than 10 to 15 colors; 2) Presently used

2
highway colors should continue to be used; 3) The separation between

colors should maximize discrimination by color normal viewers; and 4) The

separation between colors for color defective observers should be no

worse than the worst pair, red and green, in use at the time of the

revisions (Robinson, 1967)

Using these criteria, the committee selected a set of 12 colors including

white, black, red, orange, yellow, green, blue, purple, bright yellow

green, brown, gray, and buff, and adopted color meanings for all but

bright yellow green, gray, and buff. By the time the regulation was

issued in 1968, the buff color had been replaced by coral, and the gray

with light blue but neither was assigned a color meaning. The following

color meanings for highway colors are given in the latest version of the

MUTCD (1986, revision 4):

Color Meanings

red - stop or prohibition;

orange - construction or maintenance;

yellow - general hazards;

green - permitted movements and direction guidance;

blue - information guidance (motorist services)

brown - recreational and cultural interest guidance;

white - regulation;

black - regulation;

purple - unassigned;

light blue - unassigned;

coral - unassigned;

strong yellow green - unassigned.

Although purple was originally selected for identifying school situations

and warning of potential conflicts with school children, this meaning has

since been dropped. Robinson (1967) speculated that the brown color may

cause problems for some, color deficient observers who might confuse it

with green or red, although evidence for this confusion has not been

uncovered in subsequent research.

Robinson commented (1967, p. 29) that the recommended highway color code

was an extension but not a major departure from highway practice in the

1960 ' s

"Six colors are assigned meanings entirely consistent with

traditional use. Two new colors - purple and brown - are added for

specific applications and another color - orange - is assigned to a

new and broader use. Three other colors are identified and reserved

for future uses... It is also noted that in order to provide "room"

for a non-confusing orange it is suggested that highway yellow be

shifted toward the yellow established for the American Standards

Association Safety Color Code. Since this change is not large, it

could be accomplished over a period of time without obsoleting

control devices now in place on the highways" (p.28 and 29).

3
This change has yet to be accomplished, however.

CIE lightness and chromaticity specifications (see p.5 for discussion)

for the current highway colors as given by AASHTO are presented in

appendix B. CIELAB values (see p.6) are also given in this appendix.

1 . 3 Introductory Information on Color Research

Before discussing color coding, there are a number of concepts which

should be defined to aid in understanding what will follow. While the

layperson uses "Color" to describe the appearance of an object, the color

researcher uses two terms, "chromaticity", and "lightness". Chromaticity

is a precise mathematical description of the wavelengths reflected by an

object, and includes both hue and saturation, while lightness is a

description of the amount of light reflected by an object. (Definitions

are given in Appendix C.) Chromaticity is specified in terms of the

Commission Internationale de l'Eclairage (CIE) tristimulus system in

which three color primaries are used to match a given color.

1.3.1 Color Appearance

Perception of the color of an object is the result of the interaction of

three separate variables:

1. The visual sensitivity of the observer when the object is viewed.

2. The spectral reflectance distribution of the object which is a

function of the particular pigments or dyes in the object.

3. The type of illumination (spectral power distribution) under which

the object is viewed.

It is easy to overlook the impact of the light source on color

appearance, but as Schiff (1980, p. 35) put it,

"a red surface appears red because it selectively absorbs

wavelengths other than red, and it reflects more of the long

wavelengths than of those in the middle or short wavelength end of

the visible spectrum. Sources, surfaces, and media that are not

differentially selective in the wavelengths they send, reflect, or

transmit to the eye are seen as ' achromatic ' rather than colored.

They appear black, gray or white."

A red object cannot preferentially reflect red (longwave) radiation if

the light source does not contain long wavelength radiation, however.

Commercially available sources vary widely in their spectral power

distribution with low pressure sodium (LPS) containing power concentrated

at about 589 nm, and tungsten having a relatively continuous spectral

power distribution,-^ The CIE uses the term "color rendering" for

specifying the ability of a light source to reveal the colors of objects.

The IES (1984, p.1-8) describes the Color Rendering Index (CRI) of a

light source in the following manner:

^Tungsten has less power in the

spectrum than daylight.

short wavelength portion of its

4
"a measure of the degree of color shift objects undergo when

illuminated by the light source as compared with the color of those

same objects when illuminated by a reference source of comparable

color temperature"

The color rendering index, however, does not provide any information

about an illuminant's effect on specific colors. Furthermore it is not a

color appearance specification. The latter is needed to define and

communicate what color a color is; that it, is the red that I see a

cherry red, a burgundy red, a brick red, a magenta, or is it really pink?

A number of color appearance and specification systems have been

developed so that one person can understand what another person means by

the term "red" or any other color. Major systems include the Munsell

system, the CIE x,y and L*a*b* chromaticity systems, the OSA USC color

order system, the ISCC-NBS color name system, and the NCS (Swedish) color

system (Billmeyer, 1987).

In the Munsell system, color is defined as a three dimensional space with

three axes, hue (color), chroma (saturation) and value (lightness). The

central black-white axis represents value, while the hues (colors) are

arranged around this axis, with increasing chroma (saturation) as one

goes further from the central axis (IES 1984; Hurvich, 1981). Color is

specified by a set of numbers and letters representing hue, value/chroma

(in that order). Thus, 5R 4/10 indicates a particular red, of value 4

and chroma 10. Munsell has also developed a set of 1600 color chips to

represent this space.

The Inter-Society Color Council - National Bureau of Standards (ISCCNBS) system which also contains a universal color language is a color

specification system using levels of color names which are defined ever

more precisely as the level increases. Thus, in level one, 13 common

color names define all colors, level 4 contains the Munsell system, while

in level six, color is measured instrumentally , and specified in terms of

the CIE chromaticity system (see Kelly and Judd, 1976) . Both the Munsell

and ISCC-NBS color systems are based on the use of CIE source C (or

average north daylight) as the standard light source.

The Optical Society of America Uniform Color System (OSA-UCS) system is a

color space with uniform visual spacing based on a rhombohedral lattice.

There are three axes in this system - L for lightness, j for yellownessblueness, and g for greenness - redness . The OSA system is considered to

be one of the best representations of human visual spacing. A set of

color chips has also been developed for this space.

The Swedish National Color System (NCS) system uses a different approach

for specifying color order. This system is based on the degree of

resemblance between a particular color and the six elementary colors - red, yellow, green, blue, black, and white. Hue is defined in terms of

the percentage resemblance of the test color to the two nearest

elementary colors, while chromaticness is defined in terms of the

resemblance of a test color to a color of the same hue with the maximum

possible chromatic content, and blackness is defined in terms of the

resemblance of the color to a perfect black (Billmeyer, 1987).

5
Finally, the CIE chromaticity system provides a way for specifying the

color in mathematical terms for any light source whose spectral power

distribution is known. This system is based on the fact that three

colored lights (primaries) can be mixed to match any given color. In

1931 the color matching data obtained for the visible spectrum from a set

of observers under rigorously controlled conditions were averaged and

adopted as the color matching functions of the normal human eye (Standard

Observer) by the CIE (Billmeyer and Saltzman, 1981; Hurvicti, 1981). The

amounts of the three primaries (color matching functions) needed to match

a color at each wavelength are termed "Tristimulus Values" or X, Y, and

Z. The three primaries, x, y, and z, have been chosen so that they are

all-positive functions.

To specify the color of an object in the CIE system, one must first

determine the spectral reflectance (or transmittance) function of the

object and the spectral power distribution of the light source

illuminating it. These two wavelength distributions are then multiplied

by each of the three tristimulus values for all wavelengths from 360-830

run and summed to obtain the X, Y, and Z tristimulus values (Wyszecki and

Stiles, 1982). The system is set up so that the chromaticity coordinates

(x, y, and z) are fractions (such as x — X/X+Y+Z) which sum to unity,

allowing one to derive the third coordinate arithmetically if the first

two are known. This approach allowed the development of the twodimensional CIE chromaticity diagram on which the x and y coordinates are

plotted, and the color of an object is specified. As noted earlier, the

concept of chromaticity includes both hue and saturation.

In 1978 the CIE defined two uniform color spaces - CIELUV and CIELAB.

The CIELAB or CIE L*a*b* system is a mathematical transformation of the

CIE system to a uniform color space which approximates the human visual

response more closely by modeling additional features of the eye's

response. In CIELAB, colors are plotted in comparison to white

(modelling lightness and color constancy) and a nonlinearity is applied,

so that equal distances between points correspond approximately to equal

perceived color differences. The CIELAB space is a cube root version of

the formula for evaluating color differences developed by Adams and

Nickerson. Robertson (1977) compared both CIELUV and CIELAB and

determined that Munsell loci of constant hue and chroma were represented

somewhat more accurately in CIELAB, but neither space is completely

accurate in representing uniform color differences. The CIELAB space is

widely used for industrial applications such as textiles, as well as for

surface colors in general.

1.3.2 Color Codes

There are three major types of colors used for safety alerting - ordinary

surface, fluorescent, and re troreflective (as well as combinations of

fluorescent and retroreflective) . Ordinary surface colors are neither

fluorescent nor retroreflective but rather diffusely reflecting opaque

surfaces (See ASTM, 1987, p.ix). The CIE (1983, p. 2) defines

fluorescent colors as materials which:

6
"are paints, pigments or dyes which exhibit photo luminescence as the

result of exposure to daylight. They absorb energy from daylight in

the shorter wave-length regions of the visible spectrum and/or in

the ultra-violet region and reradiate some of this energy at longer

wavelengths, producing narrow bands of emission in the visible

region.

The CIE (1983, p.2) also defines retroreflective materials as:

"differing from ordinary materials in that the light reflected from

them is mainly returned in directions close to the direction from

which it came. This property is maintained over wide variations of

the direction of the incident light. Under diffuse incident light,

e.g. daylight, the luminance factor is usually less than that

obtained for corresponding ordinary colors, but may be sufficient to

permit color recognition."

Retroreflective materials are available in two types - prismatic (Cube

corner) and spherical lens (See ASTM F923, 1985). Spherical lens

materials are available in several grades ranging from engineering to

high intensity grade, (depending on the narrowness of the cone of

returning light)

There are numerous color coding systems in use around the world. These

include the two U.S. codes (ANSI and AASHTO) as well as two major

international codes (CIE and ISO). In 1983, the CIE published

recommendations for the chromaticity and luminance factor of surface

colors (ordinary, fluorescent and retroref lective) to be used in visual

signalling. Specification of the luminance factor (or "ratio of the

specimen luminance to that of a perfect diffuser, when illuminated and

viewed under specified geometry"- ASTM E 284-81) is needed for surface

colors, which unlike lights, are not seen in isolation. The CIE

recommendations caution that accurate perception of surface colors will

depend on a number of factors, such as the spectral power distribution of

the illuminant, the reflectance of the surface, the state of the

observer's adaptation, and the color of surrounding areas.

For the most effective visual signalling system, the CIE recommended

minimizing the number of colors. The colors that are most accurately

recognized are red, yellow, green, blue, black and white with orange,

purple, gray, and brown as additional colors (which should be used

carefully to avoid confusions with the primary signaling colors)

Additional information for traffic signs can also be rapidly conveyed by

combination with contrasting color, distinctive symbols, and unique

shapes. The CIE cautioned (1983, p. 4) that

"in choosing colors for a given signalling system, it is important

to take into consideration the interrelations between the colors

themselves and the relations between the colors and the natural

surroundings of the signs. The detection of a sign, as well as the

recognition of its shape, require that there should be a good

contrast between the luminance and/or the chromaticity of the sign

7
and its surroundings ... Colors of high luminance factor may be

difficult to recognize under strong illumination, e.g. yellow may be

confused with white. On the other hand, colors of low luminance

factor when weakly illuminated, or when seen against a light

background, may be mistaken for black."

The color specifications given by the CIE have in part been chosen to be

recognizable by color defective observers. The recommendations state

that the purple boundary for the red chromaticity region has been chosen

partly to compensate for the reduced sensitivity to the extreme red end

of the visible spectrum typical of the protanopic and protanomalous

observer. When green is to be used in a system with red and yellow, the

CIE recommends avoiding greens on the yellow side of the color region.

In figure 1 a graph of the chromaticity regions specified by the CIE for

ordinary colors (including red, orange, yellow, green, blue, purple,

white, gray, brown and black) is presented, while in figure 2 a similar

graph presents data for retroreflective colors (including red, orange,

yellow, green, blue, purple and white). These specifications are

somewhat similar but not identical to those given by ISO, and the British

Standards Institute (BSI) , but rather different from the DIN standard.

In particular, the specifications for green vary widely among standards.

The CIE specifications differ from those used by Federal Highway

Administration (FHWA)^ which also differ from those given by ANSI Z53.1

(1979). Figure 3 presents the FHWA (AASHTO) specifications while figure 4

presents the ANSI specifications. The FHWA specifications are probably

least similar to those used in international practice. On the other

hand, the ANSI specifications are the same as those specified by the U.S.

Department of Transportation (DOT) Office of Hazardous Materials

Transport and are also referenced by the Occupational Safety and Health

Administration (OSHA) regulations for industrial safety (CFR, 1981)

.

Table 1 presents the chromaticity and luminance factor coordinates for

color codes specified by different standards associations and regulatory

authorities including, FHWA"’, ANSI, CIE, DIN, and ISO. As both the

figures and table make clear, the biggest differences occur in the green

region of the spectrum with the green specified by the U.S. standards

occupying a much smaller region which is shifted away from yellow toward

blue. This was done to minimize red-green confusions by color defective

observers (a subject which will be addressed in greater detail in section

2). Several standards, including ISO, do not give specifications for

orange, while in others the yellow is shifted from red toward green.

^The FHWA references the AASHTO specifications in the Manual on

Uniform Traffic Control Devices.

-’The FHWA specifications are also the same as those given by the

General Services Administration (GSA) in LS-300C (1977).

8
CIE - Standard llluminant D65

x

Figure 1 Chromaticity regions specified by the CIE for ordinary colors

under D65.

9
CIE - Retroreflective for D65

x

Figure 2 Chromaticity regions specified by the CIE for retroreflective

colors under D65„

10
FHWA III & IV Retroreflective

x

Figure 3 Chromaticity regions specified by the FHWA for retroreflective

colors under source C.

11
ANSI Z53.1 for llluminant C

x

Figure 4 Chromaticity regions specified by ANSI surface colors for source C„

Z53 .

1

for ordinary

12
Table 1 Chromaticity Coordinates for National and International Safety

Color Codes

FHWA

Types II and II-A (Engineering Grade) Retroreflective Sheeting Corner Points

for Illuminant C

Color 1 2 3 4 y

X V X y X y X y min max

White 0.305 0.290 0.350 0.342 0.321 0.361 0.276 0.308 35.0

Red 0.602 0.317 0.664 0.336 0.644 0.356 0.575 0.356 8.0 12.0

Orange 0.535 0.375 0.607 0.393 0.582 0.417 0.535 0.399 18.0 30.0

Brown 0.445 0.353 0.604 0.396 0.556 0.443 0.445 0.386 4.0 9.0

Yellow 0.482 0.450 0.532 0.465 0.505 0.494 0.475 0.485 29.0 45.0

Green 0.130 0.369 0.180 0.391 0.155 0.460 0.107 0.439 3.5 9.0

Blue 0.147 0.075 0.176 0.091 0.176 0.151 0.106 0.113 1.0 4.0

Type III and IV (High Intensity Grade) Retroreflective Sheeting for Illuminant C

Color 1 2 3 4 y

X y X y X y X y min max

White 0.303 0.287 0.368 0.353 0.340 0.380 0.274 0.316 27.0

Red 0.613 0.297 0.708 0.292 0.636 0.364 0.558 0.352 2.5 11.

Orange 0.550 0.360 0.630 0.370 0.581 0.418 0.516 0.394 14.0 30.

Yellow 0.498 0.412 0.557 0.442 0.479 0.520 0.438 0.472 15.0 40.

Green 0.030 0.380 0.166 0.346 0.286 0.428 0.201 0.776 3.0 8.

Blue 0.144 0.030 0.224 0.202 0.190 0.247 0.066 0.208 1.0 10.

FHWA 1969 Surface Colors for Illuminant C

X y Y%

Red 0.6003 0.3146 09.00

Orange 0.5609 0.3955 24.58

Yellow 0.5007 0.4555 50.68

Brown 0.4766 0.3816 05.52

Green 0.2088 0.4101 06.56

Blue 0.1780 0.1833 06.56

Purple 0.3056 0.2060 12.00

Bril. Yellow Green 0.3461 00.495 43.06

Light Blue 0.2410 0.2854 43.06

Coral 0.3815 0.3169 51.08

Black 0.3101 0.3161 09.43

White 0.3101 0.3161 78.66

0

0

0

0

0

13
Table 1 . Continued

ANSI Z53.1 Specifications for Safety Colors (Central Points) for Illuminant C

Color

X y Y% a* b* L*

Red 0 . 5959 0.3269 12.00 56.61 40. 98 41.22

Orange 0.5510 0.4214 30.05 33.70 82. 89 61.70

Brown 0.4766 0.3816 5.52

Yellow 0.4562 0.4788 59.10 -4.02 86. 26 81.35

Green 0.2110 0.4121 12.00 -48.04 8. 09 <-! CM CM Blue 0.1691 0.1744 9.00 -0.85 -42. 23 35.98

Purple 0.3307 0.2245 15.57

White 0.3101 0.3163 78.00

Gray 0.3101 0.3163 19.80

Black 0.3101 0.3163 2.02

Corner Coordinates for Z53.1 Specification for Safety Colors (Corner Points)

Illuminant C

Color 1 2 3 4

X y X y x y X y

Red 0.7010 0.2989 0.5533 0.3240 0.5701 0.3427 0.6678 0.3320

Orange 0.5832 0.4162 0.5331 0.4035 0.5331 0.4285 0.5606 0.4287

Brown 0.6031 0.3963 0.4450 0.3531 0.4450 0.3828 0.5599 0.4394

Yellow 0.4980 0.5011 0.4453 0.4492 0.4334 0.4665 0.4781 0.5209

Green 0.0129 0.7413 0.2445 0.4100 0.2213 0.3671 0.0147 0.4851

Blue 0.0935 0.1273 0.1785 0.2014 0.1985 0.1930 0.1079 0.0911

Purple 0.3019 0.6433 0.3072 0.2296 0.3509 0.2449 0.4287 0.1232

Corner Coordinates for DIN 6171 :Surface Colors for Traffic Signs (Corner

Points) for Illuminant C

Color 1 2 3 4

X y X V X y X y

Red 0.658 0.342 0.590 0.337 0.604 0.314 0.686 0.314

Yellow 0.481 0.518 0.441 0.471 0.490 0.440 0.531 0.468

Green 0.026 0.399 0.177 0.355 0.284 0.425 0.201 0.776

Blue 0.137 0.038 0.225 0.180 0.209 0.226 0.094 0.125

White 0.307 0.307 0.347 0.347 0.337 0.357 0.297 0.317

& Gray

White 0.315 0.335 0.337 0.357 0.332 0.362 0.310 0.340

Orange 0.583 0.416 0.533 0.398 0.552 0.356 0.631 0.369

Purple 0.453 0.134 0.372 0.238 0.321 0.206 0.334 0.079

Black 0.215 0.275 0.282 0.208 0.452 0.378 0.385 0.445

15
CIE 1983 Surface Colors (Corner Points) for Illuminant d 65

Color 1 2 3 4

X V X y X V X V

Red 0.690 0.310 0.595 0.315 0.569 0.341 0.655 0.345

Orange 0.610 0.390 0.535 0.375 0.506 0.404 0.570 0.429

Yellow 0.522 0.477 0.470 0.440 0.427 0.483 0.465 0.534

Green 0.313 0.682 0.313 0.453 0.209 0.383 0.013 0.486

Blue 0.078 0.171 0.196 0.250 0.225 0.184 0.137 0.038

Purple 0.302 0.064 0.307 0.203 0.374 0.247 0.457 0.136

White 0.350 0.360 0.300 0.310 0.290 0.320 0.340 0.370

Gray 0.350 0.360 0.300 0.310 0.290 0.320 0.340 0.370

Black 0.385 0.355 0.300 0.270 0.260 0.310 0.345 0.395

Brown 0.510 0.370 0.427 0.353 0.407 0.373 0.475 0.405

CIE 1983 Specifications for Retroreflective Colors (Corner Points) for

Illuminant Dg 5

Color 1 2 3 4

X V X V X y X y

Red 0.690 0.310 0.595 0.315 0.569 0.341 0.655 0.345

Orange 0.610 0.390 0.535 0.375 0.506 0.404 0.570 0.429

Yellow 0.522 0.477 0.470 0.440 0.427 0.483 0.465 0.534

Yellow 0.545 0.454 0.487 0.423 0.427 0.483 0.465 0.534

Green 0.007 0.703 0.248 0.409 0.177 0.362 0.026 0.399

Blue 0.078 0.171 0.150 0.220 0.210 0.160 0.137 0.038

Purple 0.302 0.064 0.307 0.203 0.374 0.247 0.457 0.136

White 0.355 0.355 0.305 0.305 0.285 0.325 0.335 0.375

ISO 3864 Standard for Safety Colors and Safety Signs - 1984 (Corner Points) for

Illuminant D 55

Color 1 2 3 4

X y X y X y X y

Red 0.690 0.310 0.595 0.315 0.569 0.341 0.655 0.345

Yellow 0.519 0.480 0.468 0.442 0.427 0.483 0.465 0.534

Green 0.230 0.754 0.291 0.438 0.248 0.409 0.007 0.703

Blue 0.078 0.171 0.150 0.220 0.210 0.160 0.137 0.038

White 0.350 0.360 0.300 0.310 0.290 0.320 0.340 0.370

Black 0.385 0.355 0.300 0.270 0.260 0.310 0.345 0.395

Brown Not Specified

Orange Not Specified

Purple Not Specified

Gray Not Specified

14
2 . BACKGROUND INFORMATION ON COLOR VISION

Current research on human color vision capabilities is discussed in the

following section. The capabilities of both normal and color defective

observers are documented, as well as the development of color codes for

color defective observers based on their discrimination capabilities.

2 . 1 Normal Color Vision

Recently, Boynton (1988), Hurvich (1981), Jacobs (1986), Marr (1982),

Pokorny and Smith (1986), Wright (1946, 1969), and Hurvich and Jameson

(1972) reviewed current research in color vision. These reviews

reiterated that there are two types of photoreceptors in the human eyethe rods, which operate at low illuminance levels, and the cones, which

operate at higher illuminance levels and which are responsible for color

perception. The rods contain one type of photopigment, maximally

sensitive about 505 nm, while it is now believed that the cone

photopigments have their spectral peaks at about 419, 531 and 559 nm

based on data from microspectrophotometry (Jacobs, 1986). The three

types of color receptors in the eye are linked into an opponent color

system with two separate color channels - red versus green, and blue

versus yellow, as well as one achromatic channel.

The ability to discriminate color varies through the visible spectrum.

Wyszecki and Stiles (1982) discussed research on the ability to make fine

discriminations of differences in wavelength. They reported that all the

curves for wavelength discrimination have a similar appearance, with

discrimination becoming rapidly poorer at the ends of the visible

spectrum. Two relative maxima of AA are observed at approximately 460 nm

in the blue and in the green at about 530 nm, while three relative minima

occur at approximately 440, 490, and 590 nm. Wavelength discrimination

depends on luminance level, field size, surround luminance, retinal area

studied and observation technique (Pointer, 1974; Frome , Buck and

Boynton, 1981; Burns and Eisner, 1985).

Generally, decreasing field size decreases discriminability , particularly

if very strict foveal fixation is also used. In this case, wavelength

discrimination is very poor in the blue-green region. Wright collected

extensive just noticeable difference (JND) data from which it is evident

that the CIE 1931 chromaticity diagram is not a uniform color appearance

diagram; differences in the "green" region in the upper portion of the

diagram are less detectable than similar differences in the "bluishpurple" region in the lower left portion (Wyszecki and Stiles, 1982).

This means that differences in chromaticity vary through the spectrum and

across mixtures of colors. Such variations are much less pronounced in

CIELAB as noted earlier. Pointer (1974) found that the color temperature

of the adapting field influences discrimination sensitivity, while Burns

and Eisner (1985) determined that very large fields and high retinal

illuminances will also alter the ability to make color matches.

Another approach to determining accurate color recognition has been the

color naming approach used for surface colors. Werner and Wooten (1979)

16
commented that hue naming and perception has a basis in physiology in the

opponent color coding found in the ganglion and lateral geniculate cells.

In a series of articles, Boynton and his colleagues explored the location

of "basic" colors in the OSA set of uniform colors using three response

measures - consistency of color naming, consensus of color names among

subjects, and reaction times. They explored the hypothesis that certain

colors are basic to the human visual system and are not a learned

response specific to a particular language or culture. Thus, Boynton and

Olson (1987) found that the 424 color samples of the OSA set could be

largely described by a lexicon of eleven basic color terms - white,

black, red, green, yellow, blue, brown, gray, orange, purple, and pink.

They found a consistent use of the eleven basic terms for about 70% of

the color judgements and similar consistency for 5% of the nonbasic

terms. Responses for only about 5% of the judgements were both

inconsistent and lacking consensus. In addition to the more consistent

use of color names, response time was shortest for the basic terms.

Boynton and Olson found that greens and blues tended to be used more

frequently than other color names, although this may in part be due to

the lack of good whites, blacks and highly saturated colors (reds in

particular) in the OSA sample set. They also found that although

observers agreed on color names for samples, the centroid color

(calculated mathematically from the OSA chromaticity values for each

color sample) for a given color name tended to be close but was not

identical among observers.

Uchikawa and Boynton (1987) determined that native Japanese speakers also

divided the color space into 11 categories of colors that were very

similar to those used by English speaking observers. The authors

"interpret the results to imply a strong physiological basis for color

sensation, one that is little influenced by genetic or cultural

differences between Americans and Japanese" (1987, p.1833). Boynton

(1987) reported that the color naming technique works well even when the

color rendering of the light source is degraded (through the addition of

low pressure Sodium light) . He suggested that people tended to remember

the name (category) of a color rather than the color sensation itself

indicating that "categorical color perception, which is not tested by

current color-rendering measures, is remarkably well-preserved despite

illumination of very poor quality" (p. 69).

The eleven basic color names identified by Boynton and his colleagues are

very similar to those used in current safety color codes. Such codes

typically use white, black, red, green, yellow, blue, brown, gray,

orange, and purple. (Pink is the only "basic" color not in use, although

FHWA does provide for a coral color.) These data suggest strongly that

current safety color coding systems are tapping into basic color

sensations that observers agree upon and recognize readily.

Accurate recognition of a color depends not only on the color itself but

also on the contrast with its background. In illumination engineering,

contrast has traditionally been specified in terms of the luminance of a

black object on a white background. Applying such logic to a colored

sign does not allow the chromatic contribution to black and white

17
contrast to be quantified, however. A number of laboratory studies have

looked at the perceived "distinctness" of a sharp border between two

areas of uniform color. These studies indicate that red- green contrast

adds to black and white contrast (as an orthogonal vector) in determining

the distinctness of a border (Frome, Buck and Boynton, 1981). The

results from these studies are similar whether subjects assign a

numerical rating to the border between the two colors; or set an

achromatic border to have the same distinctness as a colored one (Frome,

Buck and Boynton, 1981). Such findings would seem to have direct

application to highway signs, where lettering has both achromatic and

chromatic contrast with the background.

The red-green component of contrast of sign lettering depends not only on

the pigments used for the sign, but also on the spectrum of the

illuminant. Worthey (1982) showed that common light sources differ

markedly in their ability to reveal red-green contrasts, with most

fluorescent and all high intensity discharge lamps tending to reduce redgreen contrasts relative to daylight. An experiment on the distinctness

of borders between colored Munsell papers revealed that illuminant

differences did indeed affect the distinctness of the object-color border

(Worthey, 1986b).

2 . 2 Use of Color Coding to Convey Information

Carter and Carter (1981), Christ (1975), Green and Anderson (1956)

Jacobsen et al. (1985), and Vos et al. (1956) discussed the effectiveness

of color coding for conveying useful information quickly and accurately,

particularly under stressful conditions. Their research confirms the

desirability of using color coding to convey simple, yet critically

important information. Several researchers including Birren (1957),

Booher (1978), Olson and Bernstein (1979), Robinson (1968), and Shinar

(1985) discussed problems detecting signs, colors, and obstructions on

the highway and the effectiveness of retroreflective materials for

detection.

Christ (1975) reviewed and analyzed data from 42 experimental studies

published between 1952 and 1973 on the effectiveness of color coding for

visual displays. He found that when unique color codes were used for a

target, performance was superior for color displays relative to black and

white displays. Furthermore, the increase in identification and

searching performance could be as great as 200%.

"More specifically, if the subject's task is to identify some

feature of a target, colors can be identified more accurately than

sizes, brightness, familiar geometric shapes, and other shape or

form parameters, but colors are identified with less accuracy than

alphanumeric symbols" (Christ, 1975, p. 560).

When color is used as a redundant variable (e.g. a particular shape is

always associated with a particular color)

,

identification accuracy for

simple targets is increased when compared with the use of size or

brightness as a redundant cue. A similar improvement in performance for

18
color coding is found when the task is to count or locate a feature of a

target in a display. Christ (1975, p. 560) commented that "compared to

the use of achromatic codes, search time with the use of colors can be at

least 40% less than size, 43% less than brightness, 63% less than shape,

and 43% less than alphanumeric symbols. On the other hand, irrelevant

colors in a display interfere with the subject's ability to locate

achromatic target features". Christ found that if subjects know the

color of the targets, using redundant colors can decrease search time by

32-34% for size, brightness, and shape, and 74% for alphanumeric symbols.

When Green and Anderson (1956) assessed color coding for visual search,

they found that when the observer knew the target color, the search time

depended on the number of symbols of the same color. When observers did

not know the target color, search time was proportional to the total

number of symbols in the display, thereby indicating that color can be an

effective redundant code. Search time increased for multi-colored

displays relative to single-color displays when observers were not told

the target color. In contrast, Jacobsen, Neri, and Rogers (1985) found

that the use of a fully redundant color code (using cyan, yellow, and

red) resulted in significantly shorter search time (almost twice as fast)

for a set of symbols when compared with a monochrome set. In addition,

search time was not increased for a non-color coded dimension also

present in the display. The authors concluded that color can improve

performance on certain types of displays. Boynton and Bush (1956) found

that increasing background complexity would also alter detectability,

while Cole and Vingrys (1985) noted that road traffic signs which use

redundant color coding are more likely to be located accurately and

attract the motorist's attention than achromatic signs. MacDonald and

Cole (1988) determined that color coding facilitated detection of warning

messages that appeared unexpectedly and infrequently (such as traffic

signs)

The data on color coding indicate that the use of color to provide

important, easily recognized information to motorists is likely to be one

of the most effective ways to ensure that they receive this information.

They must, however, be familiar with the color code for maximum

effectiveness. The history of color codes has involved the attempt to

develop codes with colors that are maximally discriminable from each

other, and immediately recognizable. Most of the research has been done

with colored lights rather than surface colors, perhaps because of the

need to signal information over long distances for naval and air

applications

To this end, Halsey (1959a) evaluated the discriminability of fifty

different blue, green, purple and white test colors to determine the

chromaticity boundaries for maximally discriminable signal lights in a

color naming experiment. She found that reducing illuminance decreased

the accuracy of color identification noticeably, particularly for

desaturated blues, purples, and greens, with violet being frequently

identified as blue. Whites were confused with yellows but not with blue

or greens. Increasing the viewing distance increased observer

variability and tended to shift color names slightly toward green.

19
Halsey concluded that because green was identified with reasonable

accuracy, the 1951 CIE boundaries for it were appropriate. Because the

majority of the blues within the CIE boundaries were called "purple”, she

recommended that blue and purple should not be used in the same

signalling system if possible.

In a second experiment, Halsey (1959b) explored the effects of removing

purple as a permissible name on the accuracy of identifying blue lights.

Using the same 50 test colors at two illuminance levels, she found that

blue lights were identified with much greater accuracy when purple was

not allowed as a choice. Again, reducing signal light illuminance

resulted in poorer discrimination.

Areas requiring further evaluation include the impact of color contrast

on the ability to detect sign information. As noted earlier, Frome et

al. (1981) found that the distinctness of borders was enhanced when both

chromatic and luminance contrast were present, while Worthey (1982)

demonstrated that red-green contrasts (but not blue-yellow) contribute to

border distinctness. Uchikawa and Kaiser (1982) demonstrated that colors

which were equal in brightness and saturation were not necessarily equal

in luminance. Finally, Burns, Smith, Pokorny and Eisner (1982) found

that more saturated lights were brighter than less saturated lights and

lights at the extremes of the spectrum were brighter than those in the

middle. These experiments suggest strongly that the color of an object

(or sign) can affect its perceived brightness and contrast. Since the

studies were done as vision experiments using lights under carefully

controlled laboratory conditions, further research is needed to extend

these results to safety colors under a variety of illuminants.

2.3 Problems Associated with Defective Color Vision

Determining which colors are appropriate for safety color coding is

complicated by the fact that some 8-10% of the U.S. population is color

defective. In the following paragraphs, the frequency of color defects

will be discussed, as well as the chromaticity regions for the dominant

color confusions.

Cole (1972), Cole and Vingrys (1983, 1985), Vingrys and Cole (1986)

discussed the research base for existing color vision standards in the

transport industries, relying on data on color confusions by different

types of color defective observers and reports on accident causes. Sloan

and Habel (1955a, 1955b), Nathan et al . (1964), Cole and Jenkins (1982),

Halsey (1959a, 1959b), and Jameson and Hurvich (1978) reported data on

color recognition by defective observers. These reviews indicated that

the potential for serious confusions between some reds and greens may

have been responsible for several accidents in the transport industry.

2.3.1 Color Vision Defects

There are two major classes of color defects - inherited and acquired.

The three major types of inherited color deficiencies - anomaly,

dichromacy, and monochromasy - are distinguished by the ability to match

20
red and green lights. ^ As noted earlier in the discussion of the CIE

chromaticity diagram, a color normal observer requires a combination of

three lights (primaries) to match any given color. Although an anomalous

observer also requires three primaries to match a given color, the three

will differ from those used by a normal observer. Dichromatic observers

require only two primaries, while monochromatic observers require only

one primary. The latter essentially see the world in shades of black and

white

According to traditional classifications, defects are classified by the

pigment which is missing or altered. Thus, protanomaly and protanopia

refer to alteration or loss of the long wavelength pigment, deuteranomaly

and deuteranopia refer to alteration or loss of the mid-wavelength

pigment, and tritanomaly and tritanopia refer to alteration or loss of

the short wavelength pigment. Occasionally anomalous and dichromatic

defects are classified together, under the headings of "protan",

"deutan" , and "tritan" (Hurvich, i 9 8 1 )

Hurvich (1981) gave the following incidence of color deficiencies in

different populations:

Caucasian males - 8.08%

Asian males - 4.9%

Other males - 3.12%

Caucasian Females - 0.74 %

Asian Females - 0.64%

Other Females - 0.69%

Hurvich also pointed out that for Caucasians the incidence of specific

defects varies in the following manner:

Male Protanopes - 1.0% Female Protanopes - 0.02%

Male Protanomalous - 1.0% Female Protanomalous - 0.02%

Male Deuteranope - 1.1% Female Deuteranopes - 0.01%

Male Deuteranomalous - 4.9% Female Deuteranomalous - 0.38

Male Tritanopes - 0.0001% Female Tritanopes - 0.001

Male Monochromats - 0.003% Female Monochromats - 0.002%

Total Males - 8.0% Total Females - 0.43%

Thus, the majority of those with defective color vision are Caucasian

males with roughly half of these being deuteranomalous . The few females

with defective color vision also tend to be deuteranomalous.

Traditionally, an anomalous observer was considered to be color weak with

less than normal sensitivity in one receptor system. More recently,

anomalous observers have been considered to have one receptor response

that is shifted from the normal, with the protanomalous receptor shifted

toward longer wavelengths, and the deuteranomalous receptor shifted

toward shorter wavelengths (Hurvich, 1972, 1981). Pokorny and Smith

(1987) reported that the abnormal protan pigment peaks at about 541 ran as

compared with the 534 nm peak normally found for the mid-range

^Tritan observers are identified by their inability to match a

of blue and green lights. Such observers are very rare, however.

set

21
photopigment. The deutan peak appears to be near 553 run compared with

the 560 nm peak for the normal longwave pigment. In addition, there is a

deficit in long-wave luminosity for protanomalous observers which is not

found in deuteranomalous observer (Hurvich, 1972) . Some anomalous

observers may also have reduced neural functioning or lesser

concentrations of photopigments as compared with normal observers

(Pokorny and Smith, 1987). Currently, some researchers believe that most

color defects are due to variations in the green pigment gene with

different combinations of both hybrid and normal genes for color

defective observers (Piantanida and Nathans, 1987).

Unlike the anomalous observer, who can be considered to have a shifted or

anomalous photopigment, the dichromatic observer is usually considered to

be missing a photopigment. Protanopic observers lack the long wavelength

receptor system, deuteranopic observers lack the middle wavelength

system, and tritanopes (which are very rare) lack the short wavelength

system. Protanopes also have a luminosity function which is shifted

toward shorter wavelengths, while both deuteranopes and tritanopes have a

relatively normal spectral luminosity function. Another interpretation

of the cause of the defects is that because the deuteranopic spectral

luminosity function is similar to that of the normal observer, the

deuteranopic photopigments are normal but the red/green opponent

chromatic system has zero effectiveness (Hurvich, 1981) .

A deuteranope sees only various saturations of blue and yellow, no red or

green, with a white point at about 500 nm. Because the luminosity

function of the protanope is displaced toward shorter wavelengths, long

wavelength light seen as yellow by the deuteranope will look darker to

the protanope and may be confused with dark grays or blacks (Hurvich,

1981). For protanopes, color discrimination is absent from about 520 nm

through the red, while for deuteranopes it is absent from about 530 nm

through the red. Color discrimination in the tritanope is absent from

about 445 to 480 nm (Wyszecki and Stiles, 1982). Wyszecki and Stiles

(1982) noted similar reductions in color discrimination for both

protanomalous and deuteranomalous observers although the reduction varies

for the two types of observers. Neutral points (the point at which a

monochromatic wavelength will match a given white light) for the

protanope occur from 490-495 nm and for the deuteranope from 495-505 nm.

The maximum of the luminous efficiency curve also varies for the various

types of observers, being about 540 nm for protans, about 560 nm for

deutans , and 555 nm for tritans.

Detecting color defects is a difficult procedure because some observers

with apparently normal photopigment systems appear to be less efficient

in processing color information (perhaps at the neural level) so their

color matches have greater variability than expected. Conversely, there

are some anomalous observers, even some with strong deviations from

normal color response functions, who have extremely good color

discrimination. In fact, the view is emerging that there is a range of

peak sensitivity for the visual pigments of both color normal and color

defective individuals with particular variation in the long wavelength

22
pigment and between males and females (Jacobs, 1987; Alpern, 1987;

Mollon, 1987; Adams 1987).

In addition, color discrimination in dichromatic observers is apparently

influenced by the size of the stimulus field. Such observers typically

have better discrimination for larger fields and higher levels of

illumination (Breton and Cowan, 1981; Boynton, 1988). Boynton (1988)

pointed out that the pigment- loss explanation of dichromacy, while still

adequate to explain the results for small fields, must be modified for

large fields. The experimental data indicate that with large fields most

dichromats can perceive red, even though they supposedly lack the

receptor for red. This may be due to the presence of an anomalous third

receptor activated only by the use of large fields (Boynton, 1988) .

The variations in color discrimination capabilities make diagnosing color

defects difficult and predicting color vision almost impossible. In

addition, the picture for diagnosing tritan-type defects is complicated

by the fact that changes in macular pigment and yellowing of the lens

(typical of acquired color defects) also result in losses in sensitivity

to short -wave length pigments. Tests such as lantern tests (Farnsworth,

Holmes-Wright) , wool sorting tests (Holmgren) , color chip sorting tests

(Farnsworth Dichotomous Panel D and Farnsworth-Munsell 100 Hue) , and

color plate (pseudoisochromatic) tests have been developed to detect

color defects. The tests seem to test different aspects of the

deficiency so that a person (with a mild defect) can "pass'’ one test and

fail another. Most of these tests will diagnose dichromatic individuals,

although they may not distinguish between protan and deutan defects (Cole

and Vingrys (1982, 1983). Using a battery of tests is the best way of

diagnosing color defective observers. Unfortunately, there is no simple

test for diagnosing anomalous color vision such as the pseudoisochromatic plates used for dichromats. Rather, accurate diagnosis

requires use of an anomaloscope - an expensive, laboratory instrument.

2.3.2 Implications of Color Deficiency for Color Coding

The practical implications of color deficiency are that reds and greens

tend to be confused, and pro tan- type observers tend to have reduced

sensitivity to reds, so that reds appear very dark. Knowing that many

dichromats use the color names "red" and "green" more appropriately than

expected from knowledge of their visual sensitivity, Jameson and Hurvich

(1978) assessed their ability to make fine color discriminations and use

color names. They found that the orderings made by the dichromats varied

systematically in saturation from blue colors through neutral into yellow

and that as expected, protanopes appeared to use lightness differences as

cues for colors. The color-naming behavior suggests that protanopes

follow the rule that if a color is dark, then it should be called "red".

It appears that "normal" color naming behavior occurs more frequently

with protanopes than with deuteranopes because they use lightness, rather

than color cues. Interestingly, Jameson and Hurvich found that although

the color-naming behavior was often more accurate than expected, this did

not carry over to performance of the perceptual task (namely, ordering

color chips)

23
The reduced luminosity of red in the protanope implies two conflicting

approaches - one, that red should be made brighter to be discriminated

from darker colors in the set; and two, it should remain darker to be

discriminated from green. The data from various color recognition tests

also suggest the need to ensure that light levels are reasonably high for

safety signs and traffic lights because color discrimination appears to

improve at higher levels. Booher (1978) noted the likelihood of

confusions between traffic signal lights, as well as the overall reduced

sensitivity to red lights, as potential problems for color defective

observers

.

Various color coding schemes have been proposed to improve the ability of

color defective observers to detect colors. One such approach is shown

in figure 5 which presents color confusion lines for different types of

dichromatic observers. These lines represent sets of chromatic stimuli

which will match for particular dichromatic observers. Judd, as reported

by Sloan and Habel (1955a), suggested that both deuteranopes and

protanopes see the visible spectrum in blue, white and yellow. As a

result, he developed a color code for signal lights based on the

following assumptions: 1) Dichromats who see reds as yellow will call

them red if they know the color code only contains red, green, and blue;

2) Blue signals if sufficiently large and luminous will be termed blue by

both dichromats and color-normal observers; and 3) Colors which vary from

blue-green to yellow-green for a normal observer will appear to vary from

a slightly bluish white to slightly yellowish white for a dichromat.

Their low saturation will cause them to appear different than the blue

and red signals in the system. If white is not included in the coding

system, then this "green" will not be mistaken for it. As a result, the

most feasible color code is one based on the assumption that dichromats

see two distinct hues separated by a zone perceived as white.

Sloan and Habel (1955a) conducted an experimental assessment of the color

code developed by Judd. Their experiment was designed to determine the

minimum angular subtense and luminance of colors that could be accurately

distinguished by both normal and dichromatic observers. Using eight

colors at four different luminances, they attempted to ensure that the

colors could not be distinguished by luminance differences alone by

setting the effective luminances of red to be similar to those for the

blue and bluish green. The results for ten normal observers indicated

that a 1° field was accurately recognized for luminances of- 0.7 mL and

greater. A similar study with 40 color defective observers indicated

that all but five strongly protanopic observers identified every light

correctly. If a larger test field (2°) were used, one of these five

could identify the colors accurately and three others could be trained to

recognize the test colors. A fifth failed the test repeatedly, however.

Sloan and Habel (1955a) commented that the fact that only protanopes

experienced difficulty in distinguishing reds and greens suggests that

this discrimination is intrinsically more difficult for them than for

deuteranopes. The difference in the neutral points for the two types of

dichromat means that the yellowish-green test lights were closer to white

24
Protanopic chromaticity

confusions shown on the

(x,y) chromaticity diagram

Deuteranopic chromaticity

confusions shown on the

(x,y) chromaticity

diagram

Tritanopic chromaticity

confusions shown on the

(x,y) chromaticity diagram

Figure 5. Confusion lines for dichromatic observers. Figures reproduced

from Judd and Wyszecki, Color in Business. Science and

Industry . 2nd Ed. (1963) with permission of John Wiley and

Sons, New York.

25
for the deuteranope and less likely to be confused with red. Finally,

the authors suggested that protanopes also have more difficulty in using

color names accurately (because perhaps they are used to using luminance

cues to distinguish colors). As a result, perhaps they should be

excluded from occupations requiring rapid, accurate recognition of

colors. The authors noted, however, that "Even if it were necessary to

exclude protanopes, the adoption of this particular three-color code

would make it possible to qualify about three- fourths of those with

deficient color perception" (p. 598). Sloan and Habel commented that

their data indicate that Judd's basic assumptions provide very accurate

predictions of the chromaticity limits for distinguishable colors for

most color defective observers.

In a second study, Sloan and Habel (1955b) evaluated the illuminances at

which color defective observers could distinguish red and green signal

lights seen at a distance, using lights subtending a very small visual

angle (0.4 min). In this experiment, the chromaticities of the green

lights were shifted slightly toward yellow (compared with the earlier

experiment) . The results indicated that the shift toward yellow markedly

decreased a color deficient observer's ability to recognize signal colors

accurately. In addition, as the intensity of the signal lights

decreased, so also did the accuracy of recognition. The authors

concluded that "For aviation beacons and other signals of very small

angular subtense, the chromaticity limits specified by Judd must be

rigidly maintained if any color deficient subjects are to use this redgreen signal system" (Sloan and Habel, 1955b, p.601).

Knowing that protanopic observers have a reduced sensitivity to red

light, Cole and Vingrys (1983) determined that as the dominant wavelength

of a color increases, the protanomalous response becomes more like that

of the protanope, until for deep red the response is virtually the same.

Both protanopic and deuteranopic observers showed a similar reduction in

sensitivity to white. Their data also suggested that protanomalous

observers may actually have an increased ability to detect green relative

to normal observers. Decreasing signal size did not differentially

decrease sensitivity to the different colors.

Cole and Vingrys (1983) calculated the reduction in visual range for

protanomalous and protanopic observers and found that their visual range

is about 0.4 of the normal for intense red signal colors. Protanomalous

observers also have a reduction of 0.55 to 0.65 in their visual range for

reds which lie within the CIE specified area for reds, and a detectable

reduction in sensitivity for white lights.

2.3.3 Color Deficiency in the Transport Industry

Cole and Vingrys (1985) reviewed the literature on color defects, visual

capabilities, and accident statistics to determine if transport standards

excluding color defective operators have merit. They commented that:

"color coding is used extensively in transport systems and ...is a valuable coding dimension. It is the most useful code for long

26
distance visual signalling and can facilitate accurate

identification and rapid search in complex visual environments.

This suggests that observers with defective color vision, who have a

diminished ability to discriminate color, will be at some

disadvantage in acquiring visual information quickly and accurately,

either as monitors or as operators within transport systems. . . . The results of the experimental trials are conclusive: they all

indicate that color defective observers will make significantly more

errors and have significantly slower reaction times recognizing

color signal lights when compared to normal observers ." (p . 7)

Three areas of difficulty typically are cited: increased reaction time;

increased number of identification errors or confusions; and failure by

protan observers to see reds as reds. Thus, reaction times of 42-98%

longer than normals have been reported for color defective observers,

with protanopic observers being the slowest. Error rates, too, are

greater, with errors occurring most frequently for orange-red, red,

yellow, green and white colors. The authors suggest that the orange red

currently recommended for signal red by the CIE is too yellow and will

not be recognized as red by color defective observers.

If the color code is restricted to three colors (red, green, and blue)

color defectives have little difficulty with green, but if more colors

are present in the code, then error rates may run as high as 40-50%. As

a result, Cole and Vingrys reiterated the notion that greens should be

bluish green rather than yellowish green to avoid confusion with reds.

They also noted that blues and deep reds seem to be reliably identified

by all observers, and that in almost every study, protan observers made

more errors than deutans but anomalous observers did not necessarily make

fewer errors than trichromats. Cole and Vingrys commented that the loss

of luminosity is about the same for both protanopic and protanomalous

observers, which means that both should display reduc-ed sensitivity to

yellow and white lights as well as to red. The result is that the

relative visual range for these observers is calculated to be between 30-

52% for red signals, 84% for yellows, and 82-96% for whites.

Furthermore, the recognition distances for protan observers for red

vehicle lights and traffic lights are about 50-70% of the normal

observer's. Finally, protanopes require almost four times the intensity

for red signals such as those used for road traffic signals (Cole and

Vingrys, 1985). Many red signals and signs are likely to be ineffective

for protan observers, particularly at night (Cole, 1972). The practical

implication is that protan observers will fail to see red signals that

are readily recognized by normal observers, or at the very least, they

will have longer reaction times.

Cole and Vingrys (1985) commented that even though the laboratory data

predict that color defective observers should have problems with color

codes using three or more colors, this finding does not always hold up in

field experiments. Nevertheless, they reviewed data from six field

studies which indicated that color defectives made more errors

identifying colored signal lights than did normal observers. The

analysis indicated further that increasing viewing distance decreased the

27
accuracy of color naming for the color defective observers. The authors

concluded that the field trials indicated that color defective observers

make significantly more color confusions and have a shorter visual range

than normal observers.

Cole and Vingrys then examined the literature on transportation accidents

to determine the number attributable to defective color vision. They

noted that a number of anecdotal accounts attribute several railway

accidents in England and Sweden in the late 1800 's to defective color

vision and consequent failure to recognize colored signal lights.

Unfortunately, there is no definitive evidence of the kinds of color

defects or their role, if any, in these accidents. Examination of six

studies of highway accidents also indicates confusion about the type and

degree of defect and its contribution to the accident. Cole and Vingrys

concluded that one study apparently indicated that protans had almost

double the number of rear-end collisions, while deutans had twice as many

accidents at traffic-light controlled intersections. Two aviation

studies indicated increased frequency of accidents in general aviation

that were attributable to color deficiency, although there is some

question about whether the number of flights was equal for both normal

and for color defective pilots. Cole and Vingrys concluded, however,

that defective color vision can be a significant risk factor in aviation.

"Although a number of road accident studies report that the color

defective population as a whole is not more likely to be involved in

accidents than is a normal control group, there is good evidence to

suggest that protans have higher road accident rates than would

normally be expected (Verriest et al., 1980). In aviation, those

color defective observers who are identified as having the more

severe defects of color vision (fail lantern tests) have also been

shown to have a higher accident rate than a group comprised of

normals and those who pass a lantern test." (p. 20)

Cole and Vingrys commented that "because of redundancy and system

elasticity only rarely should a failure to appreciate a color code be

critical to the operation of the system. It is likely to be critical

only when visual information is degraded, as it is under adverse weather

conditions, or when other elements of the system are not functioning

correctly" (p. 19). They concluded that:

"clearly there is sufficient evidence to warrant the retention of

color vision standards in those transport industries where the

highest standards of safety are expected. It has been established

that color defective observers have difficulty in the recognition of

color codes and that this difficulty may lead to higher accident

rates for some color defectives. Therefore, while the setting of

any standard is, to a degree, arbitrary, the available data suggest

that protans and those observers with the more severe defects of

color vision may well be at a greater risk of accident than are

other observers. (Cole and Vingrys, 1985, p. 20).

28
The review of the literature on color defects indicates that current

color codes have been developed to minimize red-green confusions,

typically by shifting the green toward blue. This shift appears to be

the most effective way to ensure that the majority of color defective

observers will recognize colors at least somewhat accurately, while

maintaining accurate recognition for normal observers.

2.4 Problems Associated with Aging and Acquired Color Defects

Problems of accurate color recognition due to the ageing process are

believed to be due to yellowing of the lens and macular pigments. Both

are particularly common as one ages and result in tritan- like defects.

Pokorny and Smith (1986) noted that acquired color vision defects may

arise from progressive cone degeneration; optic nerve disorders;

choroidal disorders; pigmentary degeneration, vascular disease, glaucoma,

cataract or dominant optic atrophy. They pointed out that Lakowski

published a seminal paper indicating that color discrimination loss is

also age -dependent, due in part to yellowing of the lens and possible

sensory/performance decrements. Wright (1969) noted that the lens of the

eye yellows with age which causes significant variations in color vision.

In addition, variability in color discrimination between observers may

arise because of variations in the density of (yellow) macular pigment.

The net effect is to reduce the blue and violet energy reaching the

photoreceptors for those with heavy pigmentation. Recent investigations

into acquired color defects have centered on the question of possible

increased sensitivity of short wavelength sensitive cones to acquired

damage (Pokorny and Smith, 1986)

Although current color vision standards do not consider changes in color

vision due to aging, this may not be a practical problem since the

changes do not result in significant red-green confusions. Rather the

losses are generally in the blue or short wavelength portion of the

spectrum, which is less widely used for safety alerting.

2 . 5 Problems Associated with the Viewing Condition

The impact of variations in observer sensitivity on the detectability of

colors has been discussed in great detail in the preceding section. This

review pointed out the need to consider observer sensitivity in setting

chromaticity standards for safety colors. While the ability to detect

safety colors is influenced by the size of the sign, the overall

illuminance and luminance, the background characteristics and clutter,

the largest impact may be that of the illuminant. There are two other

factors to be considered in this decision, however - the illuminant and

the object color itself. The impact of variation in the spectral power

distribution of the illuminant and in the spectral reflectance

distribution of the object itself will be discussed in this section.

2.5.1 Impact of the Illuminant

The switch to High Intensity Discharge (HID) sources with higher energy

efficiencies but poorer color rendering capabilities has created major

29
difficulties in the accurate recognition of highway and other types of

safety signs. Thornton (1977) and Jerome (1977) discussed the effect of

changes in the illuminant on the recognizability of the safety colors,

while Glass et al. (1983) and Collins et al . (1986) reported data on the

detectability of ordinary surface, retroreflective , and fluorescent

safety colors under different illuminants.

As background, Terstiege (1980) suggested that colors of trans illuminated

signs by day and by night should agree with the recommendations of CIE 39

(1983) as long as fluorescent lights are used, with no shift out of the

designated chromaticity regions. He did not, however, evaluate possible

chromaticity shifts due to HID lamps.

Jerome (1977) reported a study on the identifiability of the ANSI safety

colors under different light sources including HID sources. The ANSI

safety color specifications given in table 1, include red, orange,

yellow, green, blue, purple, black, which are gray, and white. Jerome's

experiment was conducted under quite low levels of illuminance (5.3 lux)

to simulate emergency viewing conditions.

Of particular interest for highway applications are Jerome's data for

fluorescent (since it is the closest to actual daylight), clear mercury,

and high pressure sodium (HPS) light sources. For fluorescent, the only

confusion was that 15% of the observers saw black as blue. For clear

mercury, the major confusions were the following: red was termed purple

by 10% and black by another 13%; orange was termed red by 22% and yellow

by 40%; yellow was termed white by 25%; green was termed blue by 18% and

gray by 13%; blue was termed black by 20%; black was termed either blue

or purple by 20% each; and both gray and white were termed yellow by 20%

each. For HPS, the major confusions were as follows: red was termed

orange by 19%, orange was termed red 17% and yellow 69%; yellow was split

evenly between yellow and white; green was termed blue by 50% and black

another by 25%; blue was termed black by 44%, while black was termed blue

by 28%. Finally gray was termed yellow by 22%, while 17% also termed

white yellow. Thus, there were major confusions for the HID sources

between red, yellow, and orange, and to a lesser extent between blue,

green, and black, as well as between yellow, white, and gray. Under

metal halide, yellow was never confused with red or orange (and vice

versa) , while green and blue were never confused with black. Jerome

suggested that colors must be separated by at least 40 units in color

space to be discriminable from each other. The effect of changing light

source is to alter the separation in space between colors. He also noted

that blue and green were confused with each other under all the light

sources to a greater or less extent (although red and orange were

confused somewhat under all sources except fluorescent)

.

Thornton (1977) evaluated the design of safety colors to make them more

discriminable under different light sources. He pointed out that an

isolated safety color must be readily identifiable as such to convey the

intended information. "For reliability of identification of the safetycolor - that is, to be sure the human observer gets the proper message

intended by use of the safety-color - it is essential that the color

30
perceived by the observer be the intended color, and be instantly

identifiable by him, by name" (Thornton, 1977, p. 92). The problem is

that certain lamps such as those studied by Jerome (1977) distort the

colors so that they lose their immediacy of identification. There are,

of course, two solutions to the problem: one, to change the light source;

and the other, to change the color. Thornton addressed the latter

approach. He noted that the chromaticity of red, orange, and yellow

shift toward each other under HPS and that their dominant wavelengths are

in the region typically termed orange yellow. He stated further "that

under the HPS lamp the gamut of coloration has become small; it follows

that the safety-colors are perceived as pale or unsaturated and grayish,

and this is in accord with observation. The red safety color is not

identifiable as 'red'" (p. 94). Similarly, under clear mercury the

dominant wavelength of ANSI Red shifts to orange and the saturation to

low.

Thornton's suggestion was to redesign the spectral reflectance of the

safety colors by suppressing the amount of blue-green and yellow

reflectance in each color. This approach is effective for those

illuminants which have spectral power distributions across the visible

spectrum. Illuminants such as low pressure sodium, clear mercury, and

high pressure sodium, however, have little or no energy in the red

portion of the spectrum, meaning that they cannot render red (and orange)

colors accurately. In these cases, the addition of fluorescence to a

safety color may make it more identifiable. Thornton demonstrated

theoretically that the addition of fluorescence to red, orange, yellow,

and purple improved their dominant wavelength under clear mercury. The

improvement was less marked for blue and green (which had maintained a

more correct dominant wavelength anyway) . Addition of fluorescence to

red and orange for LPS is effective since their dominant wavelength is

greater than 589 nm (the primary wavelength of LPS) . A similar procedure

for green and blue is not effective for LPS, however, since their

dominant wavelength is below 589 nm. Although Thornton did not use human

observers in a strict experimental protocol, he reinforced the idea that

the ANSI safety colors are unlikely to be identified accurately under

many common lights sources, including those used in highway applications.

He also suggested that these illuminants will desaturate colors by

altering both their chromaticity and luminance.

2.5.2 Impact of the Object Color

Two studies at NBS (Glass, Howett, Lister, and Collins, 1983; and

Collins, Kuo, Mayerson, Worthey, and Howett, 1986) explored the

identifiability of ordinary, fluorescent, and retroreflective colors

under a variety of light sources

The first study by Glass et al. (1983) concentrated on red and orange

samples in a pilot laboratory experiment which used seven observers and

five light sources including tungsten, metal halide (MH) , fluorescent,

high pressure sodium (HPS), and low pressure sodium (LPS). Four series

of samples were studied: the ten ANSI samples; 20 ordinary samples

(primarily red) ; ten retroreflective or retroreflective fluorescent

31
fluorescent samples (three yellow-green, three orange and eight red) . Observers viewed each sample under each light source and responded with a

color name. Responses were tabulated for the following color names: red,

orange, yellow, green, blue, purple, white, brown, gray, and black, as

well as two combination categories of red-orange and orange-red.

The data indicated that ANSI blue, green, and purple were generally

identified correctly under all sources except LPS (although green was

frequently termed blue under HPS) . Yellow was correctly identified under

all sources, but serious confusions occurred for orange and red under all

sources except tungsten and fluorescent. For the 20 ordinary samples,

two samples, a yellow-green and a red, were identified correctly more

frequently than the corresponding ANSI color with all other colors having

significant confusions for most illuminants. Nominally red samples were

termed red, orange, or yellow depending on the illuminant. In the

retroref lective series, three samples, blue, green, and orange, were

more accurately identified under all light sources than the corresponding

ANSI color. None of the retroreflective red samples were effective,

since all had marked confusions with orange. In addition, the white

retroref lective sample (viewed in a non-retroreflective mode) was

confused with gray under all sources except LPS where it was termed

yellow. Two fluorescent samples were identified as being effective reds

with few confusions with orange or yellow even under LPS. The green

fluorescent samples were effective except under LPS where they were

termed yellow - a potentially dangerous confusion. The authors concluded

that there is a set of colors (including red, orange, yellow, green and

blue) which are more likely to be accurately identified than the ANSI set

and which should be researched further.

In the second study, Collins et al. (1986) evaluated the appearance of

fifty eight color samples including eleven red, ten orange, eight yellow,

ten green, six blue, five purple/magenta, two brown, four white, one gray

and one black. The ten ANSI samples were included as well as the "best"

blue, green, orange, and red samples from the study by Glass et al

.

(1983). A total of 16 ordinary, 17 retroreflective , 17 fluorescent, and

eight retroreflective and fluorescent samples were used. In eleven cases

a particular sample was available in both a retroref lective and nonretroref lective version (with the non-retroreflective version being

either ordinary or fluorescent) . Each sample was studied under each of

seven illuminants - tungsten (TUN) , cool white fluorescent (CW) , metal

halide (MH) , clear mercury (MER) , high pressure sodium (HPS) , low

pressure sodium (LPS) and an equal (in illuminance) mixture of metal

halide and high pressure sodium (MIX) . In addition, the spectral

reflectance distribution of all samples was measured under an

incandescent source. The spectral reflectance distribution for each nonfluorescent sample was then calculated for the seven illuminants used in

the study and the three CIE reference illuminants (A, C, and D 55 ) . Each

of the 27 fluorescent samples was directly measured under each of the

seven illuminants.

Ten color normal observers viewed each sample twice under all sources.

Observers reported the dominant color name, primary hue, secondary hue

32
and percentage of secondary hue (if any), lightness and saturation for

each sample. The results are in line with those of previous experiments

which indicated serious confusions between ANSI red, orange, and yellow

for LPS , HPS , and mercury, confusion of green with blue-green under HPS

and non-recognition of green under LPS. In addition, Collins et al.

determined that there was a set of "best" colors which were identified

more accurately under the seven light sources than the ANSI colors. This

set included the fluorescent red (57) identified by Glass et al . , a new

fluorescent orange (48), and three ordinary colors for blue (28), green

(26), and yellow (22). The ANSI samples for purple, brown, and white

performed better than the comparison samples.

Collins et al. converted the spectroradiometric data for each sample into

chromaticity and luminance data in both CIE x,y and CIELAB coordinates.

The data for both the ANSI and "best" samples were plotted in CIELAB

space to examine the gamut of coloration under each light source. This

analysis demonstrated that the gamut for the "best" colors was larger for

all light sources than that for the ANSI colors, thereby supporting the

contention that these colors are better representations of the safety

colors

Of interest to the present review is a comparison of the color naming

results for retroreflective and non-retroreflective versions of the same

sample. This indicated that in no case was the retroreflective sample

identified correctly more frequently than the non-retroreflective one,

and in three of the cases the performance was significantly poorer

(according to a comparison)

2.5.3 Effectiveness of Highway Colors

Although the research by Collins et al . (1986) focused on the ANSI safety

colors and attempts to improve their recognizability , their data

represent one of the few evaluations that contained colors similar to the

current highway colors. For the present report, their data were

reanalyzed to determine those colors that were similar to the current

FHWA colors and performance for these colors was compared with that for

the ANSI safety colors for each of the seven illuminants. Because data

from this study were obtained by viewing color samples under diffuse

illumination conditions, the experimental conditions simulate signs

illuminated by overhead illumination or daylight. They do not simulate

viewing signs under nighttime highway conditions in which signs are

illuminated directionally by car headlamps.

Similarity between the FHWA colors and the experimental colors was

determined by comparing each of the 58 samples visually with the

appropriate set of colors in the Highway Color Tolerance Charts and then

graphing those colors which were a reasonable visual match in CIELAB

space. Examination of the CIE and CIELAB specifications given in

Appendix b, indicated that a number of the (retroref lective) colors used

in that experiment, specifically red #11, orange #35, yellow #21, green

#25, and blue #27, were very similar to those specified by FHWA for

highway use. In subsequent paragraphs, these samples will be referred to

33
as "highway" colors since they are close to, but not always identical

with, the FHWA centroid color specifications.

In the reanalysis, the psychophysical results (for dominant color name,

primary hue, lightness and saturation) were examined for both the ANSI

standard color and the color most similar to the current highway

specifications for red, orange, yellow, green, and blue. A color sample

was considered to be a good example of a particular color if it had a

high percentage of that color name as the dominant color name, medium

lightness (except for yellow which should have high lightness) , high

saturation, and a high percentage (above 90%) of the desired color as the

primary hue

.

Figure 6 presents two graphs of CIELAB data for ANSI red, FHWA red and

two retroreflective red samples (#11 and #33) studied by Collins et al.

(1986). These graphs present two views of data which are, in effect

plotted in the three-dimensional L*a*b* space. In the upper graph, the

data are presented in an a*b* chromaticity space, in which a* represents

the red-green dimension and b* represents the blue-yellow dimension. In

the lower graph the data are presented in a L*a* space in which L*

represents lightness. Inspection of the two graphs in figure 6 indicates

that sample #11 is very close in both chromaticity and lightness to

highway red, confirming the visual comparison with the color tolerance

charts

.

The color naming, lightness, and saturation data for ANSI red are shown

in figure 7 for each of the seven light sources studied, while similar

data for sample 11 (highway red) are shown in figure 8. The top portion

of each figure presents the percentage of times that a particular color

name was given for the sample. The lower left figure presents the data

for percentage lightness (high, medium and low) , while the lower right

presents the data for percentage saturation (again, high, medium and

low). Comparison of figures 7 and 8 indicates that highway red (#11) was

termed red more frequently than ANSI red under all sources except HPSwhere it was never termed red. Highway red (#11) was also seen as having

medium lightness and high saturation more frequently than ANSI red.

34
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35
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Figure 8. Color naming, lightness and saturation judgements for sampl, #11 (highway red). K

37
Table 2 presents psychophysical data for the ANSI and highway comparison

samples. The frequency that a sample was given a particular color name,

primary hue percentage (PH%) , secondary hue percentage (SH%) , lightness

judgement (high, medium, low), and saturation judgement (high, medium,

low) is given for each source. Four primary and secondary hues were used

- Red (R) , Yellow (Y) , Green (G) and Blue (B)

.

Inspection of table 2 reveals that highway red (#11) is given red as a

primary hue slightly more frequently for all light sources except HPS and

LPS . Thus, the overall performance for highway red (#11) is somewhat

better - except under HPS and LPS. The frequent confusions with orange,

however, for these light sources suggest that both samples have

significant problems of accurate identification under sodium sources. A

X^ analysis of the differences in the frequency of color names, medium

lightness judgements, and medium saturation judgements was not

significant (p>.05) for the two samples, indicating that the differences

are not particularly great. The sample that was the "best" red of those

tested by Collins et al. was a fluorescent one for which extensive

durability research should be done before recommending its use under

outdoor conditions.

Figure 9 presents the CIELAB data for four orange samples, including ANSI

and FHWA. Examination of these graphs suggests that sample #35 is very

close to the FHWA specifications, a suggestion confirmed by visual

comparison with the color tolerance charts. Figures 10 and 11 present

the color naming, lightness and saturation data for ANSI orange and

highway orange (#35) . Examination of these figures suggests that highway

orange (#35) is a better orange than the ANSI sample since it is termed

orange more frequently under all light sources. It does, however have a

tendency to have lower lightness and saturation than the ANSI sample.

Table 2 indicates that highway orange (#35) is termed orange more

frequently than the ANSI sample and that its primary hue is red rather

than yellow. (Only four primary hues were allowed - red, yellow, green

and blue.) A x

^ comparison of the differences in frequency counts was

significant for color name, indicating that the highway orange was termed

"orange" more frequently than ANSI orange (p<.05). These data thus

indicate that the current highway orange is effective.

Figure 12 presents the CIELAB data for six yellow samples, including ANSI

and FHWA. Examination of these graphs indicates that sample #21 is very

close to the specifications both in CIELAB units and the color tolerance

charts. Inspection of the lower portion of figure 12 indicates that the

ANSI sample is in a different quadrant of a*b* space - being closer to

the b* axis than the other five samples. Figures 13 and 14 present the

appearance data for the ANSI sample and highway yellow (#21).

Examination of these graphs indicates that the ANSI sample is termed

yellow more frequently, has a higher lightness and greater saturation

than highway yellow (#21) for all light sources. The x^ comparisons were

significant for color name, lightness, and saturation (p<.05) for the two

samples. In addition, table 2 indicates that there is a lower percentage

of yellow as the primary hue for highway yellow (#21), as well as

consistently lower lightness.

38
Table 2. Psychophysical Comparisons for ANSI and Highway Color Samples

COLOR NAME COUNTS LIGHTNESS SATURATION

ANSI RED #6

Source Red Orange Brown PH% SH% High Med Low High Med Low

CW 11 5 1 R 85 Y 18 0 14 6 5 11 4

HPS 0 15 2 R 69 Y 31 1 10 9 4 13 3

MIX 2 9 3 R 74 Y 26 0 14 6 5 10 5

LPS 0 0 0 Y 77 G 24 2 15 3 1 6 13

MER 0 0 20 R 82 Y 20 0 3 17 0 9 11

MH 6 4 1 R 79 Y 24 0 14 6 3 14 3

TUN 12 3 0 R 85 Y 17 0 18 2 11 6 3

HIGHWAY RED #11

Source Red Orange Brown PH% SH% High Med Low High Med Low

CW 14 2 0 R 86 Y 17 0 17 3 10 10 0

HPS 0 14 1 R 64 Y 36 0 15 5 6 12 2

MIX 4 8 2 R 77 Y 24 0 16 4 6 12 2

LPS 0 0 1 Y 79 G 22 3 14 3 0 5 14

MER 6 0 13 R 87 Y 16 0 1 19 0 14 6

MH 12 3 2 R 82 Y 18 0 15 5 8 9 3

TUN 13 2 0 R 87 Y 16 0 19 1 13 7 0

ANSI ORANGE #5

Source Orange Yellow PH% SH% High Med Low High Med Low

CW 13 0 Y 72 R 28 2 18 0 1 19 0

HPS 5 13 Y 88 R 16 6 13 1 10 10 0

MIX 10 2 Y 82 R 21 1 19 0 5 13 2

LPS 0 20 Y 96 R 06 9 11 0 10 6 4

MER 0 12 Y 93 R 13 1 17 2 1 12 7

MH 11 1 Y 74 R 28 2 17 1 3 13 4

TUN 17 1 Y 76 R 24 3 16 1 3 15 2

HIGHWAY ORANGE #35

Source Orange Yellow Olive PH% SH% High Med Low High Med Low

CW 13 1 0 Y 70 R 31 2 16 2 0 16 4

HPS 16 0 0 Y 69 R 31 3 17 0 4 15 1 MIX 12 1 0 Y 78 R 22 1 16 3 3 13 4

LPS 0 19 1 Y 96 G 11 7 12 1 7 7 6

MER 1 6 7 Y 84 G 18 0 15 5 0 7 13

MH 16 1 0 Y 78 R 24 1 16 3 1 14 5

TUN 19 0 0 R 61 Y 39 1 17 2 4 12 4

39
ANSI YELLOW #4

Source Yellow YG PH% SH% High Med Low High Med Low

CW 15 4 Y 90 G 13 12 8 0 6 14 0

HPS 19 1 Y 93 G 12 14 6 0 11 7 2

MIX 17 2 Y 94 G 12 12 8 0 6 14 0

LPS 20 0 Y 99 G 7 14 6 0 18 2 0

MER 8 10 Y 85 G 18 11 9 0 10 9 1 MH 16 4 Y 95 G 12 11 9 0 12 8 0

TUN 17 2 Y 94 G 8 9 11 0 5 14 1

HIGHWAY YELLOW #21

Source Yellow Gold Orange PH% SH% High Med Low High Med Low

CW 11 3 3 Y 94 R 8 4 16 0 3 14 3

HPS 18 0 1 Y 95 G 12 7 13 0 8 10 2

MIX 10 2 5 Y 88 R 17 5 15 0 6 13 1 LPS 19 1 0 Y 97 G 9 8 12 0 9 9 2

MER 13 3 0 Y 96 G 8 1 19 0 2 16 2

MH 5 6 7 Y 85 R 22 4 14 2 2 14 4

TUN 6 6 6 Y 85 R 20 5 14 1 3 13 4

ANSI GREEN #3

Source Green BG Gray PH% SH% High Med Low High Med Low

CW 11 9 0 G 84 B 20 0 12 8 1 16 3

HPS 8 10 0 G 81 B 26 0 7 13 1 13 6

MIX 10 9 0 G 84 B 22 0 13 7 0 17 3

LPS 1 0 13 G/R Y 18 0 2 18 0 3 1 MER 17 2 0 G 89 B 19 0 10 10 0 7 13

MH 12 8 0 G 87 B 17 0 16 4 1 15 4

TUN 13 7 0 G 58 B 14 0 17 3 4 14 2

HIGHWAY GREEN #25

Source Green BG Black PH% SH% High Med Low High Med Low

CW 11 8 0 G 85 B 20 1 13 6 1 17 2

HPS 1 17 0 B 67 G 33 0 5 15 4 12 4

MIX 4 15 0 G 77 B 27 0 13 7 5 ,14 1 LPS 0 0 14 0 0 0 0 20 0 0 1 MER 17 1 0 G 92 B 12 0 9 11 1 13 6

MH 8 12 0 G 79 B 28 1 15 4 3 16 1 TUN 7 13 0 G 74 B 28 0 16 4 8 12 0

40
ANSI BLUE #2

Source Blue Purple Gray PH% SH% High Med Low High Med Low

CW 20 0 0 B 99 R 0 14 6 6 12 2

HPS 20 0 0 B 98 R/G 0 7 13 4 12 4

MIX 20 0 0 B 99 R 0 13 7 5 13 2

LPS 0 0 12 R 80 Y 16 0 0 20 0 0 5

MER 12 8 0 B 85 R 19 8 10 10 3 12 5

MH 20 0 0 B 98 R 0 17 3 4 12 4

TUN 20 0 0 B 97 G 0 15 5 5 13 2

HIGHWAY BLUE #27

Source Blue Black PH% SH% High Med Low High Med Low

CW 20 0 B 99 R 5 0 11 9 12 8 0

HPS 20 0 B 98 R/G 0 3 17 12 8 0

MIX 20 0 B 99 R/G 0 13 7 12 7 1

LPS 5 15 B 100 0 0 0 20 1 2 8

MER 19 0 B 96 R 0 1 19 8 12 0

MH 20 0 B 98 R/G 0 15 5 11 9 0

TUN 20 0 B 98 R/G 1 13 6 12 8 0

ANSI BROWN #7

Source Brown Tan Olive PH% SH% High Med Low High Med Low

CW 20 0 0 R 75 Y 24 0 3 17 0 13 7

HPS 11 1 7 R 79 Y 25 0 7 13 0 10 10

MIX 15 3 2 R 79 Y 21 0 5 15 1 10 9

LPS 2 6 6 G 87 Y 14 3 11 6 0 5 13

MER 11 1 7 G 86 Y 10 0 7 13 0 6 14

MH 18 2 0 R 76 Y 26 0 4 16 1 9 10

TUN 19 0 0 R 79 Y 20 0 3 17 0 9 11

HIGHWAY BROWN #38

Source Brown Tan Olive PH% SH% High Med Low High Med Low

CW 20 0 0 R 79 R/Y 0 4 16 1 11 8

HPS 13 1 6 R 80 Y 23 1 7 12 0 10 10

MIX 18 0 2 R 79 R 34 1 5 14 0 10 10

LPS 2 4 8 G 88 Y 17 1 12 7 0 3 14

MER 14 0 5 G 84 Y 9 0 3 17 1 8 11

MH 16 1 1 R 78 Y 20 0 4 16 1 12 7

TUN 20 0 0 R 78 Y 21 0 6 14 1 9 10

41
ANSI WHITE #10

Source White Yellow PH% SH% High Med Low High K(t> a Low

CW 20 0 20 0 0 0 0 0

HPS 20 0 20 0 0 0 0 0

MIX 20 0 20 0 0 0 0 0

LPS 0 20 Y 97 R 8 15 5 0 20 0 0

MER 19 0 20 0 0 0 0 0

MH 19 0 20 0 0 0 0 0

TUN 20 0 20 0 0 0 0 0

RETROREFLECTIVE WHITE #31

Source White Yellow Gray PH% SH% High Med Low High Med Low

CW 8 0 12 18 2 0 1 0 2

HPS 5 0 13 15 5 0 0 1 2

MIX 4 0 15 16 4 0 0 0 1

LPS 0 13 0 Y 94 G 9 5 15 0 6 9 5

MER 5 0 15 15 5 0 0 0 1 MH 3 0 17 15 5 0 0 0 1

TUN 4 0 16 15 5 0 0 0 1

42
*3*

VALUES

L*

value*

ORANGE

Source C

a* VALUES

ORANGE

Figure 9. CIELAB comparison data for orange samples.

43
ANSI

ORANGE

#5

Color

Naming

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tr; i 1 1 1 r 8t8£88$88S°

Figure 10. Color naming, lightness, and saturation data for ANSI orange #5

44
RETROREFLECTIVE

ORANGE

#35

Color

Naming

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l

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Figure 11 Color naming, lightness, and saturation data for sample #35

(highway orange)

.

^5
values

YELLOW

Source C

YELLOW

Source C

a* VALUES

Figure 12. CIELAB comparisons for yellow samples.

46
s

Ji

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Figure 13 Color naming, lightness, and saturation data for ANSI yellow.

47
CSI

a*fe o

>1

uj ®

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H 8

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t—

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CE

kmwwv

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18^"658 ' S3tUrati0n d3ta f° r #21

48
Examination of these data indicates that this sample is also termed

yellow less frequently than the ANSI yellow, and has lower lightness and

saturation. These comparisons suggest that samples such as #21 and #36

are not as good a yellow as the ANSI yellow, because they have a large

number of confusions with orange, and are seen as darker, less saturated

colors. Darker colors will also contrast somewhat less well with black

than lighter yellow, although such contrast differences are far too small

to be of practical significance.

Figure 15 presents the CIELAB data for four green samples, including ANSI

and FHWA. These graphs suggest that highway green (#25) is closest to

the specifications for green but that the ANSI sample has higher

lightness as measured by L*. Figures 16 and 17 present color appearance

data for highway green (#25) and the ANSI sample which suggest that the

ANSI color is seen as green more frequently than highway green (#25)

.

The latter is seen as "blue -green" under HPS , MIX, MH and TUN, whereas

the ANSI sample is seen as "green". Both samples have generally medium

saturation and medium to low lightness. The x

comparison for color name

was significant (p<.05). Table 2 indicates that highway green (#25) tends

to have lower percentages of green as the primary hue - and in fact is

given blue as the primary hue for HPS. These data suggest that the ANSI

green is a better green than highway green (#25) . Both samples are bluer

greens rather than yellower greens to minimize confusions for color

defective observers.

Finally, figure 18 presents CIELAB data for blue samples which suggest

that sample 27 is closest to the FHWA specifications, although the

agreement is poorest for the blue samples. Figures 19 and 20 present

color appearance data for ANSI blue and sample #27. These data indicate

that the ANSI blue is termed blue slightly more frequently than sample 27

(except under mercury light) and is seen as being lighter. It has a

significantly lower saturation, however, according to the x

^ analysis.

An analysis in which the data for ANSI brown and highway brown were

compared was not significant. The two samples are very close in CIELAB

space so that there should have been no difference' in psychophysical

results, as indicated by Table 2. This table does indicate problems for

the white retroreflective sample which tends to be termed gray under

diffuse viewing conditions. High intensity white retroreflective samples

have an even greater tendency to be termed gray, except when viewed under

directional illumination. (It should be noted that these white samples

may represent the effective light limit for this type of retroreflective

sheeting.) This may not be a problem since retroreflective white is

typically used as contrast color for legends against a colored

background. Care should be taken, though, to maintain good contrast

between background and legend.

49
eanm

GREEN

8ource C

20

18

16

14

12

10

8

6

4

2

0

-2

-4

-6

-8

10

-80 -60 -40 -20 0 •* VALUES

2C

39 a

GREEN

Source C

ANSI

FHWA

25

"I— 'l l l !

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CIELAB comparisons for green samples.

30

Figure 15.
ANSI

GREEN

#3

COLO*

NAME

COUNTS M

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r“—i r——i ~f 1 —i r 8 8 2 8 8

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Figure 16 Color naming, lightness, and saturation data for ANSI green,

51
in

CM

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LU

LlJ ct « o I

LU I

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LU

OL

o

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Figure 17 Color naming, lightness, and saturation data for sample #2

(highway green)

.

52
to*

VALUES

>5

60

50 -

40 -

30 -

20 -

10 -

0

-10

-20

-30

BLUE

Source C

28

ANSI

FITVTA

27

40

-60 -40 -20

b* VALUES

10

0

-10

-20

-30

-40

-50

-60

-30 -10 10

»X VALUES

Figure 18. CIELAB comparisons for blue samples.

BLUE

Source C

28

FHWAD

ANSI

40

27

53
CM

at? i*> S

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igure 19 Color naming, lightness, and saturation data for ANSI blue

54
Y///////, <

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55
The reanalysis of the Collins et al . data indicates that highway yellow

was significantly less accurately recognized than ANSI yellow with

numerous confusions with orange as well as lower saturation and

lightness. In addition, both the highway green and blue were seen as

darker than the comparable ANSI color. While highway red was generally

recognized more accurately than ANSI red, its performance was equally

poor under HPS , where both colors were termed orange. The widespread use

of HPS for roadway lighting and the importance of red in signalling stop

and prohibited actions suggests that there is the potential for serious

confusions with the highway specifications for this color. On the other

hand, the analysis suggests that highway orange may be more accurately

recognized with higher saturation and lightness than ANSI orange.

2.6 Other Studies of Highway Sign Colors

MacNeill (1965) evaluated the impact of different color combinations on

observers' ability to detect caution and warning signs for three light

levels. He determined that black on yellow, and white on black were

significantly more legible than combinations such as white on red, red on

black, or black on red. In addition, white on orange and white on red

were completely illegible under low red illuminance, while red and black

were illegible under low white illuminance. As a result, he recommended

using black on yellow for caution signs for maximum legibility - a

practice currently followed by both ANSI and FHWA.

Olson (1988) evaluated the conspicuity of road sign materials. Following

Cole and Jenkins (1982), he defined a conspicuous object as "one that

will, for any given background, be seen with certainty p > 90% within a

short observation time (t = 250 ms) regardless of the location of the

object in relation to the line of sight" (Olson, 1988, p.l). Pointing

out that this definition is an operational one which specifies both a

response level and operating conditions, he defined adequate conspicuity

as yielding 85% or better correct identification at appropriate distances

from the sign, with the 85th percentile response criterion being used

because that is common in U.S. practice.

The purpose of Olson's research was to establish minimum reflectance

values for retroreflective signs in settings representing cluttered

urban, suburban, and dark rural environments, for people of all ages. To

this end, he conducted a field study of the nighttime conspicuity of

signs in real world settings for two age groups (20-46 and 58-75) . The

signs varied in retroref lective properties, color, and background

complexity. Subjects in Olson's experiment were driven individually

through three test areas, varying in complexity. Their task was to call

out the word "sign" when they detected a sign and then name its color

once they could see that. Distance from the sign and accuracy of the

color name were recorded.

Three types of retroref lective materials were studied - cube-corner,

encapsulated lens, and enclosed lens with SIA (specific intensity per

unit area or coefficient of retroreflection) values ranging from 11 to

750. Signs in all colors, but not all SIA's were studied in each of

56
three complexity levels - high (a busy urban thoroughfare), medium (less

complex suburban street), and low (a two-lane rural road).

Olson found that sign identification distance varied as a function of SIA

and surround complexity, with distance decreasing with complexity but

increasing with SIA, at least for yellow signs. The results indicated

that higher SIA's were associated with greater sign identification

distances, and that increasing background complexity decreased sign

conspicuity. Using more highly reflective materials decreased the effect

of complexity, however. Performance for older subjects indicated that

they needed signs with an SIA about three times greater than younger

subjects. Olson found that yellow signs were identified correctly about

90% of the time, but significant confusions arose between red and orange,

orange and yellow, and blue and green. Again older subjects made

somewhat more errors and had shorter sign identification distances.

Olson found that colored signs other than yellow had greater sign

identification distances " than yellow signs with about the same SIA

except for a white sign located in an area with a great deal of white.

"However, the sign identification distances associated with the red,

orange, green, and blue signs were all substantially greater than those

for yellow signs having approximately the same SIA. This result was very

much unexpected." Olson attributes this difference to the same

phenomenon that underlies heterochromatic brightness matching in which

colored lights equivalent in luminance to white lights are seen as

brighter (Howett, 1986). Consequently, Olson conducted a laboratory

study in which red, orange, green, and blue colors were judged to be

brighter than yellow. Olson commented that heterochromatic brightness

may not be the sole explanation and that red, orange, green, and blue may

have inherently greater conspicuity in the context of road signs.

Nevertheless, his results indicated strongly that conspicuity depends

significantly on sign color as well as SIA (or brightness)

.

Olson also developed a correction for expectancy to overcome the fact

that subjects were expecting to see signs and to make the task more

realistic. This meant that the distances measured in the field study

were reduced by about 40% to compensate for driver expectancy. Based on

these data, Olson provided recommended SIA values for stop, construction,

overhead guide, and warning signs. Making recommendations for SIA was

complicated by the interaction with sign color since Olson had not

anticipated the strong color effect and had not studied all possible

color/SIA/complexity conditions. Olson's data reinforce the need to

conduct experiments on the detectability of colored retroreflective

materials under both diffuse (daylight) and directional (nighttime)

viewing conditions. They make it clear that color contributes

substantially to the conspicuity of sign materials.

^Olson did not address the issue of yellow hazard-warning signs

which may have been located along the same route followed by his

observers. Observers may have had trouble discriminating experimented

yellow signs from real yellow signs.

57
3. MEASUREMENT OF RETROREFLECTIVE COLORS

In this section measurements of the chromaticity and luminance of

currently available retroreflective highway safety colors (as provided by

five manufacturers) are given in both CIE x,y and CIELAB color space.

The impact of different instruments, measuring geometries, and

illuminants is discussed. The feasibility of developing a nighttime

color standard is also addressed.

3 . 1 Background on Retroreflection

Shinar (1985) conducted a study in which both the expectancy of seeing a

pedestrian at night and the reflection of the pedestrian's clothing were

varied. Although the use of retroreflective and high visibility

materials increases pedestrian detectability, the reduction in accident

frequency is smaller than expected perhaps because drivers do not expect

to see pedestrians and do not respond appropriately. In Shinar'

s

experiment, 40 observers were instructed to detect pedestrians on a

roadway under four different expectancy conditions. In the first

condition, the observer had no awareness of where the pedestrian would be

in the roadway, while in the fourth condition the car was stationary, and

the pedestrian walked away from it until the observer could ho longer

detect him. The other two conditions were intermediate in the amount of

knowledge provided about the pedestrian's probable location. The second

variable was clothing reflectance, including dark to light khaki, and

dark khaki plus a retroref lective tag. In addition, for one condition,

observers were instructed to look for a moving retroreflective tag (which

would indicate the presence of a pedestrian) . The results indicated that

visibility distance increased significantly for the four expectancy and

clothing conditions. There was a significant interaction between

expectancy and detection distance for the retroreflective tag. The

results also indicated that if a driver expected to see a pedestrian,

light clothes would increase his detectability slightly, but use of a

retroreflective tag increased his detectability very significantly. The

retroreflectivity was effective, however, only if the driver associated

it with the presence of a pedestrian.

Olson and Bernstein (1979) evaluated the nighttime legibility of highway

signs. A laboratory study was conducted in which seven colors (yellow,

orange, white, red, blue, green, and black) were used as backgrounds at

different background luminances from 0.07 cd/m^ to 211 cd/m^ . Sign

legend was black for the first three colors listed above and white for

the last four colors (at a luminance of 0.03 to 737 cd/m^) . Two surround

9 9

luminance conditions were used; high (5.14 cd/m-) , and low (0.02 cd/m^)

.

The lower luminance condition approximated the illumination provided by

low beam headlights in a car. The sign legend consisted of a Landolt

ring in different orientations. Three young adults participated in all

viewing conditions; five older (65+) adults participated in a partial

set; and three other young adults with poorer low contrast acuity also

participated in a partial set. Data for the white and green sign

condition for young adults indicated that more legend contrast was needed

as background luminance decreased (and as viewing distance increased)

.

58
Data for blue and green backgrounds were similar. For red backgrounds,

legend contrast had to be increased by as much as 1.7 times for

luminances of 3.77 cd/m^ and below. The data for black backgrounds were

similar to those for colored backgrounds at the lowest luminance levels

suggesting that the effects of color contrast effects become ineffective

at luminance levels between 0.3 and 0.03 cd/m^

.

The authors commented that their data provide evidence of systematic

differences in the luminances required for recognition accuracy at

different background colors. Thus, white, orange, and yellow required

the lowest luminances (in that order) for a given level of performance.

Increasing surround luminance increased legibility distance by about 5-

10 percent. The authors also found that subjects with poorer contrast

acuity required greater luminance contrast - sometimes as much as ten

times as much - than the normal group. Of interest is the much greater

error rate of the older subjects, regardless of luminance contrast.

Olson and Bernstein then conducted a field study in which they first

evaluated the distance at which subjects could determine the orientation

of the letter "E" placed on white and green signs varying in both

background and legend reflectivity. Eighteen subjects indicated the

distance at which they could determine the position of the "E" on the

sign. In a second study, the same subjects indicated when they could

read the legend on 23 fully ref lectorized green and white signs located

along a section of actual freeway.

Data from both studies enabled the authors to develop a visibility model

for predicting field legibility distances. This model states that

legibility distance will increase somewhat with increasing background

reflectivity. Fully ref lectorized signs have a distinct advantage in

legibility distance because of their greater legend/background luminance

contrast. The authors appears to have assumed that switching from low to

high beam headlights with retroreflective backgrounds does not increase

background reflectance but does increase legend luminance so that the

contrast of the sign increases. They do not provide any measurements of

contrast, however. Studies demonstrating that retroref lective materials

can be detected more rapidly and accurately have led to the specification

of retroreflective materials for nighttime highway use. An important

research issue is that of measuring the effectiveness of the different

types of retroref lective materials under field conditions - both in

chromaticity and in luminance.

3 . 2 Measurement of Retroreflective Materials

Lozano (1980) pointed out that it is not likely that the color of

retroref lective signs will be the same under daytime diffuse, and

nighttime directional viewing conditions. The results obtained for

safety color appearance under different illuminants indicate that the

problem of accurate color identification is even greater when HID

illuminants are used (Jerome, 1976; Collins et al . , 1986). Lozano

commented that the color of retroref lective material should appear about

the same both day and night (for illuminants such as CIE A and C) even

59
though the measured chromaticities may well have shifted. He also noted

that the legibility of a sign can be reduced by 30 percent or more by

poor maintenance

.

In a monograph which reviewed the state of the art in laboratory

measurements of retroreflectivity , Eckerle (1980) pointed out that

retroreflectors are illuminated diffusely during the day, while at night

they are illuminated directionally by a small source near the observer.

He defined the entrance angle, /3

,

as the angle between the reference axis

and the illumination axis, and the observation angle, a, as the angle

between the illumination axis and the observation axis. The observation

distance is the distance between the retroreflector reference center and

the receptor (measuring instrument) aperture (or observer) . Setting the

accuracy of the observation angle is critical and can cause substantial

changes in CIL (Coefficient of Luminous Intensity) and chromaticity with

variations in blue samples as high as 11% between laboratories. Eckerle

also pointed out that the color boundary specifications for retroreflectors must take into consideration the fact that the color of a

retroreflector will vary with geometry from day to nighttime conditions.

Unlike Eckerle, who concentrated primarily on luminance measures for

retroreflective colors, Rennilson (1980) presented detailed chromaticity

measures for retroreflective materials using different nighttime

geometries with a spectroradiometer . In his experiment, retroreflective

samples were measured under illuminant A (2856K) provided by a tungsten

halogen light source. Chromaticity measures were made for different

observation angles a- and entrance angles .

Rennilson measured six colors: red, orange, yellow, green, blue, and

white in three different types of retroreflective materials - enclosed

spherical lens, encapsulated spherical lens, and prismatic material

(micro- and macro-cube corner material) . While observation angle varied

from 0.2 to 2°, and entrance angle varied from -4 to +50°, Rennilson

reported that a 4x4 matrix containing observation angles (a) of 0.2, 0.5,

1.0 and 2.0°, and entrance angles (fi\) of -4, 15, 30 and 50° was an

adequate way of describing the changes in chromaticity with changing

measurement geometry. Rennilson discussed these changes in terms of both

CIELUV and CIELAB color difference equations, using a reference measuring

condition of 0.2° observation angle and -4° entrance angle. His data

indicated (personal communication) that changing observation angles (for

those angles studied) had less impact on chromaticity than changing

entrance angles. Figures given in the paper for blue, green, orange, and

red retroref lective samples indicate relatively little change in

normalized spectral reflectance factor as a function of changing

observation angle, particularly for those angles below 1.0°..

Asher, Harrington, and Stephenson (1978) reported an international

intercomparison from 10 laboratories of chromaticity and photometric

measurements of retroreflective materials. Fifteen samples of

retroreflective sheeting, both enclosed and encapsulated lens type, were

measured for white, red, orange, yellow, green and blue. (A larger set

of 44 samples were measured under nighttime conditions.) Measurements

60
were made with 45° incidence and normal view with 45/0 geometry under

illuminants C and Dg 5 where possible. The measuring instruments were

either spectrophotometers or tristimulus colorimeters.

Comparison of the results indicated tremendous variability in the data

for chromaticity between laboratories. Spectrophotometers generally had

less variability than tristimulus colorimeters. For spectrophotometers,

the average spread in chromaticity coordinates was about 0.008 except for

a green which had 0.017. For tristimulus colorimeters, the average

chromaticity coordinate spread was about 0.02, except green where the

average was 0.035. The luminance factors also varied with an average

spread of 15% for whites, yellow, oranges, and reds, and 23% for greens

and blues

.

The authors commented that "As was found from the nighttime results,

spectrophotometric methods correlated with each other better than do the

tristimulus measurements. However, on some samples, spectral

measurements gave a variability similar to that of the tristimulus

readings. In general, the variability in chromaticity measurements made

with both day- and nighttime geometries was of a similar order which

indicates that differences in colorimetric technique are an important

cause of the variability" (Asher, et al., 1978, pp. 27-28).

3 . 3 Comparison of Chromaticity for Retroreflective Color Samples

For the present paper, the chromaticity of 88 retroreflective samples

from seven different manufacturers were measured using different

measuring instruments and measurement geometries. Three types of

materials were used - engineering grade, super engineering grade, and

high intensity. Although luminance factors were measured, the primary

focus was on a determination of the extent in chromaticity shifts as a

function of directional viewing and illuminant to provide some indication

of shifts to be expected under nighttime viewing conditions

.

Measurements were made initially in the NIST color laboratory for three

measuring devices - a Minolta colorimeter^ CR 231 with internal

Illuminant C, a Photo Research SpectraScan Spectroradiometer with

Illuminant A, and a Minolta spot colorimeter CS-100, also with Illuminant

A. All instruments were used with 45/0 illuminating and viewing

geometry. A second series of measurements was made under directional

viewing conditions in the NIST radiometry tunnel (described by Eckerle,

1980) using the spectroradiometer with source A, a -4° entrance angle,

and a 0.6° observation angle. The radiometry tunnel was used because it

was long enough to allow the detector to be placed near the illuminant.

Although this tunnel was designed for precise measurements of

retroreflectors , the specialized instrumentation in place in it measures

only the luminance, not the chromaticity, of retroreflectors . As a

result, the normal photometer could not be used, so the spectroradiometer

8 Brand names are provided for identification purposes only and do

not constitute endorsement by NIST or FHWA.

61
was substituted, with less precise positioning. Ideally, an entrance

angle of 0.2° would have been used for the measurements but even at a

distance of 35 ft in the tunnel, the smallest angle at which the

spectroradiometer detector was properly filled was 0.6°. Increasing the

distance, to reduce the entrance angle, meant that the field of view on

the detector was underfilled.

All the samples were measured under illuminant A, with the corresponding

white retroreflective sample used to determine the spectral coefficient

of retroref lection for subsequent calculations. The chromaticity and

luminance for each sample were then calculated for illuminant C after

dividing out the effects of the measuring illuminant using the program

ADNK (Collins and Worthey, 1984; Collins et al . , 1986). Comparisons were

made for illuminants A and C because A represents nighttime illumination

conditions, while C represent daytime illumination. In addition,

comparisons were made between directional and non- directional viewing

conditions, again to represent nighttime and daytime conditions.

Figure 21 presents the chromaticity measurements in CIELAB for three

different measuring procedures for a set of engineering grade samples.

This graph compares measurements taken under directional viewing

conditions with those taken under 45/0 conditions, as well as those taken

with the spectroradiometer and Minolta colorimeter under 45/0. In this

graph, the squares (and subscript 1) represent measurements made with the

spectroradiometer using directional geometry in the radiometry tunnel,

the pluses (and subscript 2) represent measurements made in the color

laboratory with the spectroradiometer using 45/0 geometry, and the

diamonds (and subscript 3) represent measurementss made with the Minolta

CR 231 colorimeter also using 45/0 geometry. All comparisons are for

illuminant C. In this and subsequent figures, R refers to the red

sample, 0 to orange, Y to yellow, G to green, B to blue, and W to white.

Although the two sets of measurements taken in the 45/0 mode (subscripts

2 and 3) with the spectroradiometer and the colorimeter might have been

expected to coincide, they did so only for the blue sample. Measurements

in the directional mode should not have been expected to coincide with

those in the 45/0 mode, and they did not, except for the white sample.

The variability between the various instrument readings was greatest for

the yellow and least for the orange, but there was no consistent pattern

for the different measuring conditions. The effects of variation in

lighting geometry were greatest for the blue sample.

Figure 22 presents two graphs for the same samples shown in figure 21,

showing the shift in a*b* space as a function of switching from source C

(daytime viewing) to source A (nighttime viewing) . In both portions of

this figure, all measurements were made with the spectroradiometer. The

upper graph compares the data for directional viewing conditions (those

obtained in the tunnel) , while the bottom graph presents data for 45/0

geometry (obtained in the color lab). In this figure, data for source A

are represented by squares, while those for source C are represented by

pluses. Subscripts 1 and 2 refer to source C; subscripts 4 and 5 refer

to source A.

62
to*

Geometry & Instrument Comparison

Eng

Figure 21 Instrumental Comparisons

Source C.

for Engineering Grade Samples for

63
Comparison of Source C with Source A

Retroreflective Eng

Comparison of Source C With Source A

45/0 Eng

Source A + Source C

Figure 22 Shift from Illuminant C to Illuminant A for Retroreflective and

45/0 Viewing Conditions for Engineering Grade Samples.

64
Two points can be made about the graphs in figure 22. Comparing the

upper graph with the lower graph demonstrates that the geometry

(directional vs. 45/0) under which the samples were measured shifted

their position in a*b* space substantially, with the greatest shift

occurring for blue samples. Secondly, comparing the individual data

suggests that the chromaticity of all the samples except white shifted

somewhat as the illuminant was changed from source C to source A. Again

the shift was greatest for the blue sample. (Some of this shift may be

due to the mathematical assumptions for CIELAB and the von Kries

transformation or to noise in the spectroradiometer at low light levels

in the short wavelength portion of the spectrum.) Comparison of the two

graphs indicates that the way in which the sample was measured - 45/0

versus directional - had as much or more impact on its position in color

space as did changes in the illuminant.

Figure 23, which presents data for a set of super engineering grade

retroreflective samples, shows the same variability between measurement

methods. The greatest scatter between methods occurred for the yellow

sample, and the least for the orange. Again, the data obtained with the

Minolta 231 were different from those obtained with the spectroradiometer

for all samples except the blue and orange. These data reinforce the

idea that the geometry used for measuring the samples has a marked impact

on their position in a*b* space.

Figure 24 presents graphs comparing the shift in chromaticity for the

same set of super engineering grade samples for sources A and C. The

upper graph presents the directional (retroref lective) measurements made

in the tunnel and the lower one presents 45/0 measurements made in the

color laboratory. Both graphs show appreciable shifts due to the light

source, with the greatest shifts occurring for the blue sample. Again,

comparing the two graphs reveals that the measurement technique had a

marked effect on the position in a*b* space, particularly for green and

blue samples.

Figures 25 and 26 present similar data showing the shifts in chromaticity

for sources A and C for samples from two other manufacturers, with figure

25 representing engineering grade samples, and figure 26 representing

high intensity grade samples. As in figure 24, the upper graph presents

directional measurements, while the lower one presents 45/0 measurements.

Both figures demonstrate that the use of different measuring techniques

clearly shifted the samples in a*b* space as much as the shift from

source A to C. Despite the variability in chromaticity due to measuring

geometry and instrument, color samples from different manufacturers

tended to plot in about the same place in CIELAB space for the same

measuring technique and illuminant. This suggests that there was

consistency in the measuring technique for a given geometry and

instrument

.

65
Geometry & Instrument Comparison

Figure 23 Instrumental Comparisons for Super Engineering Samples.

66
to*

Comparison of Source C With Source A

Source C + Source A

Comparison of Source C With Source A

Source C + Source A

Figure 24 Shift from Illuminant C to Illuminant A for Retroreflective and

45/0 Viewing Conditions for Super Engineering Samples.

67
lb*

Comparison of Source C With Source A

Retroreflective Eng

Comparison of Source C With Source A

Diffuse 45/0 Eng

D Source C + Source A

Figure 25 Shift from Illuminant C to Xllmninant A for Retroreflective and

45/0 Viewing Conditions for Engineering Grade Samples.

68
fc>*

fc>*

Comparison of Source C With Source A

140

120

100

80

60

40

20

0

-20

-40

-60

-80

-100

-110 -90 -70 -50 -30 -10 10 30 50 70

a*

Source C + Source A

Comparison of Source C With Source A

45/0 High Intensity

130

120

110

100

90

80

70

60

50

40

30

20

10

0

-10

-20

-30

-40

-50

-60

-70

-80

-90

-100 -80 -60 -40 -20 0 20 40 60

a*

O Source C + Source A

Figure 26 Shift from Illuminant C to Illuminant A for Retroreflective and

45/0 Viewing Conditions for High Intensity Samples.

Retroreflective High Intensity

FT

+ GDI

G1

"GT

+

B4+

BN4

+ BN1

04

+

01 •

R4+

R1

D

B1

69
Nevertheless, the data presented in figures 21-26 underscore the difficulty of making accurate measurement of the chromaticity of retroreflective sign material even under controlled laboratory conditions. They

demonstrate that the use of a self-contained instrument such as a Minolta

CR231 does not provide the same results as a spectroradiometer under

either 45/0 geometry or directional geometry. Nor do the latter two

measuring techniques agree with each other.. In many cases, the

chromaticity shifts due to measuring technique are beyond the color

tolerance limits for the highway samples given in Table 1 - not because

the sample changed, but simply because the way in which it was measured

differed.

Such variability reinforces the difficulty of developing a simple field

procedure for measuring the color of retroreflective sign material.

Because changing from 45/0 geometry to directional measuring conditions

appears to affect chromaticity substantially, short cut techniques using

non- directional lighting conditions (such as those provided by the

Minolta 231) will not be of sufficient accuracy to determine whether a

sign meets the retroreflective color specifications used by FHWA. An

attempt to use a car headlamp as an illuminant in a field method was not

particularly successful due to the need to maintain precise alignment

between the detector and the illuminant. A field technique is proposed

in appendix A which would use an instrument especially designed with an

integral light source for making directional measurements but this

requires validation before being used.

Figures 21-26 suggest that using different measuring instruments may have

had less impact on the chromaticity measurements than switching viewing

conditions from 45/0 to retroreflective . These graphs also indicate,

however, that the switch from illuminant A to illuminant C shifts the

colors in color space, sometimes out of the color tolerance limits for

highway colors given in table 1. This suggests that the measurement

techniques followed here do not allow one to assume that daytime

chromaticity and nighttime chromaticity are the same. Rather, even under

the less-than-ideal laboratory conditions used, in which the geometry was

similar to, but not identical with, that currently recommended by the

CIE, the chromaticity of retroref lective material was different for

Xlluminants A and C. This indicates that one cannot measure a sample

under daylight conditions and assume that these measures will meet the

nighttime specifications. The solution appears to be the use of a field

measurement technique such as that presented in Appendix A, or rewriting

the specifications for daytime illumination and calculating the likely

shift for nighttime conditions. The data obtained to date make it very

clear that there are appreciable shifts in the chromaticity of retroreflective samples between illuminants C and A. Much greater shifts can be

expected for HID sources such as HPS and clear mercury, reinforcing the

contention that the daytime and the nighttime color of current sign

materials are not the same.

70
4. CONCLUSIONS

4.1 Feasibility of Altering Current Highway Color Specifications

The detailed reanalysis of the data collected by Collins et al. for

safety color appearance indicates strongly that highway yellow was

significantly less accurately recognized than ANSI yellow, with more

confusions with orange, lower saturation, and lower lightness. In

addition, both highway green and blue were seen as darker than the

comparable ANSI color. On the other hand, highway orange was more

accurately recognized with higher saturation and lightness than ANSI

orange. While highway red was generally recognized more accurately than

ANSI red, performance for both was very poor under HPS (and LPS) where

they were termed orange. The widespread use of HPS as a roadway

illuminant and the importance of red to indicate "stop" and prohibited

actions suggests the potential for serious confusions for this color.

Nonetheless, the reanalysis of the data on safety color appearance

suggests very strongly that serious consideration should be given to

altering the AASHTO (FHWA) specifications for highway colors to meet the

ANSI specifications. Such a move should increase the general

recognizability of colors for traffic signs, and increase the unity among

standards for safety colors in the United States.

Because the ANSI colors are widely used in industrial and other safety

applications, there should be no problem with using these colors on

ordinary highway signs. While there have been problems in the past with

making retroreflective colors with higher luminance factors, analysis of

the chromaticity data for the samples obtained from several different

manufacturers suggests that at least some are close to the ANSI samples,

indicating that the feasibility is greater now. (Obviously, of course,

currently available retroref lective materials meet the AASHTO, not the

ANSI specifications.)

4 . 2 Additional Research

Before specifications are changed dramatically, though, there is a need

for further research on the recognizability of retroref lective colors

viewed under directional lighting. The data collected by Collins et al.

were only for color samples viewed by diffuse illumination. While this

represents a major portion of highway viewing, it does not deal with the

nighttime situation of signs illuminated by headlights and HID lamps.

The colors identified as more effective should be evaluated under

nighttime viewing type conditions

Ideally the evaluation would be done as a psychophysical investigation

under laboratory conditions in which geometry, illuminant, and adaptation

level are precisely controlled and then validated under field conditions.

The study should use a range of observation and entrance angles, which

simulate those seen by a motorist approaching a highway sign. A baseline

condition under diffuse overhead "daylight" illumination should be

included to provide data on the extent of color appearance shifts due to

the shift from diffuse to directional viewing. Color samples should

71
include retroreflective versions of the ANSI colors and the current FHWA

colors to verify that the data from Collins et al. (showing better

performance by the ANSI colors) are in fact valid for retroreflective

viewing conditions. Color samples should also include aged materials, as

well as different types of retroreflective materials from engineering

grade to high intensity. The adaptation level should approximate that of

a nighttime driver, although the illuminant on the retroreflector should

be at normal headlamp intensity. The illuminants should include tungsten

halogen, metal halide, and high pressure sodium since the latter sources

are candidates for car headlamps in the future . The experimental

procedure should determine dominant color name, primary and secondary

hue, lightness, and saturation for each color sample to maximize

information on color appearance shifts. At the same time, physical

measurements should be made of the chromaticity and luminance of each

sample under each viewing condition, so that the color appearance

judgements can be correlated with the physical characteristics of the

color samples.

The proposed procedure will provide evidence on the degree of color shift

as a function of viewing geometry and illuminant changes. It should

ascertain if the apparent improvement in performance for samples meeting

the ANSI specifications found by Collins et al. hold for directional

viewing conditions. At the same time, the performance of colors which

differ from both the ANSI and FHWA specifications can be assessed to

determine if there is a '‘best" color for retroreflective and normal

viewing conditions.

Another situation which should be researched experimentally is an

evaluation of the chromatic contribution to contrast for colors (as

discussed in section 2.1) using surface colors with different illuminants

for different combinations of sign colors. In addition, the relative

contribution of car headlamps and street/sign lighting should be measured

with a spectroradiometer to determine exactly the spectral power

distributions that commonly illuminate roadway signs. At the moment, the

assumption is that the illuminant is only the headlamp or only the street

lighting. The reality is that the illuminant is some unknown mixture of

both, which is likely to shift the chromaticity of roadway signs in some

unknown manner

.

Eventually, the durability of fluorescent pigments particularly for red

signs should also be assessed for highway applications. The studies by

Glass et al .

,

Collins et al., and Thornton suggest strongly that the best

way of ensuring the red and orange are detected as such under HID sources

is to make them fluorescent. While some manufacturers claim to make

fluorescent materials that perform adequately after several years of

aging, the durability of such materials must be evaluated in laboratory

and field aging tests, before using outdoors.

Finally, the field measurement technique suggested for measuring the

chromaticity of retroref lective colors should be evaluated with an

instrument containing the proper light source-detector geometry. Under

laboratory conditions, it is relatively easy to get the light source

72
close enough to the detector to maintain a very small observation angle.

Under field conditions, however, if the light source is separated from

the detector, it is virtually impossible to obtain an observation angle

of 0.5°, and have the detecting instrument perform adequately.

Therefore, a housing for the light source should be designed, built, and

evaluated under field conditions to verify the measurements of

chromaticity . In addition, another question to be researched is the

feasibility of measuring signs under diffuse illumination (daytime)

conditions and then calculating the shift in chromaticity for nighttime

conditions. This might allow the measurements to be made during the day

when it would be safer for the measuring crew.

73
5. RECOMMENDATIONS

The analysis presented in the preceding pages suggests that there are

reasonable grounds for changing the current chromaticity specifications

for highway colors (particularly for yellow, green, and blue) to bring

them in line with the ANSI Z53.1 (1979) color codes and to increase their

detectability for drivers. The data reviewed in section 3 indicate that

the ANSI yellow, in particular, is identified more accurately in terms of

hue, lightness, and saturation. The reanalysis of the data in section 2

suggests that serious consideration should be given to altering the FHWA

specifications for colors used on traffic control devices to meet the

ANSI specifications.

While this change is being implemented, however, the effectiveness of the

ANSI colors presented in a retroreflective format should be assessed.

Such evaluation should involve field and laboratory research to verify

that these new retroreflective colors are recognized accurately when

viewed under nighttime conditions with both headlights and fixed roadway

lighting, as well as under daytime conditions. In addition, the

difficulties in measuring retroreflective materials accurately should be

explored in greater detail before implementing the field test method

given in Appendix A.

Switching to the ANSI Z53 specifications would have the additional

advantage of bringing all the safety colors specified in the United

States into agreement. This would increase the likelihood that people

will learn to recognize the colors more readily since all color codes

would be the same (See reviews by Christ, 1975; Cole and MacDonald,

1988) . The alteration in color specifications should not have any

negative impact on the ability of color defectives to recognize the

colors, since the ANSI colors were designed to lie off the confusion

lines shown in figure 5. While safety colors currently meet the Z53

specifications, retroreflective colors obviously do not, requiring time

for manufacturers to determine the feasibility of switching

retroreflective materials to the ANSI specifications.

74
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and Worthey, J.A. The role of color in lighting for meat

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1983.

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Eckerle, K.L. Photometry and Colorimetry of Retroref lection: State-ofMeasurement -Accuracy Report. Washington, D.C.: National Bureau of

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Glass, R.A.

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Halsey, R. M. Identification of signal lights. II. Elimination of the

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80
Wright, W.D. Researches on Normal and Defective Color Vision. London:

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Mesures des Caracteristiques Colorimetriques

X08-012, Dec 1974.

Australian Standard 1614. The Design and Use of Reflectorized Signs for

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Australian Standard 2700. Color Standards for General Purposes . AS

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Certain Equipment in Industry. AS 1318-1985.

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SABS 513-1985.

81
APPENDIX A. FEASIBILITY OF NIGHTTIME COLOR SPECIFICATIONS

Written by W.N. Hale

A.l Background

A. 1.1 Feasibility of Retrorefiective Color Specification

The daytime color specification given in LS 300C (1977) specifies a test

method using instruments with 45/0 (or the reverse) illuminating and

viewing geometry. The daylight sources are either diffuse (skylight) or

directional (sunlight) , and when directional can come from any direction.

The viewing angle in daylight is roughly zero (perpendicular to the plane

of the sign) but varies as the observer approaches the sign.

At night the viewing geometry is similar, but the illuminating geometry

is quite different. For the minority of signs which have their own light

sources, illumination is approximately at 45°^. For the great majority

of signs, the illumination is from approaching headlamps and is similar

to the viewing geometry, given that the observer is almost directly

behind one of the headlamps. However, at nighttime the peculiar optical

characteristics of the retrorefIective sheeting dominate the visibility

situation, specifically the narrow observational angles and the larger

and more rapidly changing entrance angles.

Can a practical nighttime color standard be written? If so, can a

practical test method be written for both laboratory and field testing?

A laboratory test method is needed for acceptance of new material. A

field test method is needed for determining whether existing signs need

replacement; it might also be used for accepting new material.

The procedures and equipment employed by Rennilson (1980) can be used to

measure existing specimens known to be satisfactory for both daytime and

nighttime use, and from these data a draft nighttime specification could

be written. However, such equipment is much more expensive, and the

laboratory space needed much more extensive, than that used now for

testing for compliance with the daytime color specification. Only a

minority of users now employ even this less expensive instrumentation.

If sufficient specimens of all the colors from all the manufacturers are

measured in the laboratory, using a variety of observational and entrance

angles, as was done by Rennilson (1980), one (or more) nighttime color

specification can be written, along with appropriate test methods.

It is to be expected that the above measurements will indicate

differences in the results obtained on different types of sheeting

enclosed lens, encapsulated lens, prismatic, etc. -- and only extensive

review of the data will determine the actual feasibility of such

^The contribution from vehicle headlamps to the overall illuminance

on an overhead, externally illuminated sign remains to be specified.

82
nighttime color specification(s)

One important factor not explored in this study is the differences

between the new materials used as measurement specimens and the weathered

materials which are candidates for replacement. Such a study will have

to use both instrumental and visual test methods, as did the original

work that resulted in the daytime color specification. One may find that

optical differences that occur among different materials when new will be

quite different for weathered retroreflectors

A second important factor, noted but not extensively explored in the

present study, relates to variations in the spectral reflectance

characteristics of colors of the same name, both among different products

of the same manufacturer and between manufacturers . Among the set of 20

specimens which were measured on the outdoor photometric range, it was

noted that one of the three reds had a rather different curve from the

other two; this was a difference between different manufacturers. The

two browns, from the same manufacturer, have different curve shapes.

These curve shape differentials may cause variations in the way the

respective colors shift as a function of being viewed under different

light sources.

It would seem that a goal for a practical specification and test method

would be one that could be performed either in the laboratory or in the

field, using the same instrumentation and dedicated light source. Such a

test method, when used in the field, should be such that it can be

performed with vehicle-mounted equipment by personnel with a minimum of

training. The cost of instrumentation and light source can be limited to

about $8,000 so that it might be feasible for a spectrum of different

government agencies.

A2 . Field Measurements

The principal literature source on color measurement of retroreflectors

under nighttime conditions is the paper by Rennilson (1980) in which he

described the results of spectroradiometric measurements made under

laboratory conditions which included four different observation angles

and four different entrance angles, a total matrix of 16 different

conditions. Rennilson' s reference point was the 0.2° observation angle

and -4° entrance angle which is a standard geometry used in the

evaluation of highway sign materials for intensity of retroref lected

light. With this geometry as the zero point he computed chromaticity

differences from it for the other fifteen geometric conditions.

Rennilson' s study showed that for observation angles up to 0.5° and

entrance angles up to 15° the chromaticity differences were minor.

However, for the next incremental increase in angular deviation, to 1.0°

observation and 30° entrance angles, chromaticity differences increased

to an important degree.

The Manual on Uniform Traffic Control Devices (1978, rev. 1986) states

that highway signs should have the same apparent color day and night.

83
This is naive in view of abundant information to the contrary with

respect to the appearance of colors under a variety of light sources

(Collins et al . , 1986). Color rendition of light sources has been

explored in some detail in recent years, and much of this work has

included the specific sources used in highway and highway sign

illumination. The chromaticity shift with change in light source is most

dramatic for more vivid colors, such as highway sign color. At the same

time one can assume that drivers learn the appearance of familiar signs

under various conditions of illumination, minimizing the negative aspects

of these color shifts.

In an unpublished paper by Rennilson and Hale results were reported of

viewing highway sign colors simultaneously under sunlight and CIE

Illuminant A, typical of automotive headlamps. The color shifts were

quite dramatic, and would have been more so had the sunlight been

replaced by any other phase of daylight, which would have been more blue.

As one example, highway blue under Illuminant A is visually closer to

highway green under sunlight, than it is to highway blue under sunlight.

As background for developing a field test method for color measurement of

retroreflective materials, a Minolta CS 100 Luminance Meter was used on

an outdoor photometric range to measure a series of 20 retroreflective

specimens, consisting of 7 examples of high intensity materials and 13

engineering grade specimens.

As background, it was noted that a field test method should have several

requirements

:

1. Be capable of making measurements from a variety of distances, as

opposed to addressing the sample directly, as is usual with

colorimeters and spectrophotometers.

2. Be able to make measurements within an entrance angle spread of +

15° primarily from a vehicle parked at the roadside, with the

minimum necessity to dismount from the vehicle to approach the sign.

3. Include the use of a telespectroradiometer or telecolorimeter

combined with a high intensity light source representative of CIE

Illuminant A (2856 K)

.

To develop the field test method the outdoor photometric range used as a

light source, an automobile headlamp at a range of 45 ft (13.7 m) and a specimen holder capable of providing entrance angles from 0 to + 45°,

with a tolerance of + 1°. Light source color temperature was

determined to be 2960 K.

The 12 in by 12 in (0.3 m by 0.3 m) specimens were measured using a

Minolta CS-100 telecolorimeter, with an acceptance aperture of 1°. It

was deployed at a range so that the acceptance angle subtended a circle

Sin (0.2 m) in diameter, just under the accessible specimen width (8.5 in

or 0.21 m) at the maximum entrance angle.

84
The CS100 telecolorimeter was positioned within the edge of the incident

light beam so as to minimize the observation angle. Facilities were not

available to accurately determine the observation angle, although it was

designed to be as low as possible and was maintained throughout the

measurements

Selected results from the field measurements are shown in table Al . The

measurements were made at entrance angles of 0, 15, 20, 25, and 30°, with

the data being presented in that sequence. Table Al presents data for

white, red, orange, yellow, blue, green, and brown engineering and high

intensity grade samples. Data for blue, green, and brown samples are

shown in CIELAB, while the data for the other colors are in CIE x,y

because their luminance was too high for the meter to convert the data

into CIELAB. Little change with entrance angle is obvious for these

colors. They are all quite close to the spectrum locus in the CIE 1931

chromaticity diagram. Each color shows a reduction in saturation as the

entrance angle increases. For the 13 engineer grade colors, the same

pattern of color change with entrance angle is apparent as for high

intensity colors. This group includes two blue specimens which behaved

similarly to brown and green.

The field data indicate that increasing entrance angle beyond 15-20°

creates scatter in the measurements for green, blue, and brown samples.

It also confirms that accurate positioning of the light source close to

the receptor is impossible to do with car headlamps and suggests the need

for developing a precision-mounted light source for the telecolorimeter.

Experience with the crude field method was used in writing the following

test method for measuring highway signs.

85
Table A1 . Data obtained for retroreflective red, orange, yellow, blue,

green, and brown samples under field conditions at night with

entrance angles of 0, 15, 20, 25, and 30°.

Engineering Grade High Intensity

Angle Sample Y X y Sample Y X y

0 Red 1 127 0.6525 0.3419 Red 2 97.8 0.6800 0.3168

15 Red 1 116 0.6534 0.3419 Red 2 96.9 0.6812 0.3159

20 Red 1 109 0.6540 0.3414 Red 2 96.7 0.6818 0.3155

25 Red 1 101 0.6551 0.3405 Red 2 96.7 0.6824 0.3149

30 Red 1 093 0.6558 0.3400 Red 2 210.0 0.6780 0.3200

Angle Sample Y X y Sample Y X y

0 Orange 1 273 0.5984 0.3781 Orange 2 369 0.6258 0.3706

15 Orange 1 229 0.6080 0.3766 Orange 2 377 0.6262 0.3706

20 Orange 1 215 0.6091 0.3761 Orange 2 378 0.6257 0.3712

25 Orange 1 202 0.6098 0.3758 Orange 2 372 0.6254 0.3711

30 Orange 1 186 0.6104 0.3757 Orange 2 368 0.6253 0.3717

Angle Sample Y X y Sample Y X y

0 Yellow 1 415 0.5605 0.4330 Yellow 2 680 0.5737 0.4257

15 Yellow 1 363 0.5622 0.4331 Yellow 2 700 0.5740 0.4256

20 Yellow 1 339 0.5628 0.4308 Yellow 2 696 0.5737 0.4259

25 Yellow 1 314 0.5632 0.4303 Yellow 2 683 0.5737 0.4260

30 Yellow 1 290 0.5635 0.4300 Yellow 2 662 0.5741 0.4257

Angle Sample L* a* b* Sample L* a* b*

0 Green 1 95.75 -140.76 65.88 Green 2 114.53 -164.29 64.74

15 Green 1 93.05 -138.23 65.39 Green 2 114.04 -165.15 64.42

20 Green 1 91.47 -136.54 64.39 Green 2 113.61 -165.46 64.03

25 Green 1 88.44 -133.13 63.03 Green 2 112.01 -164.43 63.07

30 Green 1 86.30 -130.79 61.87 Green 2 110.37 -163.11 62.07

Angle Sample L* a* b* Sample L* a* b*

0 Blue 1 60.71 -63.36 -36.40 Blue 2 27.84 7.26 -45.86

15 Blue 1 56.93 -59.98 -36.20 Blue 2 28.45 6.25 -44.74

20 Blue 1 54.10 -56.73 -35.93 Blue 2 28.45 6.04 -44.87

25 Blue 1 52.46 -54.49 -35.70 Blue 2 29.26 6,74 -44.40

30 Blue 1 50.57 -52.18 -35.41 Blue 2 29.66 5.83 -43.96

Angle Sample L* a* b* Sample L* a* b*

0 Brown 1 32.59 18.40 29.60 Brown 2 33.58 14.12 23.97

15 Brown 1 32.39 17.94 29.57 Brown 2 36.19 13.12 20.50

20 Brown 1 30.75 17.70 29.71 Brown 2 33.43 13.69 25.31

25 Brown 1 31.85 16.04 27.80 Brown 2 33.15 14.39 25.08

30 Brown 1 31.11 16.62 26.30 Brown 2 33.77 12.81 25.70

86
A3. Test Method for Color Measurement of Retroreflective Highway Signs

Under Nighttime Illumination

A3 . 1

Introduction

Highway signs are produced in a variety of colors as specified by the

Federal Highway Administration. Safety considerations dictate that such

specifications contain minimum requirements. In order to determine if

new and existing signs meet such requirements, it is necessary to provide

a standard test method.

A3 .

Scope

A3 . 2 .

This test method is applicable to all types of retroreflective

materials approved for highway sign usage. Its purpose is to

permit the user to determine when environmental conditions,

damage or other factors have rendered the sign unsafe for its

intended purpose, as well as to evaluate new materials.

A3 .

Applicable Documents

A3 . 3 .Manual on Uniform Traffic Control Devices (MUTCD) , Revision No.

4 March 1986.

A3. 3.

ASTM Standards 10 . A3 . 3 . 2 .

E284 Standard Definitions of Terms Relating to

Appearance of Materials.

A3 . 3 . 2 .

E808 Standard Practice for Describing Retroreflection

A3 . 3 . 2 .E811 Standard Practice for Measuring Colorimetric

Characteristics of Retroreflectors under Nighttime

Conditions

A3. 4. Terminology

A3 . 4 . 1 See A3 . 3 . 2 . 1 , A3 . 3 . 2 . 2 and A3 . 3 . 2 .

above

A3 . 5Summary of Test Method

A3 . 5 .

Color Measurements are made with a telecolorimeter having a

1° acceptance angle, at a variety of ranges so that the work

can be accomplished with maximum speed and safety, during

hours of darkness

A3 . 5 .With the telecolorimeter is a high intensity light source

representing CIE Illuminant A, with a color temperature of

2856 + 25 K, providing an observation angle of 0.33° as

currently specified by the CIE.

10ASTM standards are available from ASTM, 1903 Race St.

Philadelphia, PA 19003.

87
A3 . 5 .

3

Measurements shall be made so that the entrance angle does

not exceed 15°. (Further research is needed to confirm that

there is minimal scatter in chromaticity measurements up to

entrance angles of 15°).

A3. 5.

4

The beam spread of the light source shall be such that at the

minimum range of 3 m (9.8 ft), it covers a 127 mm (5 in)

diameter circle, which will increase in diameter as the range

increases. This permits the color of highway signs which are

ordinarily small (Stop, Curve, Warning, Speed Limit, etc.) to

be measured at close range while excluding the legend from

the measurement area. The procedure will also permit those

signs (directional guide signs, route markers, etc.) which

are usually large and often somewhat inaccessible to be

measured at a greater range. The intent here is to measure

the various types of signs at the ranges at which they are

readily accessible, and at which the instrument's acceptance

angle will subtend an uninterrupted circle of a size that

will be available on that type of sign.

A3 . 5 .

5

Procedures for measuring specular gloss are given in ASTM

D523. It is not appropriate to measure gloss as part of this

test method.

A3 . 6

.

Significance and Use

A3 . 6 .

1

Highway signs are color coded, with the background color

indicating the sign's function, such as regulatory, warning

and guidance to locations or intersecting roads, and location

of off-highway facilities such as fuel and food. In order

for the signs to be differentiated from a variety of

backgrounds, and then identified as to color, and therefore

function, it is necessary that their color remain

sufficiently vivid (saturated) as to be conspicuous.

A3 . 6 .

2

Specifications for highway sign materials include standard

LS-300C which provides a specification for the color in

daylight, along with a test method. This document provides a

test method for determining color at night, and can be used

to determine when the sign must be replaced because it no

longer meets minimum standards for conspicuity during hours

of darkness.

A3 . 7

.

Apparatus

A3 . 7 .

1

Telecolorimeter. This is a tristimulus colorimeter capable

of measuring reflecting materials and self-luminous material

at ranges from 3.5 m (11.5 ft) to infinity. It must have

acceptance angles between 0.5° and 1.5° in order to measure

sign specimens of the appropriate size over the range of

interest

.

88
A3 . 7 . 2 Light Source. The light source shall be tungsten and shall

have a color temperature of 2856 + 25 K, equivalent to CIE

Illuminant A. It shall have intensity and beam spread

characteristics appropriate to the task.

A3 . 7 .

The observation angle between light source and

telecolorimeter shall be 0.333°^. The light source may be

built into the telecolorimeter or attached to it by

mechanical means, or subject to any other arrangement so long

as all of the above requirements are met.

A3 . 8 . Test Specimens

Signs are to be measured in place and are not to be cleaned or

otherwise prepared for examination. The instrument- light source

combination is meant to be brought to the sign in such a manner that

it addresses the sign within the permissible range and entrance

angle

A3 . 9Calibration and Standardization

A3 . 9 .The light source shall be calibrated to meet the requirements

of section A3 . 7 . 2 . (See Wyszecki and Stiles, 1982). The

calibration should be checked prior to each use of the

apparatus. Note that the telecolorimeter, with a suitable

dedicated computer, can be used for testing the light source.

A3 . 9 .The telecolorimeter shall be calibrated in the following

manner. Select the local reference standard of the same

nominal color as the specimen to be measured. Activate light

source- instrument combination and follow instrument

manufacturer's instructions for calibration with local color

standard. The reference standard has been calibrated

spectroradiometrically for a 0.33° observation angle and 0°

entrance angle. These geometric conditions should be set

with respect to instrument and specimen.

A3 . 9 .Reference standards for telecolorimeter calibration are

available as noted below.

1 1 ‘‘The 0.33° observation angle in A3 . 7 .

was selected to conform with

the document being written by CIE Committee 2-9 for nighttime measurement

of these materials by spectroradiometry

^Calibrated reference standards are available from Hale Color

Consultants, Inc., 1505 Phoenix Rd.

Phoenix, MD 21131.

89
A3 .10. Report will include:

A3 . 10.1 Name, serial number and manufacturer of telecolorimeter

and light source.

A3. 10.2 Source and calibration information for calibration

standards

.

A3. 10.3 CIE Y, x, y and CIELAB L*, a*, b* data for CIE Iliuminant

A, for each specimen.

A3. 10.4 Measurement range (estimated).

A3. 11. Precision and Bias

A3. 11.1 Precision and bias data are being developed for this test

method.

90
A4.1 Future Research on Use of Degraded Signs and Evaluation of Day-Night

Color and Gloss

A4.1.1 Degraded Signs

If highway signs were made from paint or similar materials, with

conventional reflection properties, there is little question that a good

correlation could be found between day and night color, thus permitting

the measurements to be made during daylight. Daylight measurements can

be made more quickly, under safer conditions, and at lower costs.

It is the singular geometric reflection properties of retroreflective

materials that cause the important differences between both their light

reflection characteristics and their color between daytime and nighttime.

And it is the degradation with age and weathering of such properties that

one would wish to evaluate. Thus even if a useful correlation could be

determined between day and night appearance of new materials, such as

those used in the current study, there is no guarantee that this

correlation would be true for the very type of degraded material that

should be evaluated. While there is merit in being able to measure the

color of retroreflective material for both day and night appearance, it

is probable that the more important factor for evaluation is the

appearance of this same material when it has deteriorated near the point

where it may be necessary to replace it. This should be the subject of a

separate study. Some of the techniques employed in the present study

will be useful in such further research.

A4.1.2 Gloss Specification for Retroreflective Signs

Current specifications for evaluation of gloss specify the use of ASTM D

523 Standard Test Method for Specular Gloss, using 85° geometry.

However, this method includes three separate geometries, 20, 60 and 85°,

and specifies that 60° geometry is to be used for most specimens. It

continues to specify that if 60° gloss is higher than 70 units, then the

20° geometry is to be employed. Similarly, D 523 notes that when 60°

gloss is less than 10 units, 85° geometry should be used.

It has long been known that none of these geometries are linear with

visual gloss appraisal. Specifically, the 60° geometry scale is

compressed at both the high and low gloss ends, so that large visual

gloss differences measure as very little different; on the other hand,

the 60° geometry is usually quite adequate between 10 and 70 gloss units.

Similarly, the 20 and 85° geometry have an expanded scale in the high and

low gloss regions, respectively, and compressed scales in other regions.

The literature search has disclosed no references to explain the use of

85° geometry for high gloss retroreflective sheeting, when D 523

specifies 20° gloss for such specimens. However, a leading researcher at

one of the manufacturers suggests that 20° geometry has been tried, and

rejected because at this angle some of the incident light penetrates the

first surface and is retroreflected within the acceptance cone of the

91
gloss measuring instrument, adding to the specular beam and resulting in

a false reading.

Inasmuch as the 85° gloss scale is importantly compressed for high gloss

specimens, one must be careful in setting minimum values for new

material. A study is indicated where all current materials are employed,

as different types of first surface plastic sheeting are employed within

the industry. Consideration should be given to 60° and 85° geometry, as

well as other geometries. It might also be useful to consider other

types of gloss evaluation, such as distinctness of image gloss as well as

to reappraise the requirement for a gloss specification.

While new materials have a high gloss finish, outdoor aging results in

deterioration of both gloss and color. For new materials the 45/0

geometry specified for color measurement probably excludes the specular

beam completely or almost so, permitting color and gloss to be separately

measured. It is also quite possible that a sphere instrument with a

light trap for excluding the specular component would work as well for

the color measurement of new material. The 45/0 geometry is that which

has historically been used in tristimulus colorimeters, the usual

instrument employed with retroreflective material, and the wide

availability of these instruments (which have a lower cost than a

spectrophotometer) is a good reason for specifying this geometry.

As retroreflective sheeting deteriorates under environmental conditions,

the high gloss surface gradually assumes a lower gloss. At some point in

this degradation, the specularly reflected beam may encompass such a wide

angle that some portion of it falls within the acceptance cone for color

measurement. It will then interfere with the color measurement, adding

unmodified reflected light, amount unknown, to the chromatic

characteristics of the specimen.

It thus appears that the entire matter of gloss behavior and its

evaluation should be the subject of further study. It needs to be

positively determined if it is necessary to evaluate gloss of both new

and old materials; and if so, how this should be done.

A4 . 1 . 3 Future Research on Nighttime Color Measurement Using a Telecolorimeter

While it has been determined that the telecolorimeter used in this

experiment, the Minolta CS-100, is quite capable of making accurate and

repeatable colorimetric measurement of retroreflective materials, it was

not possible to calibrate it satisfactorily for measurements made at the

range of entrance angles necessary for evaluation of highway signs at

night

.

It would be necessary to make extensive measurements by spectroradiometry

of the full range of retroreflective materials, at a variety of entrance

angles up to 30°, to select a series of calibration standards against

which the instrument would be calibrated. It is likely that such a set

of reference standards would be samples of retroref lective sheeting

92
of reference standards would be samples of retroreflective sheeting

previously calibrated on a spectroradiometer

If the above experimental work determined that the telecolorimeter

response did not change importantly over an entrance angle range from 0

to 15 or 20°, it would then seem possible that a standard and test method

could be successfully written and employed for nighttime color

measurement in the field. The range of entrance angles must be wide

enough that field measurements could be confined to this range by a

visual determination, and without reducing personnel safety or increasing

time and difficulty of field measurement.

The CS-100 is currently calibrated using a white porcelain panel, for

45/0 geometry. However, as E XXXX^ specifies that colorimetric

measurement of retroreflective sheeting should employ chromatic

calibration standards which are themselves retroreflective , it is

believed this approach would produce more accurate results.

^E XXXX is the new ASTM E-12 Committee draft standard on

Photoelectric Tristimulus Measurement of Object Colors, currently up for

ASTM society ballot after approval by Committee E-12. It is referenced

in the new draft specification for daytime measurement of highway sign

material recently approved by task group of ASTM Committee D04.38 on

Traffic Control Devices, which is intended to replace LS-300c.

93
A5 . Preliminary Recommendations on Highway Color Specifications

Would minor shifts in the highway color specifications enhance or degrade

the observer's ability to discriminate these colors, or to identify them

correctly under various light sources? Collins et al „ (1986) showed that

some sources tend to obscure the hue differences between colors adjacent

to each other in color space, in the sequence red, orange, yellow, green,

blue. However, while the first three of these hues are rather close to

each other, the last two are more distant from the initial three, and

from each other. This visual spacing as specified under daylight (CIE

Illuminant C) directly relates to their visual spacing under other

sources

.

The original highway colors, red, yellow, green, blue and white, were

formally specified some thirty years ago. The hue spacing of the four

chromatic colors was certainly adequate, as was the contrast of these

background colors with white and black used for legends. Red, green and

blue were quite dark and contrasted well with white. Yellow, a light

color, contrasted well with black.

When the FHWA recognized the need for additional sign colors, it proposed

a vivid orange for highway construction sites, and a brown for parks,

historic sites and similar locations. About this same time a purple

color was tested in several locations; it was soon apparent that pigments

available for purple color in signs did not have the requisite outdoor

ageing characteristics needed for this application.

While pigment characteristics were not a problem for orange and brown,

color spacing was. Both of these had to be placed in the available space

between red and yellow. Orange was located midway between these two

colors, and appropriate tolerances set to define the "color boxes" in CIE

x,y space; color tolerance charts were designed to provide visual

interpretation of these tolerances, as had been done for the original

colors. The same applied to brown, which was specified sufficiently dark

so as not be confused with orange which occupies the same hue region.

A further problem with orange is that in vivid form it falls closer to

the center of the lightness range between black and white than did any of

the original four chromatic colors. Because contrast and legibility are

largely a function of lightness contrast, less contrast is achievable

between legend and surround with orange than with the other colors.

If color boundaries are shifted slightly to improve hue spacing, are

pigments available with the necessary aging characteristics, especially

in the more critical red, orange, yellow hue region? Manufacturers of

retroreflective sheeting are understandably reticent to disclose

proprietary data, or the results of their research with pigments

necessary to produce other colors. However, any color shifts proposed

would certainly be of modest magnitude, and time for necessary research

and testing could be allowed. Improvements in correlation between

accelerated testing and real-time aging serve to shrink the time -frame

for such work. Where colors are now the product of two chromatic

94
pigments, the hue shift proposed may be so minor that these same pigments

could still be used, but in different ratios. Manufacture of highway

sign materials is now highly competitive; this will be an incentive for

rapid response to proposed new colors.

1.

Table A2 contains Munsell specifications for the daylight color of

both the ANSI and FHWA colors. The recommendations for switching to

the ANSI specifications are partly based upon the data obtained by

Collins et al. and the author's extensive experience in this field.

Although it is desirable that they be subjected to suitable

experimental investigation under retroreflective viewing conditions,

the following points are pertinent.

A. The table below shows, in Munsell hue steps, the spacing

between adjacent hues in the existing FHWA and ANSI Z53.1

standards

Adiacent Colors FHWA Z53 . Red to Orange 3.25 5.25

Orange to Yellow 4.75 7.25

Yellow to Green 23.0 18.5

Green to Blue 19.5 19.5

Blue to Red 31.0 32.0

B. To increase the separation between Red, Orange and Yellow:

1. Consider changing Highway orange to the Z53.1 orange,

increasing the red-orange hue spacing from 3.25 steps to

5.75 steps.

2. Also consider switching Highway yellow to the Z53.1

yellow. This would increase the orange-yellow hue spacing

from 4.75 steps to 7.25 steps.

3. Consider the possibility of further research to determine

if colors which are intermediate between the ANSI and

highway specifications might be recognized more

accurately. Such colors were not explicitly evaluated by

Collins et al., although their data suggest that several

other blue, green, and yellow colors could be further

evaluated for highway applications.

C. No color change has been suggested for White or Brown.

95
Table A2 . Munsell notation for FHWA and ANSI Highway Color Centroids and

Tolerances

.

Color FHWA ANSI

RED

Centroid 7. OR 3.5/13 7.5R 4/14

H + 6 . 0 - 8.0 R 6.5 - 8.5 R

V + 3.0 - 4.0 3.5 - 4.5

C + 12.0 - 15.0 12.0 - 16.0

ORANGE

Centroid 2.5YR 5.5/14 5. OYR 6.0/15

H + 1.25 - 3.75 YR 3.75 - 6.25YR

V + 5.0 - 6.0 5.5 - 6.5

C + 12.0 - 15.0 13.0 - 16.0

BROWN

Centroid 5 . OYR 2.75/5 5. OYR 2.75/5

H + 2.5 - 7.0 YR 2.5 - 7.0 YR

V + 2.25 - 3.25 2.25 - 3.25

C + 4.0 - 6.0 4.0 - 6.0

YELLOW

Centroid 10. YR 7.5/14 5.0Y 8.0/12

H + 8. SYR - 2.0 Y 3.5 - 6.54Y

V + 6.5 - 8.0 7.5 - 8.5

C + 12.0 - 16.0 10.0 - 14.0

GREEN

Centroid 7.5G 3.0/8 7.5G 4.0/9

H + 5.0G - 0.5 BG 5 . 0G - 0. 5BG

V + 2.25 - 3.75 3.5 - 4.5

C + 6.0 - 10.0 7.0 - 11.0

BLUE

Centroid 2.5PB 3/8 2.5PB 3.5/10

H + 10B - 5PB 10B - 4. 5PB

V + 2.0 - 3.5 3.0 - 4.0 . c + 6.0 - 10.0 8.0 - 12.0

96
D. Changes in Lightness. Changes of this type impact chiefly on

the contrast of the sign surrounds with the white or black

legends. Recommendations are:

1. Red should be changed from Munsell 3.5 to 4.0 value, to

agree with the lightness range of the Z53.1 Red.

Tolerances would be 3.5 to 4.5.

2. Orange, if changed to the Z53.1 orange, would then have a

lightness of 6.0 value, instead of 5.5/, which will

improve its contrast with its black legend. Where orange

is contrasted with white, as in construction barricades,

consideration should be given to retaining a lightness of

5.5.

3. Yellow should increase in lightness from 7.5 to 8.0, to

agree with the Z53.1 Yellow. The existing yellow

lightness minimum is at 6.5 value, which is quite dark. A

lightness range with a 7.0 value minimum would seem more

suitable. No light limit specification is necessary or

desirable

4. Green and blue have very dark lightness minima, as well as

dark specifications for their centroid colors. Both

colors should have their centroids lightened by 0 . 5 value

steps, at 3.5, with light and dark tolerances at 4.0 and

3.0.

E. Changes in Saturation. If saturation increases are feasible

for retroreflective materials , experiments should be performed

to determine if such increases would improve visibility and

legibility

2. Appendix B shows CIELAB data for the existing FHWA colors in tabular

form for the corner points of the color boxes, and the range of

lightness, in CIELAB L* , a*, b* form, for the CIE 1976 2° Observer

with data computed for CIE Illuminant C. The table is difficult to

use, however, because extensive interpolation is needed between the

light and dark levels for the corner boxes in CIELAB. Further work

is needed to define usable color boxes in CIELAB. Although ASTM

D3134 provides CIELAB tolerances, it is in the process of being

revised so that it is premature to express tolerances in D-3134

format until such tolerances have been determined to be firmer.

97
Appendix B. CIE x,y and CIELAB specifications for Highway Colors

Color X

White 1 0.305 0 . White 2 0.350 0 . White 3 0.321 0 . White 4 0.276 0 . Red 1 Dark 0.602 0 . Red 1 Light 0.602 0 . Red 2 Dark 0.664 0 . Red 2 Light 0.664 0 . Red 3 Dark 0.644 0 . Red 3 Light 0.644 0 . Red 4 Dark 0.575 0 . Red 4 Light 0.575 0 . Orange 1 Dark 0.535 0 . Orange 1 Light 0.535 0 . Orange 2 Dark 0.607 0 . Orange 2 Light 0.607 0 . Orange 3 Dark 0.582 0 . Orange 3 Light 0.582 0 . Orange 4 Dark 0.535 0 . Orange 4 Light 0.535 0 . Brown 1 Dark 0.445 0 , Brown 1 Light 0.445 0 . Brown 2 Dark 0.604 0 . Brown 2 Light 0 . 604 0 . Brown 3 Dark 0.556 0 . Brown 3 Light 0.556 0 . Brown 4 Dark 0.445 0 . Brown 4 Light 0.445 0 . Yellow 1 Dark 0.482 0 . Yellow 1 Light 0.482 0 . Yellow 2 Dark 0.532 0 . Yellow 2 Light 0.532 0 . Yellow 3 Dark 0.505 0 . Yellow 3 Light 0.505 0 . Yellow 4 Dark 0.475 0 . Yellow 4 Light 0.475 0 . Green 1 Dark 0.130 0 . Green 1 Light 0.130 0 . Green 2 Dark 0.180 0 . Green 2 Light 0.180 0 . Green 3 Dark 0.155 0 . Green 3 Light 0.155 0 . Green 4 Dark 0.107 0 . Green 4 Light 0.107 0 . Blue 1 Dark 0.147 0 . Blue 1 Light 0.147 0 . Blue 2 Dark 0.176 0 . Blue 2 Light 0.176 0 . Blue 3 Dark 0.176 0 . Blue 3 Light 0.176 0 . Blue 4 Dark 0.106 0 . Blue 4 Light 0.106 0 .

Y L* a* b*

35 65.75 8.31 -8.05

35 65.75 5.04 12.22

35 65.75 -11.32 13.17

35 65.75 -10.44 -6.40

8 33.98 53.09 34.46

12 41.22 60.77 39.45

8 33.98 56.68 58.59

12 41.22 64.88 71.06

8 33.98 48.78 58.59

12 41.22 55.84 71.06

8 33.98 38.98 39.01

12 41.22 44.62 44.66

18 49.50 37.57 46.56

30 61.65 44 . 54 55.20

18 49.50 46.15 85.34

30 61.65 54.71 106.30

18 49.50 35.24 84.77

30 61.65 41.78 105.35

18 49.50 31.02 54.30

30 61.65 36.78 64.38

4 23.67 14.93 14.70

9 35.98 19.56 19.26

4 23.67 27.12 40.81

9 35.98 35.54 62.04

4 23.67 14.65 40.69

9 35.98 19.20 61.77

4 23.67 9.47 19.28

9 35.98 12.41 25.26

29 60.78 9.87 65.70

45 72.89 11.43 76.06

29 60.78 17.44 102.33

45 72.89 20.19 121.85

29 60.78 4.61 104.02

45 72.89 5.34 124.48

29 60.78 -0.04 77.86

45 72.89 -0.04 90.14

3.5 21.94 -47.29 -3.09

9 35.98 -64.78 - -4.23

3.5 21.94 -36.44 1.61

9 35.98 -49.93 2.20

3.5 21.94 -49.00 7.11

9 35.98 -67.13 9.75

3.5 21.94 -60.72 2.85

9 35.98 -83.19 3.91

1 8.99 27.97 -45.78

4 23.67 44.39 -72.68

1 8.99 27.37 -38.60

4 23.67 43.44 -61.27

1 8.99 6.38 -23.97

4 23.67 10.13 -38.05

1 8.99 -1.58 -34.53

4 23.67 -2.52 -54.82

y

290

342

361

308

317

317

336

336

356

356

356

356

375

375

393

393

417

417

399

399

353

353

396

396

443

443

386

386

450

450

465

465

494

494

485

485

369

369

391

391

460

460

439

439

075

075

091

091

151

151

113

113

98
Appendix C. Definitions

Definitions have been adopted from ASTM E284 as reprinted in ASTM Standards

on Color and Appearance Measurement . 2nd Ed, 1987, except where noted.

Chromaticity - the color quality of a color stimulus definable by its

chromaticity coordinates, or by its dominant (or complimentary) wavelength

and its purity taken together. (CIE, 1983)

Chromaticity coordinates - the ratios of each of the tristimulus values of a

color to the sum of the tristimulus values. (Chromaticity coordinates in the

CIE system of color specification are designated by x, y, and z and by a*, b*

and L* in the CIELAB system.)

Color - (1) (Perceived) attribute of visual perception that can be described

by color names such as white, gray, black, yellow, brown, vivid red, deep

reddish purple, or by combinations of such names.

Note 1 - Perceived color depends greatly on the spectral power

distribution of the color stimulus, but also on the size, shape,

structure, and surround of the stimulus area, the state of adaptation of

the observer's visual system, and the observer's experience with similar

observations

(2) (psychophysical) characteristics of a color stimulus (that is, light

producing a sensation of color) denoted by a colorimetric specification with

three values, such as tristimulus values.

Note 1 - Tristimulus values are sometimes derived on a relative rather

than an absolute basis. In this case they may need to be supplemented

by the value of a suitable absolute photometric quantity.

Note 2 - The appearance of colors depends not only on their absolute

tristimulus values, but also on the conditions under which they are

viewed, including the nature of the surround; however, colors having the

same absolute tristimulus values appear the same in identical viewing

conditions. Spectrally different color stimuli can have the same

absolute tristimulus values.

Color Difference - (1) Color difference (perceived) , the magnitude and

character of the difference between two colors described in such terms as

redder, bluer, lighter, darker, grayer, or cleaner.

(2) Color difference (computed) , - the magnitude and direction of the

difference between two psychophysical color stimuli and their components

computed from tristimulus values, or chromaticity coordinates and luminance

factor, by means of a specified set of color-difference equations.

Colorimeter, tristimulus - Instrument that measures color, in terms of

tristimulus values, often by the use of filters to convert the relative

spectral power distribution of the illuminating source to that of a standard

illuminant, and to convert the relative spectral sensitivity of the sensor to

sensitivities prescribed by a standard observer.

Colorimetry - The science of color measurement.

Color space - A geometric space, usually of three dimensions in which colors

are arranged systematically.

99
Color temperature - Of a source, the temperature usually expressed in

kelvins, of a full radiator that would emit light of the same chromaticity as

the source.

Contrast - (objective) - the degree of dissimilarity of a measured quantity

such as luminance of two areas, expressed as number computed by a specified

formula such as C = L-2 - Lq / Lq .

Footcandle (fc) - The unit of illuminance when the foot is taken as the unit

of length. It is the illuminance on a surface one square foot in area on

which there is a uniformly distributed flux of one lumen, or the illuminance

produced on a surface all points of which are at a distance of one foot from

a directionally uniform point source of one candela. (IESNA, 1984)

Goniophotometer - Instrument that measures luminous flux as a function of

angles of incidence or propagation.

Hue - The attribute of color perception by means of which a color is judged

to be red, orange, yellow, green., blue, purple, or intermediate between

adjacent pairs of these considered in a closed ring (red purple being an

adjacent pair).

Illuminance - Luminous flux incident per unit of area.

Lightness - (1) the attribute of color perception by which a non- selfluminous body is judged to reflect more or less light. (2) The attribute by

which a perceived color is judged to be equivalent to one of a series of

grays ranging from black to white.

Luminance - Luminous flux in a beam, emanating from a surface, or falling on

a surface, in a given direction, per unit of projected area of the surface as

viewed from that direction, per unit solid angle.

Photometer - an instrument for measuring light.

Retroreflection - Reflection characterized by the flux in an incident beam

being returned in directions close to the direction from which it came, this

effect occurring over a wide range of incident angles.

Saturation - Attribute of a visual sensation according to which an area

appears to exhibit more or less chromatic color, judged in proportion to its

lightness or brightness.

Trans illuminated signs - intended to be viewed by both daylight and by

supplementary artificial illumination. "The materials used for the surfaces

of transilluminated signs exhibit properties partially of transmission and

partially of diffuse reflection. By day they are commonly seen by reflected

daylight; but they may also be illuminated artificially by transmitted light,

so as to make them visible by night or to enhance their visibility under poor

daylight conditions. The color perceived is dependent on the color of the

illuminant under the conditions of observation. In addition, particularly in

the case of internally colored materials, there may be difference in color

depending on whether the light is transmitted or reflected" (CIE, 1983, p2-

3).

100
NBS-114A tREv. 2-80

U.S. DEPT. OF COMM.

4.

BIBLIOGRAPHIC DATA

SHEET (See instructions)

TITLE AND SUBTITLE

PUBLICATION OR

REPORT NO.

NISTIR 88-3894

2 . Performing Organ. Report NoJ 3. Publ i cation Date

NOVEMBER 1988

Evaluation of Colors for Use on Traffic Control Devices

5. AUTHOR(S)

6. PERFORMING ORGANIZATION (If joint or other than NBS, see instructions) 7. Contract/Grant No.

NATIONAL BUREAU OF STANDARDS

U.S. DEPARTMENT OF COMMERCE S. Type of Report & Period Covered

GAITHERSBURG, MD 20899

9. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (Street. City. State. ZIP)

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101

10. SUPPLEMENTARY NOTES

T Document describes a computer program; SF-185, FIPS Software Summary, is attached.

11. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant

bi bl iography or literature survey, mention it here)

Color has traditionally been used to code safety information because of its ability

to attract attention and evoke a rapid response. In the present report, research on

color coding, highway safety color codes, color deficiency, retroref lective materials,

and conspicuity, is reviewed to evaluate the effectiveness of chromaticity specifications for highway signs and markings. The current highway specifications are typically

for colors of medium lightness and saturation, and sometimes can appear quite dark.

Data from a study by Collins et al (1986) are reanalyzed to compare color appearance

data for both ANSI and highway colors viewed under seven illuminants, including several

HID sources. The analysis demonstrated that the ANSI colors, expecially safety yellow,

were identified more accurately in terms of color name, lightness, saturation, and

primary hue than the corresponding highway color. In addition, selected measurements

of the chromaticity of retroref lective materials were made as background for assessing

the feasibility of developing a nighttime chromaticity specification. Based on the

analysis of the appearance of safety colors under different illuminants, it is recommended that consideration be given to switching the FHWA specifications for the chromaticity of colors used on traffic control devices to the ANSI specifications.

12. KEY WORDS (Six to twelve entries; alphabetical order; capitalize only proper names; and separate key words by semicolon s) Chromaticity, CIELAB, color, color code, color vision, color defects, conspicuity,

highway, safety, retroref lectivity

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