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Publication Number: FHWA-RD-98-057

Human Factors Design Guidelines for Advanced Traveler Information Systems (ATIS)and Commercial Vehicle Operations (CVO)

 

CHAPTER 3: GENERAL GUIDELINES FOR ADVANCED TRAVELER INFORMATION SYSTEM (ATIS) DISPLAYS

 

SELECTION OF COLORS FOR CODING VISUAL DISPLAYS

Introduction: Selection of colors for coding visual displays refers to the use of different colors either to bring information to the attention of a driver, or to aid the driver in distinguishing between items on a display. Color coding may be used to make absolute or relative discriminations, and should be used in a way that is redundant with other coding dimensions (e.g., shape, size, brightness).

Design Guidelines***

When either absolute or relative discriminations are required, the following Commission Internationale de l'Eclairage (CIE) color set should be used to achieve maximum discrimination.

Recommended CIE Color Set for Maximum Discrimination

 

SATURATED SET

DESATURATED SET

COLOR NAME

U'

V'

U'

V'

RED

0.4161

0.5285

0.3819

0.5112

GREEN

0.1206

0.5613

0.1462

0.5546

BLUE

0.1724

0.1681

0.1594

0.2679

ORANGE

0.3347

0.5119

0.2794

0.4998

YELLOW

0.2023

0.5204

0.2023

0.5204

LIGHT BLUE

0.1590

0.3052

0.1600

0.3800

PINK

0.2595

0.3079

0.2500

0.3700

WHITE

0.1978

0.4684

0.1978

0.4684

 

Supporting Rationale: A set of seven colors (plus white) that are maximally discriminable has been identified (Reference 1). Reference 1 also identified a more subdued set of colors that are highly discriminable. The names of the colors and the CIE 1976 Uniform Chromaticity–Scale (UCS) units for both the saturated and desaturated color sets are given above. Either of these color sets is suitable for use in situations where absolute or relative discriminations are required. Research has shown that color coding reduces both the time required to make discriminations and the number of errors, particularly on dense displays (Reference 2). Analysis of an in–vehicle navigation system showed that differences in traffic congestion were more easily discriminated when color coded than when coded using varying line widths (Reference 3). Reference 3 also found that color coding of the recommended route was considered helpful by drivers when using other, comparable systems. Additionally, they report that color coding is useful to distinguish between portions of a route already completed and the portion remaining to the destination.

Special Design Considerations: (1) Approximately 8 percent of the population, mostly males, does not have normal color vision, and color deficient vision does not disqualify an individual from driving. Therefore, when critical information must be presented to drivers, color coding should be redundant with other coding (e.g., shape coding). (2) The ability to perceive and distinguish colors is mediated by the cones in the retina. Therefore, the ability to discriminate colors is reduced in twilight and full nighttime conditions compared to daytime conditions. In the guidelines above, both saturated and desaturated color sets are provided, to reflect different approaches that ATIS designers might take regarding the use of color.

Cross References:

Symbol Color

Use of Color Coding

Color Contrast

Color Coding of Traffic Flow Information

Key References:

    1. Boff, K. R., & Lincoln, J. E. (Eds.). (1988). Engineering data compendium: Human perception and performance. Wright–Patterson Air Force Base, OH: Armstrong Aerospace Medical Research Laboratory.

    2. Clarke, D. L., McCauley, M. E., Sharkey, T. J., Dingus, T. A., & Lee, J. D. (1996). Development of human factors guidelines for advanced traveler information systems and commercial vehicle operations: Comparable systems analysis. Washington, DC: Federal Highway Administration (FHWA–RD–95–197).

    3. Hennessy, R. T., Hutchins, C. W., & Cicinelli, J. G. (1990). Color requirements for the E–2C enhanced main display unit (EMDU) (Final Report No. N00019–89–C–0174). Washington, DC: Naval Air Systems Command.

*Primarily expert judgement
**Expert judgement with supporting empirical data
***Empirical data with supporting expert judgement
****Primarily empirical data

 

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USE OF COLOR CODING

Introduction: Color coding refers to the use of chromaticity to differentially identify items in a display systematically. The categories used to color code objects on a display depend upon the tasks required of the operators.

Design Guidelines***

Design Guidelines for the use of color include:

  • The number of colors used to code information should be kept to a minimum, not to exceed 4 colors for casual users and 7 colors for experienced, long term ATIS/CVO users.

  • Do not violate population expectations regarding use of color. Several examples of population stereotypes are:

    • - Red: indicates Stop, Warning, System Operating Out of Tolerance

    • - Yellow: indicates Caution

    • - Green: indicates Go Ahead, System Operating Within Tolerance

  • Color codes should be applied consistently throughout the system; colors should have the same meaning on each screen that the system can display.

  • As the number of colors used is increased, the size of color coded objects should be increased.

  • Use compatible color combinations when colors are presented simultaneously. Avoid red/green, blue/yellow, green/blue, and red/blue pairs unless an attempt is being made to make different parts of the screen appear in different planes.

 

Schematic Example of the Use of Color Coding

Schematic Example of the Use of Color Coding

Important Note: The map display depicted above is provided solely to augment this Design Guideline by illustrating general design principles. It may not be suitable for your immediate application without modification.

Supporting Rationale: These guidelines represent a collection of guidelines from the human factors literature as presented in References 1–4.

Special Design Considerations: (1) Approximately 8 percent of the population, mostly males, does not have normal color vision, and color deficient vision does not disqualify an individual from driving. The most common deficiency is an inability to distinguish between red and green. Therefore, when critical information must be presented to drivers, color coding should be redundant with other coding (e.g., shape coding). (2) The ability to discriminate colors is reduced in twilight and full nighttime conditions compared to daytime conditions.

Cross References:

Symbol Color

Selection of Colors for Coding Visual Displays

Color Contrast

Color Coding of Traffic Flow Information

Key References:

    1. Durrett, H. J. (1987). Color and the computer. San Diego, CA: Academic Press.

    2. Hennessy, R. T., Hutchins, C. W., & Cicinelli, J. G. (1990). Color requirements for the E–2C enhanced main display unit (EMDU) (Final Report, Contract No. N00019–89–C–0174). Washington, DC: Naval Air Systems Command.

    3. Sanders, M. S., & McCormick, E. J. (1993). Human factors in engineering and design (5th ed.). New York: McGraw–Hill.

    4. MIL–STD–1472D. (1989). Human engineering design criteria for military systems, equipment and facilities. Washington, DC: U.S. Government Printing Office.

*Primarily expert judgement
**Expert judgement with supporting empirical data
***Empirical data with supporting expert judgement
****Primarily empirical data

 

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COLOR CONTRAST

Introduction: Color contrast refers to the relationship between symbol and background associated with chromatic differences such as hue and saturation. Determining the amount of contrast provided to the driver becomes a more complex problem when the symbology and/or the background are colored.

Design Guidelines***

Colored symbols should differ from their colored backgrounds by a minimum of 100DE (CIE Yu'v') distances.

 

Equation for Determining Color Contrast

Equation for Determining Color Contrast

 

NOTE: Reference 1 states, "The discriminability of pairs of colors depends on their differences in chrominance and luminance. While an entirely satisfactory metric does not exist which combines these attributes into a single assessment of total color difference, an estimate can be derived by calculating the weighted difference between the locations of the colors in the 1976 CIE UCS (CIE UCS L*u*v*)."

"Note that this estimate should be used only to ensure discriminability of colors of relatively high luminance. Severe nonlinearities in the UCS limit the usefulness of this metric for colors having small luminance differences. In addition, the specification of small color differences should be treated with caution due to the inherent lack of color uniformity on most CRTs."

Supporting Rationale: The interested reader is referred to Reference 2 or Reference 1 for a review of both color contrast issues and the research that has been done in this area (see also References 3 and 4). In brief, color contrast research has been aimed at developing a measure of color contrast that can be related to human visual functioning. Such research has attempted to develop a UCS (i.e., one in which equal distances on a color diagram correspond to equal perceptions regarding color differences, where the color difference within a UCS is used to indicate the magnitude of color contrast). The measure of color contrast (or difference) is then correlated with human performance (Reference 2). Reference 1 has provided a metric for determining symbol colors to maximize legibility for symbols of relatively high luminance. This metric, DE (CIE Yu'v'), which is shown in the figure, is derived from the 1976 CIE UCS color diagram (CIE UCS). Although the metric does not combine the different attributes of color into a single assessment of total color difference, it provides a useful estimate of color contrast.

Reference 1 indicates that for legibility of colored symbols on a colored background (with relatively high luminance conditions), the colors should differ by a minimum of 100DE (CIE Yu'v') distances. If the formula is applied to figures and background that differ negligibly in u' and v', this value corresponds to approximately 80 percent luminance contrast, which is rather high in comparison with traditional contrast recommendations. Specific applications may be able to use less than 100DE (CIE Yu'v') distances.

Special Design Considerations: Although DE (CIE Yu'v') provides a seemingly adequate measure of color contrast, it is clear that much more research is needed in this area before specific recommendations regarding color contrast can be made for automotive applications. Reference 2 notes that different experimental tasks as well as different response measures need to be investigated.

Color contrast is a sufficiently difficult concept when applied to fixed–color, fixed–background displays; it becomes more complex when applied to displays such as automotive HUDs. With HUDs, the background for the symbology is dynamic and can be almost any color; background luminance can range from a fraction of a footlambert to 6,000 or more footlamberts, depending on conditions. In addition, the symbology is translucent, which means that both the background color and luminance combine with the symbology's color and luminance in an additive fashion. Color contrast, therefore, is not a very meaningful parameter when applied to head–up displays.

Cross References:

Symbol Color

Selection of Colors for Coding Visual Displays

Use of Color Coding

Sensory Modality for Presenting ATIS/CVO Messages

Color Coding of Traffic Flow Information

Key References:

    1. American National Standards Institute. (1988). American national standard for human factors engineering of visual display workstations. Santa Monica, CA: Human Factors and Ergonomics Society.

    2. Decker, J. J., Pigion, R. D., & Snyder, H. L. (1987). A literature review and experimental plan for research on the display of information on matrix–addressable displays. Blacksburg, VA: Human Engineering Laboratory, VPI & SU.

    3. Post, D. L., Costanza, E. B., & Lippert, T. M. (1982). Expressions of color contrast as equivalent achromatic contrast. Proceedings of the Human Factors and Ergonomics Society 26th Annual Meeting, (pp. 581–585). Santa Monica, CA: Human Factors and Ergonomics Society.

    4. Post, D. L., & Snyder, H. L. (1986). Color contrast metrics for complex images. Blacksburg, VA: Human Factors Laboratory, VPI & SU (DTIC No. AD–A174960).

*Primarily expert judgement
**Expert judgement with supporting empirical data
***Empirical data with supporting expert judgement
****Primarily empirical data

 

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FHWA-RD-98-057

 

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