111721 TA2018001 BOS REPORT_PART8.PDF

Table 3. Summary of luminance (cdW) 
and contrast (Weber ratio) measurements
Luminance (cd/ni')
Contrast
Day
Mean
St. Dev.
Mean
St. Dev.
CEVMS
2126
798.81
-0.10
0.54
Standard Billboard
2993
2787.22
-0.27
0.84
Night
CEVMS
56.00
23.16
73.72
56.92
Standard Billboard
17.80
17.11
36.01
30.93
Visual Complexity
The DCZs were characterized by their overall visual complexity or clutter. For each DCZ, five
pictures were taken from the driver's viewpoint at various locations within the DCZ. In Reading,
the pictures were taken from 2:00 p.m. to 4:00 p.m. In Richmond, one route was photographed
from 11:00 a.m. to noon and the other from 2:30 p.m. to 3:30 p.m. The pictures were taken at the
start of the DCZ, quarter of the way through, half of the way through, three quarters of the way
through, and at the end of the DCZ. The photographs were analyzed with MATLAB® routines
that computed a measure of feature congestion for each image. Figure 10 shows the mean feature
congestion measures for each of the DCZ environments. The arterial control condition was
shown to have the highest level of clutter as measured by feature congestion. An analysis of
variance was performed on the feature congestion measure to determine if the conditions differed
significantly from each other. The four conditions with off-premise advertising did not differ
significantly with respect to feature congestion; F(3,36) = 1.25,/' > 0.05. Based on the feature
congestion measure, the results indicate that the four conditions with off-premise advertising
were equated with respect to the overall visual complexity of the driving scenes.
Arterial
Highway
Control 
CEVMS
Adveitising Conditions
Standard
Figure 10. Mean feature congestion as a function of advertising condition and road type
(standard errors for the mean are included in the graph).
27

Effects of Billboards on Gazes to the Road Ahead
For each 60 Hz frame, a determination was made as to the direction of the gaze vector. Previous
research has shown that gazes do not need to be separated into saccades and fixations before
calculating such measures as percent of time or the probability of looking to the road ahead.^^^^
This analysis examines the degree to which drivers gaze toward the road ahead across the
different advertising conditions as a function of road type and time of day. Gazing toward the
road ahead is critical for driving, and so the analysis examines the degree to which gazes toward
this area are affected by the independent variables (advertising type, type of road, and time of
day) and their interactions.
Generalized estimating equations (GEE) were used to analyze the probability of a participant
gazing at driving-related information.^'^®''''^ The data for these analyses were not normally
distributed and included repeated measures. The GEE model is appropriate for these types of
data and analyses. Note that for all results included in this report, Wald statistics were the chosen
alternative to likelihood ratio statistics because GEE uses quasi-likelihood instead of maximum
likelihood.^"^^^ For this analysis, road ahead included the following ROIs (as previously described
and displayed in figure 9): road ahead, road ahead top, and driving-related risks. A logistic
regression model for repeated measures was generated by using a binomial response distribution
and Logit (i.e., log odds) link function. Only two possible outcomes are allowed when selecting a
binomial response distribution. Thus, a variable (RoadAhead) was created to classify a
participant's gaze behavior. If the participant gazed toward the road ahead, road ahead top, or
driving-related risks, then the value of RoadAhead was set to one. If the participant gazed at any
other object in the panoramic scene, then the value of RoadAhead was set to zero. Logistic
regression typically models the probability of a success. In the current analysis, a success would
be a gaze to road ahead information (RoadAhead = 1) and a failure would be a gaze toward non-
road ahead information (RoadAhead = 0). The resultant value was the probability of a participant
gazing at road-ahead information.
Time of day (day or night), road type (freeway or arterial), advertising condition (CEVMS,
standard billboard, or control), and all corresponding second-order interactions were explanatory
variables in the logistic regression model. The interaction of advertising condition by road type
was statistically significant, (2) = 6.3, j? = 0.043. Table 4 shows the corresponding
probabilities for gazing at the road ahead as a function of advertising condition and road type.
Table 4. The probability of gazing at the road ahead as a function of advertising condition
and road type.
-
Advertising Condition
Arterial
Freeway
Control
0.92
0.86
CEVMS
0.82
0.73
II
Standard
0.80
0.77
Follow-up analyses for the interaction used Tukey-Kramer adjustments with an alpha level of
0.05. The arterial control condition had the greatest probability of looking at the road ahead
(M = 0.92). This probability differed significantly fi-om the remaining five probabilities. On
28

arterials, the probability of gazing at the road ahead did not differ between the CEVMS
(M = 0.82) and the standard billboard (M = 0.80) DCZs. In contrast, there was a significant
difference in this probability on freeways, where standard billboard DCZs yielded a higher
probability (M = 0.77) than CEVMS DCZs (M = 0.73). The probability of gazing at the road
ahead was also significantly higher in the freeway control DCZ (M = 0.86) than in either of the
corresponding freeway off-premise advertising DCZs. The probability of gazing at road-ahead
information in arterial CEVMS DCZs was not statistically different from the same probability in
the freeway control DCZ.
Additional descriptive statistics were computed to determine the probability of gazing at the
various ROIs that were defined in the panoramic scene. Some of the ROIs depicted in figure 9
were combined in the following fashion for ease of analysis:
• Road ahead, road ahead top, and driving-related risks combined to form road ahead.
• Left side of road bottom and left side of road top combined to form left side ofvehicle.
• Right side of road bottom and right side of road top combined to form right side of
vehicle.
•
 Inside vehicle and top combined to form participant vehicle.
Table 5 presents the probability of gazing at the different ROIs.
Table 5. Probability of gazing at ROIs for the three advertising conditions on arterials and
freeways.
Standard
Road Type
ROI
CEVMS
Billboard
Control
Arterial
CEVMS
0.07
N/A
N/A
Lefi Side of Vehicle
0.06
0.06
0.02
Road ahead
0.82
0.80
0.92
Right Side of Vehicle
0.03
0.06
0.04
Standard Billboard
N/A
0.03
N/A
Participant Vehicle
0.03
0.05
0.02
Freeway
CEVMS
0.05
N/A
N/A
Left Side of Vehicle
0.08
0.07
0.04
Road ahead
0.73
0.77
0.86
Right Side of Vehicle
0.09
0.02
0.05
Standard Billboard
0.02*
0.09
N/A
Participant Vehicle
0.04
0.05
0.05
The probability of gazing away from the forward roadway ranged from 0.08 to 0.27. In
particular, the probability of gazing toward a CEVMS was greater on arterials (M = 0.07) than on
freeways (M = 0.05). In contrast, the probability of gazing toward a target standard billboard was
greater on freeways (M = 0.09) than on arterials (M = 0.03).
29

Fixations to CEVMS and Standard Billboards
About 2.4 percent of the fixations were to CEVMS. The mean fixation duration to a CEVMS
was 388 ms and the maximum duration was 1,251 ms. Figure 11 shows the distribution of
fixation durations to CEVMS during the day and night. In the daytime, the mean fixation
duration to a CEVMS was 389 ms and at night it was 387 ms. Figure 12 shows the distribution of
fixation durations to standard billboards. Approximately 2.4 percent of fixations were to standard
billboards. The mean fixation duration to standard billboards was 341 ms during the daytime and
370 ms at night. The maximum fixation duration to standard billboards was 1,284 ms (which
occurred at night). For comparison purposes, figure 13 shows the distribution of fixation
durations to the road ahead (i.e., top and bottom road ahead ROIs) during the day and night. In
the daytime, the mean fixation duration to the road ahead was 365 ms and at night it was 390 ms.
Percentage Distribution of Fixation Duration
CEVMS Fsatio-is
23-
H a-
20-
Day
OE=L
»S!lL
0--r—-r
«3C0
1
 \ 
1 
1 
r
TCO 
1.100 
1,500 
1.900
500 
SOQ 
1.3CC 
1,700 
>2.000
Duration (ms]
Figure 11. Distribution of fixation duration for CEVMS in the daytime and nighttime.
30

Percentage Distribution of Rxation Duration
Standard BSIboard Rxations
60-
2
20-
Pay
N'iqht
n
1
 ' 
I 
: 
T" 
1 
1
WO 
7C0 
1 100 
1,500 
1-9O0
SOO 
900 
1,300 
1.700 
>2X0
Duration (ms)
Figure 12. Distribution of fixation duration for standard billboards in the daytime and
nighttime.
Percentage ^stribubon of Fixation Ouratbn
Road Ahead (Tcp and Bottom} Foalfons
60-
20-
Dav
rin
o-J-4
□Or
< 300 
7C0 
11C0 
1,500 
1.900
503 
BOO 
1,300 
1.700 
>2.300
Duration (ms)
Figure 13. Distribution of fixation duration for road ahead (i.e., top and bottom road ahead
ROIs) in the daytime and nighttime.
31

Dwell times on CEVMS and standard billboards were also examined. Dwell time is the duration
of back-to-back fixations to the same 
The dwell times represent the cumulative time
for the back-to-back fixations. Whereas there may be no long, single fixation to a billboard, there
might still be multiple fixations that yield long dwell times. There were a total of 25 separate
instances of multiple fixations to CEVMS wiA a mean of 2.4 fixations (minimum of 2 and
maximum of 5). The 25 dwell times came from 15 different participants distributed across four
different CEVMS. The mean duration of these dwell times was 994 ms (minimum of 418 ms and
maximum of 1,467 ms).
For standard billboards, there were a total of 17 separate dwell times with a mean of 3.47
sequential fixations (minimum of 2 fixations and maximum of 8 fixations). The 17 dwell times
came from 11 different participants distributed across 4 different standard billboards. The mean
duration of these multiple fixations was 1,172 ms (minimum of 418 ms and maximum of
3,319 ms). There were three dwell-time durations that were greater than 2,000 ms. These are
described in more detail below.
In some cases several dwell times came from the same participant. In order to compute a statistic
on the difference between dwell times for CEVMS and standard billboards, average dwell times
were computed per participant for the CEVMS and standard billboard conditions. These average
values were used in a t-test assuming unequal variances. The difference in average dwell time
between CEVMS (M = 981 ms) and standard billboards (M= 1,386 ms) was not statistically
significant, r( 12) = 
-1.40, j? > .05.
Figure 14 through figure 23 show heat maps for the dwell-time durations to the standard
billboards that were greater than 2,000 ms. These heat maps are snapshots from the DCZ and
attempt to convey in two dimensions the pattern of gazes that took place in a three dimensional
world. The heat maps are set to look back approximately one to two seconds and integrate over
time where the participant was gazing in the scene camera video. The green color in the heat map
indicates the concentration of gaze over the past one to two seconds. The blue line indicates the
gaze trail over the past one to two seconds.
Figure 14 through figure 16 are for a DCZ on an arterial at night. The standard billboard was on
the right side of the road (indicated by a pink rectangle). There were eight fixations to this
billboard, and the single fixations were between 200 to 384 ms in duration. The dwell time for
this billboard was 2,019 ms. At the start of the DCZ 
(see figure 14), the driver was directing
his/her gaze to the forward roadway. Approaching the standard billboard, the driver began to
fixate on the billboard. However, the billboard was still relatively close to the road ahead ROI.
32

Figure 14. Heat map for the start of a DCZ for a standard billboard at night on an arterial.
Figure 15. Heat map for the middle of a DCZ for a standard billboard at night on an
arterial.
%
Figure 16. Heat map near the end of a DCZ for a standard billboard at night on an arterial.
Figure 17 through figure 19 are for a DCZ on a freeway at night. The standard billboard was on
the right side of the road (indicated by a green rectangle). There were six consecutive fixations to
this billboard, and the single fixations were between 200 and 801 ms in duration. The dwell time
for this billboard was 2,753 ms. At the start of the DCZ (see figure 17), the driver was directing
his/her gaze to a freeway guide sign in the road ahead and the standard billboard was to the left
of the freeway guide sign. As the driver approached the standard billboard, his/her gaze was
directed toward the billboard. The billboard was relatively close to the top and bottom road
ahead ROIs. Near the end of the DCZ (see figure 19), the billboard was accurately portrayed as
being on the right side of the road.
33

Figure 17. Heat map for start of a DCZ for a standard billboard at night on a freeway.
Figure 18. Heat map for middle of a DCZ for a standard billboard at night on a freeway.
Figure 19. Heat map near the end of a DCZ for a standard billboard at night on a freeway.
Figure 20 through figure 23 are for a DCZ on a freeway during the day. The standard billboard
was on the right side of the road (indicated by a pink rectangle). This is the same DCZ that was
discussed in figure 17 through figure 19. There were six consecutive fixations to this billboard,
and the single fixations were between 217 and 767 ms in duration. The dwell time for this
billboard was 3,319 ms. At the start of the DCZ 
(see figure 20), the driver was principally
directing his/her gaze to the road ahead. Figure 21 and figure 22 show the location along the
DCZ where gaze was directed toward the standard billboard. The billboard was relatively close
to the top and bottom road-ahead ROIs. As the driver passed the standard billboard, his/her gaze
returned to the road ahead (see figure 23).
34

Figure 20. Heat map for the start of a DCZ for a standard billboard in the daytime on a
freeway.
Figure 21. Heat map near the middle of a DCZ for a standard billboard in the daytime on a
freeway.
Figure 22. Heat map near the end of DCZ for standard billboard in the daytime on a
freeway.
Figure 23. Heat map at the end of DCZ for standard billboard in the daytime on a freeway.
35

Comparison of Gazes to CEVMS and Standard Billboards
The GEE were used to analyze whether a participant gazed more toward CEVMS than toward
standard billboards, given that the participant was gazing at off-premise advertising. With this
analysis method, a logistic regression model for repeated measures was generated by using a
binomial response distribution and Logit link function. First, the data was partitioned to include
only those instances when a participant was gazing toward off-premise advertising (either to a
CEVMS or to a standard billboard); all other gaze behavior was excluded from the input data set.
Only two possible outcomes are allowed when selecting a binomial response distribution. Thus,
a variable (SBB_CEVMS) was created to classify a participant's gaze behavior. If the participant
gazed toward a CEVMS, 
the value of SBB_CEVMS was set to one. If the participant gazed
toward a standard billboard, then the value of SBB_CEVMS was set to zero.
Logistic regression typically models the probability of a success. In the current analysis, a
success would be a gaze to a CEVMS (SBB_CEVMS = 1) and a failure would be a gaze to a
standard billboard (SBB_CEVMS = 0).^ A success probability greater than 0.5 indicates there
were more successes than failures in the sample. Therefore, if the sample probability of the
response variable (i.e., SBB_CEVMS) was greater than 0.5, this would show that participants
gazed more toward CEVMS than toward standard billboards when the participants gazed at off-
premise advertising. In contrast, if the sample probability of the response variable was less than
0.5, then participants showed a preference to gaze more toward standard billboards than toward
CEVMS v/hen directing gazes to off-premise advertising.
Time of day (i.e., day or night), road type (i.e., freeway or arterial), and the corresponding
interaction were explanatory variables in the logistic regression model. Road type was the only
predictor to have a significant effect, x^(l) = 13.17, p < 0.001. On arterials, participants gazed
more toward CEVMS than toward standard billboards (M = 
0.63). In contrast, participants gazed
more toward standard billboards than toward CEVMS when driving on freeways (M = 
0.33).
Observation of Driver Behavior
No near misses or driver errors were observed in Reading.
Level of Service
The mean vehicle densities were converted to level of service as shown in table 
As
expected, less congestion occurred at night than in the day. In general, there was traffic during
the data collection runs. Review of the scene camera data verified that all eye tracking data
within the DCZs were recorded while the vehicle was in motion.
Success and failure are not used to reflect the merits of either type of sign, but only for statistical purposes.
36

Table 6. Level of service as a function of advertising type, road type, and time of day.
Arterial 
Freeway
Day
Night
Day
Night
Control
B
A
C
B
CEVMS
C
A
B
A
Standard
A
A
B
A
DISCUSSION OF READING RESULTS
Overall the probability of gazing at the road ahead was high and similar in magnitude to what
has been found in other field studies addressing billboards/^^'^'^^^ For the DCZs on freeways,
CEVMS showed a lower proportion of gazes to the road ahead than the standard billboard
condition, and both off-premise advertising conditions had lower probability of gazes to the road
ahead than the control. On the other hand, on the arterials, the CEVMS and standard billboard
conditions did not differ from each other but were significantly different from their respective
control condition. Though the CEVMS condition on the freeway had the lowest proportion of
gazes to the road ahead, in this condition there was a lower proportion of gazes to CEVMS as
compared to the arterials (see table 5 for the trade-off of gazes to the different ROIs). A greater
proportion of gazes to other ROIs (left side of the road, right side of the road, and participant
vehicle) contributed to the decrease in proportion of gazes to the road aliead. Also, for the
CEVMS on freeways, there were a few gazes to a standard billboard located in the same DCZ
and there were more gazes distributed to the left and right side of the road than in standard
billboard and control conditions. The gazes to ROIs other than CEVMS contributed to the lower
probability of gazes to the road ahead in this condition.
The control condition on the arterial had buildings along the sides of the road and generally
presented a visually cluttered area. As was presented earlier, the feature congestion measure
computed on a series of photographs from each DCZ showed a significantly higher feature
congestion score for the control condition on arterials as compared to all of the other DCZs.
Nevertheless, the highest probability for gazing at the road ahead was seen in the control
condition on the arterial.
The area with the highest feature congestion, especially on the sides of the road, had the highest
probability for drivers looking at the road ahead. Bottom-up or stimulus driven measures of
salience or visual clutter have been useful in predicting visual search and the effects of visual
salience in laboratory tasks.^^'^''^^^ These measures of salience basically consider the stimulus
characteristics (e.g., size, color, brightness) independent of the requirements of the task or plans
that an individual may have. Models of visual salience may predict that buildings and other
prominent features on the side of the road may be visually salient objects and thus would attract
a driver's attention.^"^^^ Figure 24 shows an example of a roadway photograph that was analyzed
with the Salience Toolbox based on the Itti et al. implementation of a saliency based model of
bottom-up attention.^'^^''^^^ The numbered circles in figure 24 are the first through fifth salient
areas selected by the software. Based on this software, the most salient areas in the photographs
are the buildings on the sides of the road where the road ahead (and a car) is the fifth selected
salient area.
37

Figure 24. Example of identified salient areas in a road scene based on bottom-up analysis.
It appears that in the present study participants principally kept their eyes on the road even in the
presence of visual clutter on the sides of the road, which simports the hypothesis that drivers tend
to look toward information relevant to the task at hand/^^'~ 
In the case of the driving task,
visual clutter may be more of an issue with respect to crowding that may affect the driver's
ability to detect visual information in the periphery/'^' Crowding is generally defined as the
negative effect of nearby objects or features on visual discrimination of a target/^^^ Crowding
impairs the ability to recognize objects in clutter and principally affects perception in peripheral
vision. However, crowing effects were not analyzed in the present study.
Stimulus salience, clutter, and the nature of the task at hand interact in visual perception. For
tasks such as driving, the task demands tend to outweigh stimulus salience when it comes to gaze
control. Clutter may be more of an issue with the detection and recognition of objects in
peripheral vision (e.g., detecting a sign on the side of the road) that are surrounded by other
stimuli that result in a crowding effect.
The mean fixation durations to CEVMS, 
standard billboards, and the road ahead were found to
be very similar. Also, there were no long fixations (greater than 2,000 ms) to CEVMS or
standard billboards. The examination of multiple sequential fixations to CEVMS yielded average
dwell times that were less than 1,000 ms. However, when examining the tails of the distribution,
there were three dwell times to standard billboards that were in excess of 2,000 ms (the three
dwell times came from three different participants to two different billboards). These three
standard billboards were dwelled upon when they were near the road ahead area but drivers quit
gazing at the signs as they neared them and the signs were no longer near the forward field of
view. Though there were three dwell times for standard billboards greater than 2,000 ms, the
difference in average dwell times for CEVMS and standard billboards was not significant.
Using a gaze duration of 2,000 ms away from the road ahead as a criterion indicative of
increased risk has been developed principally as it relates to looking inside the vehicle to in-
vehicle information systems and other devices (e.g., for texting) where the driver is indeed
looking completely away from the road ahead.^'"^'^^'^'^^ The fixations to the standard billboards in
the present case showed a long dwell time for a billboard. However, unlike gazing or fixating
inside the vehicle, the driver's gaze was within the forward roadway where peripheral vision
could be used to monitor for hazards and for vehicle control. Peripheral vision has been shown to
be important for lane keeping, visual search orienting, and monitoring of surrounding
objects.*^^'^^^
38

The results showed that drivers were more likely to gaze at CEVMS on arterials and at standard
billboards on freeways. Though every attempt was made to select CEVMS and standard
billboard DCZs that were equated on important parameters (e.g., which side of the road the sign
was located on, type of road, level of visual clutter), the CEVMS DCZs on freeways had a
greater setback from the road (133 ft for both CEVMS) 
than the standard billboards (10 and
35 ft). Signs with greater setback from the road would in a sense move out of the forward view
(road ahead) more quickly than signs that are closer to the road. The CEVMS and standard
billboards on the arterials were more closely matched with respect to setback firom the road (12
and 43 ft for CEVMS and 20 and 40 ft for standard billboards).
The differences in setback from the road for CEVMS and standard billboards may also account
for differences in dwell times to these two types of billboards. However, on arterials where the
CEVMS and standard billboards were more closely matched there was only one long dwell time
(greater than 2,000 ms) and it was to a standard billboard at night.
39

RICHMOND
The objectives of the second study were the same as those in the first study, and the design of the
Richmond data collection effort was very similar to that employed in Reading. This study was
conducted to replicate as closely as possible the design of Reading in a different driving
environment. The independent variables included the type of DCZ (CEVMS, standard billboard,
or no off-premise advertising), time of day (day or night) and road type (freeway or arterial). As
with Reading, the time of day was a between-subjects variable and the other variables were
within subjects.
METHOD
Selection of DCZ 
Limits
Selection of the DCZ limits procedure was the same as that employed in Reading.
Advertising Type
Three DCZ types (similar to those used in Reading) were used in Richmond:
• CEVMS. DCZs contained one target CEVMS.
•
 Standard billboard. DCZs contained one target standard billboard.
• Control conditions. DCZs did not contain any off-premise advertising.
There were an equal number of CEVMS and standard billboard DCZs on freeways and arterials.
Also, there two DCZ that did not contain off-premise advertising with one located on a freeway
and the other on an arterial.
Table 7 is an inventory of the target employed in this second study.
Table 7. Inventory of tai^et billboards in Richmond with relevant parameters.
DCZ
Advertising
Type
Copy
Dimensions
(ft)
Side of
Road
Setback
from Road
(ft)
Other
Standard
Billboards
Approach
Length (ft)
Roadway
Type
5
CONTROL
N/A
N/A
N/A
N/A
710
Arterial
3
CONTROL
N/A
N/A
N/A
N/A
845
Freeway
9
CEVMS
14'0"x28'0"
L
37
0
696
Arterial
13
CEVMS
14'0"x28'0"
R
37
0
602
Arterial
2
CEVMS
12'5"x40'0"
R
91
0
297
Freeway
8
CEVMS
ir0x23'0"
L
71
0
321
Freeway
10
Standard
14'0"x48'0"
L
79
1
857
Arterial
12
Standard
10'6"x45'3"
R
79
2
651
Arterial
Standard
14'0"x48'0"
L
87
0
997
Freeway
7
Standard
14'0"x48'0"
R
88
0
816
Freeway
N/A indicates that there were no ojf-premise advertising in these areas and these values are undefined
40

Figure 25 through figure 30 below represent various pairings of DCZ type and road type. Target
off-premise billboards are indicated by red rectangles.
Figure 25. Example of a CEVMS DCZ on a freeway.
Figure 26. Example of CEVMS DCZ an arterial.
Figure 27. Example of a standard billboard DCZ on a freeway.
41

Figure 28. Example of a standard billboard DCZ on an arterial.
Figure 29. Example of a control DCZ on a freeway.
ll
Figure 30. Example of a control DCZ on an arterial.
Photometric Measurement of Signs
The methods and procedures for the photometric measures were the same as for Reading.
Visual Complexity
The methods and procedures for visual complexity measurement were the same as for Reading.
42

Participants
A total of 41 participants were recruited for the study. Of these, 6 participants did not complete
data collection because of an inability to properly calibrate with the eye tracking system, and 11
were excluded because of equipment failures. A total of 24 participants (13 male, M = 28 years;
11 female, M = 25 years) successfully completed the drive. Fourteen people participated during
the day and 10 participated at night.
Procedures
Research participants were recruited locally by means of visits to public libraries, student unions,
community centers, etc. A large number of the participants were recruited from a nearby
university, resulting in a lower mean participant age than in Reading.
Participant Testing
Two people participated each day. One person participated during the day beginning at
approximately 12:45 p.m. The second participated at night beginning at around 7:00 p.m. Data
collection ran from November 20,2009, through April 23,2010. There were several long gaps in
the data collection schedule due to holidays and inclement weather.
Pre-Data Collection Activities
This was the same as in Reading.
Practice Drive
Except for location, this was the same as in Reading.
Data Collection
The procedure was much the same as in Reading. On average, each test route required
approximately 30 to 35 minutes to complete. As in Reading, the routes included a variety of
freeway and arterial driving segments. One route was 15 miles long and contained two target
CEVMS, two target standard billboards, and two DCZs with no off-premise advertising. The
second route was 20 miles long and had two target CEVMS and two target standard billboards.
The data collection drives in this second study were longer than those in Reading. The eye
tracking system had problems dealing with the large files that resulted. To mitigate this technical
difficulty, participants were asked to pull over in a safe location during the middle of each data
collection drive so that new data files could be initiated.
Upon completion of the data collection, the participant was instructed to return to the designated
meeting location for debriefing.
Debriefing
This was the same as in Reading.
43

DATA REDUCTION
Eye Tracking Measures
The approach and procedures were the same as used in Reading.
Other Measures
The approach and procedures were the same as used in Reading.
RESULTS
Photometric Measurement of Signs
The photometric measurements were performed using the same equipment and procedures that
were employed in Reading with a few minor changes. Photometric measurements were taken
during the day and at night. Measurements of the standard billboards were taken at an average
distance of 284 ft, with maximum and minimum distances of 570 ft and 43 ft, 
respectively. The
average distance of measurements for the CEVMS was 479 ft, 
with maximum and minimum
distances of 972 ft and 220 ft, 
respectively. Again, the distances employed were significantly
affected by the requirement to find a safe location on the road from which to take the
measurements.
Luminance
The mean luminance of CEVMS and standard billboards, during daytime and nighttime are
shown below in table 8. The results here are similar to those for Reading.
Contrast
The daytime and nighttime Weber contrast ratios for both types of billboards are shown in
table 8. During the day, the contrast ratios of both CEVMS and standard billboards were close to
zero (the surroundings were about equal in brightness to the signs). At night, the CEVMS and
standard billboards had positive contrast ratios. Similar to Reading, the CEVMS showed a higher
contrast ratio than the standard billboards at night.
Table 8. Summary of luminance (cd/m^) and contrast (Weber ratio) measurements.
Luminance (cd/m^)
Contrast
Day
Mean
St. Dev.
Mean
St. Dev.
CEVMS
2134
798.70
-0.20
0.53
Standard Billboard
3063
2730.92
0.03
0.32
Night
CEVMS
56.44
16.61
69.70
59.18
Standard Billboard
8.00
5.10
6.56
3.99
44

Visual Complexity
As with Reading, the feature congestion measure was used to estimate the level of visual
complexity/clutter in the DCZs. The analysis procedures were the same as for Reading.
Figure 31 shows the mean feature congestion measures for each of the advertising types
(standard errors are included in the figure). Unlike the results for Reading, the selected off-
premise advertising DCZs for Richmond differed in terms of mean feature congestion; F(3, 36) =
3.95,p = 0.016. Follow up t-tests with an alpha of 0.05 showed that the CEYMS DCZs on
arterials had significantly lower feature congestion than all of the other off-premise advertising
conditions. None of the remaining DCZs with off-premise advertising differed from each other.
The selection of DCZs for the conditions with off-premise advertising took into account the type
of road, the side of the road the target billboard was placed, and the perceived level of visual
clutter. Based on the feature congestion measure, these results indicated that the conditions with
off-premise advertising were not equated with respect to level of visual clutter.
Artenal
c Highway
w
 3.00
Control 
CEVMS 
Standard
Advertising Condition
Figure 31. Mean feature congestion as a function of advertising condition and road type.
Effects of Billboards on Gazes to the Road Ahead
As was done for the data from Reading, GEE were used to analyze the probability of a
participant gazing at the road ahead. A logistic regression model for repeated measures was
generated by using a binomial response distribution and Logit link function. The resultant value
was the probability of a participant gazing at the road ahead (as previously defined).
Time of day (day or night), road type (freeway or arterial), advertising type (CEVMS, 
standard
billboard, or control), and all corresponding second-order interactions were explanatory variables
in the logistic regression model. The interaction of advertising type by road type was statistically
significant, (2) = 14.19,;7 < 0.001. Table 9 shows the corresponding probability of gazing at
the road ahead as a function of advertising condition and road type.
45

Table 9. The probability of gazing at the road ahead as a function of advertising condition
and road type.
Advertising Condition
Arterial
Freeway
Control
0.78
0.92
CEVMS
0.76
0.82
Standard
0.81
0.85
Follow-up analyses for the interaction used Tukey-Kramer adjustments with an alpha level of
0.05. The freeway control had the greatest probability of gazing at the road ahead (M = 0.92).
This probability differed significantly from the remaining five probabilities. On arterials, there
were no significant differences among the probabilities of gazing at the road ahead among the
three advertising conditions. On fireeways, there was no significant difference between the
probability associated with CEVMS DCZs and the probability associated with standard billboard
DCZs.
Additional descriptive statistics were computed for the three advertising types to determine the
probability of gazing at the ROIs that were defined in the panoramic scene. As was done with the
data from Reading, some of the ROIs were combined for ease of analysis. Table 10 presents the
probability of gazing at the different ROIs.
Table 10. Probability of gazing at ROIs for the three advertising conditions on arterials
and freeways.
Standard
Road Type 
ROI
CEVMS
Billboard
Control
Arterial 
CEVMS
0.06
N/A
N/A
Left Side of Vehicle
0.03
0.05
0.04
Road ahead
0.76
0.81
0.78
Right Side of Vehicle
0.07
0.06
0.09
Standard Billboard
N/A
0.02
N/A
Participant Vehicle
0.07
0.06
0.09
Freeway 
CEVMS
0.05
N/A
N/A
Left Side of Vehicle
0.03
0.01
0.01
Road ahead
0.82
0.85
0.92
Right Side of Vehicle
0.04
0.04
0.03
Standard Billboard
N/A
0.04
N/A
Participant Vehicle
0.06
0.06
0.05
The probability of gazing away from the forward roadway ranged from 0.08 to 0.24. In
particular, the probability of gazing toward a CEVMS was slightly greater on arterials
(M = 0.06) than on freeways (M = 0.05). In contrast, the probability of gazing toward a standard
billboard was greater on freeways (M = 0.04) than on arterials (M = 0.02). In both situations, the
probability of gazing at the road ahead was greatest on freeways.
46

Fixations to CEVMS and Standard Billboards
About 2.5 percent of the fixations were to CEVMS. The mean fixation duration to a CEVMS
was 371 ms and the maximum fixation duration was 1,335 ms. Figure 32 shows the distribution
of fixation durations to CEVMS during the day and at night. In the daytime, the mean fixation
duration to a CEVMS was 440 ms and at night it was 333 ms. Approximately 1.5 percent of the
fixations were to standard billboards. The mean fixation duration to standard billboards was
318 ms and the maximum fixation duration was 801 ms. Figure 33 shows the distribution of
fixation durations for standard billboards. The mean fixation duration to a standard billboard was
313 ms and 325 ms during the day and night, respectively. For comparison purposes, figure 34
shows the distribution of fixation durations to the road ahead during the day and night. In the
daytime, the mean fixation duration to the road ahead was 378 ms and at night it was 358 ms.
Percentaga Distribution of Fixation Duration
CCVUS Fixations
60-
S 0-
20-
Oav
□
JQ
Wwht n
< 300 
7C0
500
110C 
1.500 
1.SC3
1.3£H3 
1,700 
>2.(a3
Duration (ms)
Figure 32. Fixation duration for CEVMS in the day and at night.
47

Percentage Distribution of Fixation Duration
Standard Billboards Fixations
g 20-
g 60-
£
20-
_Oai_
r\r-n
Ntght
I ","U .n,
I
 I 
i 
I 
I
?00 
"CO 
' 
■'CC 
1.50O 
1.5»W
500 
eoc 
t.300 
1,700 
>2X0
Dj'atcn ins;
Figure 33. Fixation duration for standard billboards in the day and at night.
Percentage Distribution of Rxation Dura&n
Road Ahead (Top and Bctfon) Facalions
20-
20-
rxiy
Ltic
N'iohl
iHr
•n——' I 
' 
I 
1 
1 
j 
1
SCO 
7C0 
MM 
1,€0O 
1.900
500 
SCO 
1,300 
-.700 
>zooa
DJiBtion (ms)
Figure 34. Fixation duration for the road ahead in the day and at night.
48

As was done with the data for Reading, the record of fixations was examined to determine dwell
times to CEVMS and standard billboards. There were a total of 21 separate dwell times to
CEVMS with a mean of 2.86 sequential fixations (minimum of 2 fixations and maximum of 6
fixations). The 21 dwell times came from 12 different participants and four different CEVMS.
The mean dwell time duration to the CEVMS was 1,039 ms (minimum of 500 ms and maximum
of 2,720 ms). There was one dwell time greater than 2,000 ms to CEVMS. To the standard
billboards there were 13 separate dwell times with a mean of 2.31 sequential fixations (minimum
of 2 fixations and maximum of 3 fixations). The 13 dwell times came from 11 different
participants and four different standard billboards. The mean dwell time duration to the standard
billboards was 687 ms (minimum of 450 ms and maximum of 1,152 ms). There were no dwell
times greater than 2,000 ms to standard billboards.
In some cases several dwell times came from the same participant. To compute a statistic on the
difference between dwell times for CEVMS and standard billboards, average dwell times were
computed per participant for the CEVMS and standard billboard conditions. These average
values were used in a Mest assuming unequal variances. The difference in average dwell time
between CEVMS (M = 1,096 ms) and standard billboards (M= 674 ms) was statistically
significant, r(14) - 
2.23,/? = 
.043.
Figure 35 through figure 37 show heat maps for the dwell-time durations to the CEVMS that
were greater than 2,000 ms. The DCZ was on a freeway during the daytime. The CEVMS is
located on the left side of the road (indicated by an orange rectangle). There were three fixations
to this billboard, and the single fixations were between 651 ms and 1,335 ms. The dwell time for
this billboard was 2,270 ms. Figure 35 shows the first fixation toward the CEVMS. There are no
vehicles near the participant in his/her respective travel lane or adjacent lanes. In this situation,
the billboard is relatively close to the road ahead ROI. Figure 36 shows a heat map later in the
DCZ where the driver continues to look at the CEVMS. The heat map does not overlay the
CEVMS in the picture since the heat map has integrated over time where the driver was gazing.
The CEVMS has moved out of the area because of the vehicle moving down the road. However,
visual inspection of the video and eye tracking statistics showed that the driver was fixating on
the CEVMS. Figure 37 shows the end of the sequential fixations to the CEVMS. The driver
returns to gaze directly in front of the vehicle. Once the CEVMS was out of the forward field of
view, the driver quit looking at the billboard.
Figure 35. Heat map for first fixation to CEVMS with long dwell time.
49

Figure 36. Heat map for later fixations to CEVMS with long dwell time.
Figure 37. Heat map at end of fixations to CEVMS with long dwell time.
Comparison of Gazes to CEVMS and Standard Billboards
As was done for the data from Reading, GEE were used to analyze whether a participant gazed
more toward CEVMS than toward standard billboards, given that the participant was looking at
off-premise advertising. Recall that a sample probability greater than 0.5 indicated that
participants gazed more toward CEVMS than standard billboards when the participants gazed at
off-premise advertising. In contrast, if the sample probability was less than 0.5, participants
showed a preference to gaze more toward standard billboards than CEVMS when directing
visual attention to off-premise advertising.
Time of day (i.e., day or night), road type (i.e., freeway or arterial), and the corresponding
interaction were explanatory variables in the logistic regression model. Time of day had a
significant effect on participant gazes toward off-premise advertising, (1) = 4.46, p = 0.035.
Participants showed a preference to gaze more toward CEVMS than toward standard billboards
during both times of day. During the day the preference was only slight (M = 0.52), but at night
the preference was more pronounced (M = 
0.71). Road type was also a significant predictor of
where participants directed their gazes at off-premise advertising, x^ (0 ~ 3.96, p = 0.047.
Participants gazed more toward CEVMS than toward standard billboards while driving on both
types of roadways. However, driving on freeways yielded a slight preference for CEVMS over
standard billboards (M = 0.55), but driving on arterials resulted in a larger preference in favor of
CEVMS (M = 
0.68).
50

Observation of Driver Behavior
No near misses or driver errors occurred.
Level of Service
Table 11 shows the level of service as a function of advertising type, type of road, and time of
day. As expected, there was less congestion during the nighttime runs than in the daytime. In
general, there was traffic during the data collection runs; however, the eye tracking data were
recorded while the vehicles were in motion.
Table 11. Estimated level of service as a function of advertising condition, road type, and
time of day.
Arterial 
Freeway
Day
Night
Day
Night
Control
B
A
C
B
CEVMS
B
A
B
A
Standard
C
A
C
C
DISCUSSION OF RICHMOND RESULTS
Overall the probability of looking at the forward roadway was high across all conditions and
consistent with the fmdings from Reading and previous related research.^^^'^'^^^ In this second
study the CEVMS and standard billboard conditions did not differ from each other. For the
DCZs on arterials there were no significant differences among the control, CEVMS, and
standard billboard conditions. On the other hand, while the CEVMS and standard billboard
conditions on the freeways did not differ from each other, they were significantly different from
their respective control conditions. The control condition on the freeway principally had trees
along the sides of the road and the signs that were present were freeway signs located in the road
ahead ROI.
Measures such as feature congestion rated the three DCZs on freeways as not being statistically
different from each other. These types of measures have been useful in predicting visual search
and the effects of visual salience in laboratory tasks.^^'^^ Models of visual salience may predict
that, at least during the daytime, trees on the side of the road may be visually salient objects that
would attract a driver's attention.^"^^^ However, it appears that in the present study, participants
principally kept their eyes on the road ahead.
The mean fixations to CEVMS, 
standard billboards, and the road ahead were found to be similar
in magnitude with no long fixations. Examination of dwell times showed that there was one long
dwell time for a CEVMS greater than 2,000 ms and it occurred in the daytime on a sign located
on the left side of the road on a freeway DCZ. Furthermore, when averaging among participants
the mean dwell time for CEVMS was significantly longer than to standard billboards, but still
under 2,000 ms. For the dwell time greater than 2,000 ms, examination of the scene camera
video and eye tracking heat maps showed that the driver was initially looking toward the forward
roadway and made a first fixation to the sign. Three fixations were made to the sign and then the
51

driver started looking back to the road ahead as the sign moved out of the forward field of view.
On the video there were no vehicles near the subject driver's own lane or in adjacent lanes.
Only the central 2 degrees of vision, foveal vision, provide resolution sharp enough for reading
or recognizing fine detail.^^^^ However, useful information for reading can be extracted from
parafoveal vision, which encompasses the central 10 degrees ofvision.^^^^ More recent research
on scene gist recognition^ has shown that peripheral vision (beyond parafoveal vision) is more
useful than central vision for recognizing the gist of a scene.^^®^ Scene gist recognition is a
critically important early stage of scene perception, and influences more complex cognitive
processes such as directing attention within a scene and facilitating object recognition, both of
which are important in obtaining information while driving.
The results of this study do show one duration of eyes off the forward roadway greater than
2,000 ms, the duration at which Klauer et al. observed near-crash/crash risk at more than twice
those of normal, baseline driving.^^'*'"^ When looking at the tails of the fixation distributions, few
fixations were greater than 1,000 ms, with the longest fixation being equal to 1,335 
The
one long dwell time on a CEVMS that was observed was a rare event in this study, and review of
the video and eye tracking data suggests that the driver was effectively managing acquisition of
visual information while driving and fixated on the advertising. However, additional work needs
to be done to derive criteria for gazing or fixating away from the forward road view where the
road scene is still visible in peripheral vision.
The results showed that drivers are more likely to look at CEVMS than standard billboards
during the nighttime across the conditions tested (at night the average probability of gazing at
CEVMS was M= 
0.71). CEVMS do have greater luminance than standard billboards at night and
also have higher contrast. The CEVMS have the capability of being lit up so that they would
appear as very bright signs to drivers (for example, up to aboutl0,000 cd/m^ for a white square
on the sign.). However, our measurements of these signs showed an average luminance of about
56 cd/m^. These signs would be. conspicuous in a nighttime driving environment but significantly
less so than other light sources such as vehicle headlights. Drivers were also more likely to look
at CEVMS than standard billboards on both arterials and freeways, with a higher probability of
gazes on arterials.
In this second study, CEVMS and standard billboards were more nearly equated with respect to
setback from the road. Gazes to the road ahead were not significantly different between CEVMS
and standard billboard DCZs across conditions and the proportion of gazes to the road ahead
were consistent with previous research. One long dwell time for a CEVMS was observed in this
study; however, it occurred in the daytime where the luminance and contrast (affecting the
perceived brightness) of these signs are similar to those for standard billboards.
^ "Scene gist recognition" refers to the element of human cognition that enables us to determine the meaning of a
scene and categorize it by type (e.g., a beach, an office) almost immediately upon seeing it.
52

GENERAL DISCUSSION
This study was conducted to investigate the effect of CEVMS on driver visual behavior in a
roadway driving environment. An instrumented vehicle with an eye tracking system was used.
Roads containing CEVMS, 
standard billboards, and control areas with no off-premise
advertising were selected. The CEVMS and standard billboards were measured with respect to
luminance, location, size, and other relevant variables to characterize these visual stimuli. Unlike
previous studies on digital billboards, the present study examined CEVMS as deployed in two
United States cities and did not contain dynamic video or other dynamic elements. The CEVMS
changed content approximately every 8 to 10 seconds, consistent within the limits provided by
FHWA guidance.^' In addition, the eye tracking system used had nearly a 2-degree level of
resolution that provided significantly more accuracy in determining what objects the drivers were
gazing or fixating on as compared to some previous field studies examining CEVMS.
CONCLUSIONS
Do CEVMS attract drivers' attention away from the forward roadway and other driving
relevant stimuli?
Overall, the probability of looking at the road ahead was high across all conditions. In Reading,
the CEVMS condition had a lower proportion of gazes to the road ahead than the standard
billboard condition on the freeways. Both of the off-premise advertising conditions had a lower
proportion of gazes to the road ahead than the control condition on the freeway. The lower
proportion of gazes to the road ahead can be attributed to the overall distribution of gazes away
from the road ahead and not just to the CEVMS. On the other hand, for the arterials the CEVMS
and standard billboard conditions did not differ from each other, but both had a lower proportion
of gazes to the road ahead compared to the control. In Richmond there were no differences
among the three advertising conditions on the arterials. However, for the freeways the CEVMS
and standard billboard conditions did not differ from each other but had a lower proportion of
gazes to the road ahead than the control.
The control conditions differed across studies. In Reading, the control condition on arterials
showed 92 percent for gazing at the road ahead while on the freeway it was 86 percent. On the
other hand, in Richmond the control condition for arterials was 78 percent and for the freeway it
was 92 percent. The control conditions on the freeway differed across the two studies. In
Reading there were businesses off to the side of the road; whereas in Richmond the sides of the
road were mostly covered with trees. The control conditions on the arterials also differed across
cities in that both contained businesses and on-premise advertising; however, in Reading arterials
had four lanes and in Richmond arterials had six lanes. The reason for these differences across
cities was that these control conditions were selected to match the other conditions (CEVMS and
standard billboards) that the drivers would experience in the two respective cities. Also, the
selection of DCZs was obviously constrained by what was available on the ground in these cities.
The results for the off-premise advertising conditions are consistent with Lee et al., who
observed that 76 percent of drivers' time was spent looking at the road ahead in the CEVMS
scenario and 75 percent in the standard billboard scenario.^^^ However, it should be kept in mind
53

that drivers did gaze away from the road ahead even when no off-premise advertising was
present and that the presence of clutter or salient visual stimuli did not necessarily control where
drivers gazed.
Do glances to CEVMS occur that would suggest a decrease in safety?
In DCZs containing CEVMS, about 2.5 percent of the fixations were to CEVMS 
(about 2.4
percent to standard billboards). The results for fixations are similar to those reported in other
field data collection efforts that included advertising signs.^^^'^^'^'^^^ Fixations greater than
2,000 ms were not observed for CEVMS or standards billboards.
However, an analysis of dwell times to CEVMS showed a mean dwell time of 994 ms
(maximum of 1,467 ms) for Reading and a mean of 1,039 ms (maximum of 2,270 ms) for
Richmond. Statistical comparisons of average dwell times between CEVMS and standard
billboards were not significant in Reading; however, in Richmond the average dwell times to
CEVMS were significantly longer than to standard billboards, though below 2,000 ms. There
was one dwell time greater than 2,000 ms to a CEVMS across the two cities. On the other hand,
for standard billboards there were three long dwell times in Reading; there were no long dwell
times to these billboards in Richmond. Review of the video data for these four long dwell times
showed that the signs were not far from the forward view when participants were fixating.
Therefore, the drivers still had access to information about what was in front of them through
peripheral vision.
As the analyses of gazes to the road ahead showed, drivers distributed their gazes away from the
road ahead even when there were no off-premise billboards present. Also, drivers gazed and
fixated on off-premise signs even though they were generally irrelevant to the driving task.
However, the results did not provide evidence indicating that CEVMS were associated with long
glances away from the road that may reflect an increase in risk. When long dwell times occurred
to CEVMS or standard billboards, the road ahead was still in the driver's field of view.
Do drivers look at CEVMS more than at standard billboards?
The drivers were generally more likely to gaze at CEVMS than at standard billboards. However,
there was some variability between the two locations and between type of roadway (arterial or
freeway). In Reading, the participants looked more often at CEVMS when on arterials, whereas
they looked more often at standard billboards when on freeways. In Richmond, the drivers
looked at CEVMS more than standard billboards no matter the type of road they were on, but as
in Reading the preference for gazing at CEVMS was greater on arterials (68 percent on arterials
and 55 percent on freeways). The slower speed on arterials and sign placement may present
drivers with more opportunities to gaze at the signs.
In Richmond, the results showed that drivers gazed more at CEVMS than standard billboards at
night; however, for Reading no effect for time of day was found. CEVMS do have higher
luminance and contrast than standard billboards at night. The results showed mean luminance of
about 56 cd/m^ in the two cities where testing was conducted. These signs would appear clearly
visible but not overly bright.
54

SUMMARY
The results of these studies are consistent with a wealth of research that has been conducted on
vision in natural environments/^^'^^'^'^ Inthe driving environment, gaze allocation is principally
controlled by the requirements of the task. Consistent results were shown for the proportion of
gazes to the road ahead for off-premise advertising conditions across the two cities. Average
fixations were similar to CEVMS and standard billboards with no long single fixations evident
for either condition. Across the two cities, four long dwell times were observed: one to a
CEVMS on a freeway in the day, two to the same standard billboard on a freeway (once at night
and once in the daytime), and one to a standard billboard on an arterial at night. Examination of
the scene video and eye tracking data indicated that these long dwell times occurred when the
billboards were close to the forward field of view where peripheral vision could still be used to
gather visual information on the forward roadway.
The present data suggest that the drivers in this study directed the majority of their visual
attention to areas of the roadway that were relevant to the task at hand (i.e., the driving task).
Furthermore, it is possible, and likely, that in the time that the drivers looked away from the
forward roadway, they may have elected to glance at other objects in the surrounding
environment (in the absence of billboards) that were not relevant to the driving task. When
billboards were present, the drivers in this study sometimes looked at them, but not such that
overall attention to the forward roadway decreased.
LIMITATIONS OF THE RESEARCH
In this study the participants drove a research vehicle with two experimenters on board. The
participants were provided with audio tum-by-tum directions and consequently did not have a
taxing navigation task to perform. The participants were instructed to drive as they normally
would. However, the presence of researchers in the vehicle and the nature of the driving task do
limit the degree to which one may generalize the current results to other driving situations. This
is a general limitation of instrumented vehicle research.
The two cities employed in the study appeared to follow common practices with respect to the
content change frequency (every 8 to 10 seconds) and the brightness of the CEVMS. The current
results would not generalize to situations where these guidelines are not being followed.
Participant recruiting was done through libraries, community centers and at a university. This
recruiting procedure resulted in a participant demographic distribution that may not be
representative of the general driving population.
The study employed a head-free eye tracking device to increase the realism of the driving
situation (no head-mounted gear). However, the eye tracker had a sampling rate of 60 Hz, which
made determining saccades problematic. The eye tracker and analyses software employed in this
effort represents a significant improvement in technology over previous similar efforts in this
area.
The study focused on objects that were 1,000 feet or less from the drivers. This was dictated by
the accuracy of the eye tracking system and the ability to resolve objects for data reduction. In
addition, the geometry of the roadway precluded the consideration of objects at great distances.
55

The study was performed on actual roadways, and this limited the control of the visual scenes
except via the route selection process. In an ideal case, one would have had roadways with
CEVMS, 
standard billboards, and no off-premise advertising and in which the context
surrounding digital and standard billboards did not differ. This was not the case in this study,
although such an exclusive environment would be inconsistent with the experience of most
drivers. This presents issues with the interpretation of the specific contributions made by
billboards and the environment to the driver's behavior.
Sign content was not investigated (or controlled) in the present study, but may be an important
factor to consider in future studies that investigate the distraction potential of advertising signs.
Investigations about the effect of content could potentially be performed in driving simulators
where this variable could be systematically controlled and manipulated.
56

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60

EXHIBITS

Title:
Accession Number:
Record Type:
Language:
Source Agency:
Source Data:
Abstract:
Evaluating the Clearview Typeface System for Negative Contrast
Signs
01489749
Project
English
Mid-Atlantic Universities Transportation Center
201 Transportation Research Building
University Park, PA 16802-4710 USA
RiP Project 35041
The development of Clearview typeface began in response to a Federal
Highway Administration (FHWA) 
study that recommended a 20
percent increase in sign letter height to provide greater reading
distances for aging drivers. The original Clearview studies showed that
it was possible to obtain significant improvements in guide sign reading
distances for older drivers without increasing letter height by using
mixed-case Clearview typefaces in place of all-uppercase Standard
Highway Alphabets. Furthermore, the positive contrast (i.e., lighter
letters on darker background) mixed case Clearview typefaces were
found to be significantly more legible than the mixed case Standard
Highway Series E(M) 
in several independent studies. This body of
research led to tlie 2004 interim approval of Clearview on positive
contrast guide signs by the FHWA. Clearview was specifically
designed to improve guide sign readability at night for older drivers
when used with high brightness sign materials by reducing or
eliminating the negative effects of halation and overglow. However, the
Clearview Typeface System also includes negative contrast versions to
be used on regulatory and warning signs. The difference between
positive contrast versions of Clearview and negative contrast versions
are limited to stroke width; with negative contrast being heavier to
counter-balance the halation effect of the lighter background when
viewed at a distance and with high brightness retroreflective materials.
While the research discussed above led to the development of
guidelines and approval for the use of Clearview in positive contrast,
definitive studies have not been conducted for negative contrast
applications. Without this research, Clearview's approval will remain
restricted to positive contrast applications and full adoption will not
take place. The objective of the proposed research is to compare the
legibility distance of the negative contrast (i.e., darker letters on a
lighter background) Clearview Typeface System with that of Standard
Highway Alphabets on regulatory signs in the daytime and nighttime
with older and younger motorists. The researchers will identify the
legibility distances and evaluate the effects of letter spacing of sign

TRIS Files:
Contract Numbers:
Funding:
Start Date;
Actual Completion
Date:
Performing Agencies:
Funding Agencies:
Index Terms:
Subject Areas:
legends using: mixed case Clearview (Clearview 2B, 3B, and 4B) and
both mixed and all upper-case Standard Highway Alphabets (Series C,
D, and E) on white signs with black legends.
UTC, RIP
DTRT12-G-UTC03
PSU-2013-02
35000.00
20130215
20140214
Mid-Atlantic Universities Transportation Center
201 Transportation Research Building
University Park, PA 16802-4710 USA
Research and Innovative Technology Administration
University Transportation Centers Program
Washington, DC 20590 USA
Mid-Atlantic Universities Transportation Center
201 Transportation Research Building
University Park, PA 16802-4710 USA
Clearview font; Contrast; Legibility; Sign legend typefaces; Traffic
signs; Visibility
Construction; Design; Highways; Operations and Traffic Management;
Safety and Human Factors
Title:
Accession Number:
Record Type:
Language:
Record URL:
Source Agency:
Evaluation of Guide Sign Fonts
01481805
Project
English
http://www.DOoledfund.org/Details/Studv/490
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590 USA

Source Data:
Abstract:
TRIS Files:
Contract Numbers:
Funding:
Start Date:
Funding Agencies:
RiP Project 29842
The objective of this study is to conduct a field evaluation of new
available highway fonts versus the Series E (Modified) and Clearview
5WR fonts for use on guide signs. This study will provide the analysis
necessary for decision to be made on inclusion of fonts for older drivers
in the Manual on Uniform Traffic Control Devices (MUTCD). In
previous studies comparing Clearview fonts to previously used types,
legibility distance, the distance at which a subject can read an unknown
word, has been a robust measure of effectiveness. Researchers believe
that in order to test the proposed font against the current standard,
nighttime data collection in which participants drive an instrumented
vehicle along a closed course while researcher's record data would be
most conducive.
RiP
TPF-5(262)
195000.00
20120223
Colorado Department of Transportation
4201 East Arkansas Avenue
Denver, CO 80222 USA
Florida Department of Transportation
Research Center
605 Suwannee Street MS-30
Tallahassee, PL 32399-0450 USA
West Virginia Department of Transportation
Division of Highways
Building 5, Room A-110
Charleston, WV 25305-0430 USA
Minnesota Department of Transportation
Transportation Building
395 John Ireland Boulevard
St Paul, MN 55155 USA
Iowa Department of Transportation
800 Lincoln Way
Ames, lA 50010 USA
California Department of Transportation
1227 O Street

Sacramento, CA 95843 USA
Responsible
Individuals:
Index Terms:
Subject Areas:
Johnson, Cory J
Clearview font; Legibility; Manual on Uniform Traffic Control
Devices; Nighttime driving; Sight distance; Sign fonts
Highways; Operations and Traffic Management
Title:
Accession Number:
Record Type:
Language:
Source Agency:
Source Data:
Abstract:
Clearview Font in Traffic Signs: Assessing IDOT Experiences and
Needs
01480029
Project
English
Illinois Department of Transportation
2300 S. Dirksen Parkway
Springfield, IL 62764 USA
RiP Project 28631
The Clearview font has many advantages over previous font practices,
such as night legibility and lack of smearing effect. Some of the
potential concerns include incompatibility with commonly used
background sheeting and sight distance. However, experience in other
states to date, as well as experimental studies in the lietarture, suggest
that the advantages appear to outweigh the concerns. The main
objective of this study is to determine Illinois' progress in using the
Clearview font and whether its use has proven successful. While most
previous in the literature were mostly done in an experimental in
setting, this study (R27-75) aims to determine how the implementation
of the Clearview font for signs has affected Illinois and its motorists in
a real-world context. Accordingly, the study team is examining the
implementation of this font from the perspectives of both installers and
motorists. This project will also monitor media reports about the
Clearview font and/or this research project. The main field research
portion of this study will include both intercept and follow-up surveys
with motorists who have encountered Clearview signs. An important
aspect of this project will be developing questions that adequately
query user perceptions. Some questions will be whether motorists
notice a difference between Clearview signs and other signs and how
eligible Clearview signs are to them. This will be done for illuminated

TRIS Files:
Contract Numbers:
Funding:
Start Date:
Actual Completion
Date:
Performing Agencies:
Funding Agencies:
Index Terms:
Subject Areas:
and non-illuminated locations in order to compare motorist reactions.
The final task is the final report, which is accompanied by an interim
report in April followed by the final report a year later. There will also
be quarterly progress reports along with meetings of the panel every
four months.
RiP
R27-75
230000.00
20100515
20120331
Northwestern University, Evanston
Transportation Center, 600 Foster Sti'eet
Evanston, IL 60208-4055 USA
Illinois Department of Transportation
2300 S. Dirksen Parkway
Springfield, IL 62764 USA
Clearview font; Illinois; Night visibility; Sight distance; Sign sheeting;
Traffic signs
Data and Information Technology; Highways; Operations and Traffic
Management
Title:
Accession Number:
Record Type:
Language:
Record URL:
Source Agency:
Effectiveness of Larger Traffic Signs, High-Performance Sheeting
and Clearview Font on Accident Reduction
01480047
Project
English
http://transDort.ksu.edu/researcli/KSUTC-08-6.Ddf
Kansas State University's Center for Transportation Research
2118 Friedier Hall
Manhattan, KS 66506-5000 USA
Source Data:
RiP Project 20990

Abstract:
TRIS Files:
Contract Numbers:
During the last several decades, the number of drivers and rural/urban
traffic has significantly increased, along with the number of traffic
signs. Traffic signs provide a plethora of necessary information -
directions, guidance, warnings, regulations, and recreation. With
today's congestion and higher speed, it's very important to recognize
specific situations where larger, brighter, and easier to read signs
should be installed to increase safety of the drivers. It is equally
important to counties with limited funds to fmd locations and/or
scenarios where bigger, more costly signs are not cost effective. Many
signing studies of problem locations recommend bigger, brighter, easier
to read signs. However, there is little evidence that sign size, or
readability directly relate to accident causation. Counties want evidence
that larger, more costly signs are cost effective in regard to safety. A
study of the other attributes can be made within this same project at
little incremental cost with results made beneficial to both the state and
counties. There is a need for documentation of the accident reduction
benefits of these sign attributes for a range of approach scenarios and
accident types. The main objective of this research will be to determine
typical locations and/or scenarios where bigger signs are effective in
reducing accidents on rural/urban roads and where they are not
effective, thus saving money for use at more critical locations. Within
this study, a secondary objective will be to also study the safety benefits
of brighter, easier to read signs.
UTC, RiP
RE-040-05; HPD-R043
KSUTC-08-6
Funding:
Start Date:
49659.00
20070228
Actual Completion
Date:
20110630
Performing Agencies: Kansas State University's Center for Transportation Research
2118 FriedlerHall
Manhattan, KS 66506-5000 USA
Funding Agencies:
Kansas Department of Transportation
Eisenhower State Office Building
700 SW Harrison Street
Topeka, KS 66603-3754 USA
Responsible
Individuab:
Stokes, Robert W

Index Terms: 
Overhead traffic signs; Research projects; Road and highway
directions; Sign sheeting; Traffic control devices; Traffic signs;
Visibility
Subject Areas: 
Highways; Operations and Traffic Management; Research

EXHIBIT?

Industry's Traffic Safety Research
The outdoor advertising industry's foundation (Foundation for Outdoor
Advertising Research and Education) has pioneered research on digital billboards
and traffic safety, commissioning top experts to study driver behavior and also to
analyze crash data. An initial study, released in 2007, was based on "human
factors" such as drivers' eye glances. Meanwhile, engineering experts have
analyzed accident reports provided by state and local authorities in jurisdictions
across the country.
Human Factors Research
•
 Virginia Tech Transportation Institute (2007)
•
 This study used an instrumented vehicle to measure eye glances in the
presence of off-premise digital billboards and conventional billboards (The
pending FHWA study relies on eye-glance methodology)
•
 Findings of industrv research:
o Drivers did not glance more frequently in the direction of digital
billboards than in the direction of other event types
o The mean glance towards digital billboards was less than one second
Accident Analysis
•
 
Tantala Associates, LLC
o Cleveland, OH (2007 and updated in 2009)
o Rochester, MN (2009)
o Albuquerque, NM (2010)
o Reading, PA (2010)
o Richmond, VA (2010)
I
 Each of these studies analyzed crash data before and after
deployment of digital billboards. Research in Reading, PA and
Richmond, VA, also used a contemporary AASHTO-approved
method known as Bayes Analysis (with and without billboards)
o Findings:
I The accident data does not show a statistical relationship
between vehicular accidents and billboards (conventional and
digital billboards)
I The number or rate of vehicular accidents didn't increase after
the installation of off-premise digital billboards
I The accident statistics near billboards are comparable to the
accident statistics on similar sections of highway without
billboards
I Accidents occur with or without billboards (digital or
conventional)

Summary of Past Traffic Safety Research Studies
• Other Studies Not on Point
Dozens of studies have examined driver distraction, including the role of signs.
However, the body of research cited by Jerry Wachtel is primarily comprised of
reports not specifically focused on digital billboards, in fact in a companion
research project, the FHWA's literature review of these studies has determined
that these studies are "inconclusive." These studies look at:
o On-premise signs
On-premise digital signs can flash, feature full motion video, and scroll text
under U.S. regulations. Roadside digital billboards operate under tougher
regulations than on-premise signs.
1. Beijer (2002) (Canada)
2. Smiley (2005) (Canada)
3. Wisconsin DOT study of the Milwaukee Stadium sign (1994) (U.S.)
o Simulators
According to Jerry Wachtel, studies using simulators to examine the effects
of digital signs are not reliable due to the inherent limitations of the simulator
environment.
1. Finnish Road Administration (2004) (Finland)
2. Brunei University (2007) (England)
3. Young and Mahfoud (2007) (England)
4. Edquist (2009) (Australia)
5. Fisher (2009) (U.S.)
o
 Literature reviews (No research completed)
1. Wachtel and Netherton (1980) (U.S.)
2. Farbry (2001) (U.S.)
3. CTC & Associates (2003) (U.S.)
4. SWOV Institute for Road Safety Research (2006) (Dutch)
5. SRF Consulting Group (2007)
6. FWHA (2009) (U.S.)
•
 
Driver Distraction/inattention
Research by government and the insurance industry has identified many factors
that distract drivers, as well as conditions related to accidents. In 2006, the
National Highway Traffic Safety Administration released a comprehensive report
known at the "100-Car Crash Study" which found that:
o Drowsiness increases the risk of accidents 4-6 times
o Distraction or inattention was estimated to cause more than 23% of all
crashes and near crashes
o Glances totaling more than 2 seconds increase near-crash/crash risk by at
least two times (A typical glance at a digital billboard is less than one
second)
o Short, brief glances away from the roadway for the purpose of scanning the
driving environment are safe and actually decrease near-crash/crash risk

EXHIBITS

LIGHTING
SCIENCES
Lighting Sciences Inc.
7826 East Evans Road
Scotfsdale, Arizona 85260 U.S.A.
Tel: 480-991-9260 Fax: 480-991-0375
www.liglitingsciences.com
October 1,2008
Report to: 
Outdoor Advertising Association of America
Subject: 
Digital Billboard Recommendations and Comparisons to Conventional Billboards
Abstract
This report summarizes several research projects undertaken by Lighting Sciences, Inc. (LSI)
related to billboard lighting. The topics that have been addressed are:
•
 
Development of digital billboard luminance recommendations
•
 A comparison of luminances of conventional billboards and digital billboards
•
 "Sky Glow** lumens entering the night sky from conventional and digital billboards.
i. 
Digital Billboard Luminance Recommendations
Lighting Sciences, Inc., has undertaken research to develop a method for specification of
luminance (brightness) limits for digital billboards based on accepted practice by the
Tlluminating Engineering-SoGiety-of North AmeriGa-(IESNA). The recommendation is extremely-
simple to implement and requires only a footcandle (fc) meter to be used.
The research establishes criteria for billboard luminance limits based on biUboard-to-viewer
distances for standardized billboard categories. For example, a standard billboard-to-viewer
distance of 250 feet is used to establish the billboard luminance limits for a 14' x 48' foot (672
sq.ft.) bulletin.
The recommended technique is based on accepted lESNA practice for "light trespass." Previous
outdoor lighting research has documented an established limit on the amoimt of light arriving at
a person's eyes to ensure that the source of the light is not offensive, or worse, potentially
dangerous. The technique is simple: the light level at the eye is measured in footcandles and has
an upper limit. The limit is low for areas that ai*e generally quite dark, but considerably higher in
well lit urban ai'eas.
A recommended specification for digital billboards is to use a limit of 0.3 fc over ambient light
conditions. To check if the level is acceptable, a footcandle meter would be held at a height of 5
ft. (which is. approximately eye height) and faced towards the billboaid at the desired billboard-

to-viewer distance. A reading of 0.3 fc or less above ambient light conditions would indicate
compliance.
The standards set forth in the report are based on the worst-case scenario of a driver or pedestrian
-viewing-the-displa-y-head=on.-(directly-ata90idegree.angle),-whilein-practice.most-display-s_are—
viewed at an angle. Since displays are generally viewed at an angle, the luminance (glare) is
substantially reduced.
Furthermore, the report provides values for billboard luminance of different color images and
notes that luminance levels are based on a worst-case scenario of an all-white display, which is
unlikely to happen, save for a malfunction. Knowing these values, and having established a
billboard luminance limit for a particular billboard, the allowable percentage of dimming setting
is also easily calculated.
The investigations and this report do not cover factors related to changing images and billboard
message movement. Issues that may be related to motorist attention are beyond the scope of the
work and use of the proposals in this study should be based on that understanding.
a. 
Comparison ofConventional and Digital Billboard Luminances
A study by Rensselaer Polytechnic Institute Lighting Research Center has measured the
luminance of typical conventional billboards and has developed the maximum value of
luminance that can be expected. LSI has compared the recommendations developed in this
report to the Rensselaer measured values.- The digital billboards will be brighter,-but only - —
slightly brighter, than the maximum luminance of conventional billboards.
Hi. 
Sky Glow
Sky glow is caused by lighting at night entering the atmosphere and being scattered by airborne
particulates. Sky glow may result from the use of lighting fixtures that emit Ught above a
horizontal plane so that it enters the atmosphere directly. The effect also is caused by light
reflecting from lighted objects, such as a road suiface, a building or a billboard.
The study has evaluated the amount of light entering the atmosphere from a variety of lighting
installations. Measured in "sky lumens," the results allow a comparison to be made of different
lighting systems relative to slcy glow. Specifically calculations have been made to compare tlie
sky lumens produced by conventional billboard lighting systems, both three and four luminarre
bottom moimted systems lighting a standard 14 x 48fl. billboard, to the sky lumens caused by
roadway and parking lot lighting.

Various scenarios have been used for the roadway lighting, combining residential and major
highway lighting in a typical neighborhood. Areas have been considered that consist only of
roadway lighting, as well as areas that contain both roadway and parking lot lighting.
-Xhoxesults-olthe study.support.a-conclusiQn-thatihe-V.astjnajoi'i1y-OfLsky_glowis..a.pi:nduct of
urban development. Even where full cut-off fixtures are used on all roadway and parking lot
lighting fixtures, and if there is an average of one billboard per square mile, over 96% of the sky
glow produced per urban square mile is fi'om those sources and not billboard lighting, for tlie
conditions examined. For ^e examples considered, a single three fixture billboard lighting
system produces approximately 2 
to 3% of the sky lumens caused by roadway/parking area
lighting in the example one square mile area. For a four fixture billboai'd lighting system, the
range becomes roughly 2.5 to 4%. These figures can be prorated. For example, if there are two
such billboards per square mile, the percentages are doubled; if there is one such billboard per
two square miles, the percentages will be halved.
The exact percentages of sky glow are affected by the density of roadways/parking areas, the
type of lighting fixtures used and the lighting level provided, among other factors. However, it is
apparent that for the scenarios considered, the contribution of billboard lighting to sky glow is
small in comparison to that firom other sources of lighting. The other sources produce 96 to 98%
of sky lumens, compared to the 2 to 4% produced per billboard in the example urban square
mile.
Digital billboards operating at the luminance levels recommended in this report produce much
fewer lumens into the night sky-than conventional bottom mounted lighting systemSi- This-is
primarily due to the elimination of the external luminaires, but also is a result of the
characteristics of the billboard pixel design whereby light in upward directions is reduced in
comparison to light sent below the horizontal in the direction of viewers.
Definitions
Luminance. Also known as photometric brightness, this is the "brightness" of the billboard as
seen fiom a particular angle of view. It is measured in candelas per sq. meter, also termed "nits.'
Illuminance. This is the amount of light firom the billboard landing on a distant surface. It is
measured in footcandles (fc) or lux.
Intensity. This is the candlepower, or concentration, of light emitted in a given direction jfrom
the entire billboard.

Reflectance. This is a measm'e of the proportion, or percentage, of light falling on a surface that
is reflected by the surface.
SECTION A - 
DIGITAL BILLBOARD LUMINANCE RECOMMENDATIONS
Al. 
Introduction
This report has been prepared for OAAA under the contract issued to Lighting Sciences Inc. for
the development of luminance (brightness) recommendations for digital billboards under
nighttime conditions. Extensive investigations have been conducted into methodologies that
could be used to develop such recommendations, specifically addressing environmental impact
and possible visibility effects on drivers.
The following approaches can be used:
1. Develop billboard recommendations based on the control of possible glare to which
drivers may be subjected.
or 
2. Produce recommendations founded on environmental impact, addressing the subject
known as light trespass.
Either of these methods can be used as a viable approach to providing an acceptable practice for
the control of digital billboard appearance, though the first method has disadvantages. In
analyzing these methods,- strict-attention has-been-paid to satisfying the following-: 
-
1. The needs of the general pubUc, including drivers.
2. The requirements of local government personnel, who may wish to incorporate
language into ordinances related to the use of digital billboards. For this, the
procedures must be straight forward and enforceable.
3. The needs of OAAA members, who require effective use of digital billboards, which
in turn requires adequate brightness for clear visibility.
The two approaches are addressed below.
A2. Method 1, Specifications Based on Driver Glare
Drivers on roadways at night where vutually any form of lighting is provided are inevitably
subjected to glare. Glare may be, for example, from oncoming headlights, street lights, or
commercial lighting, including billboards. There ai*e recommended limits to the amount of glare

that can be produced by vehicle headlights (from tlie U.S. Department of Transportation) and by
roadway lighting (from the American National Standards Institute and tlie Illuminating
Engineering Society of North America -lESNA.) In particular, the extensive procedures that
have been developed by lESNA can, in theory, be used to produce limitations on digital
-billboM^d-luminance-tliat-will-ensure-thatany-glare-problems-createdfoiLdri-vers-wilLbe-jelatively-
minor, in the order of glai'e often produced by a street lighting installation.
Lighting Sciences has conducted detailed investigations into this approach, based upon
publication ANSI DESNA RP-8-00, "American National Standard Practice for Roadway
Lighting." The basic procedures for such a method would be to specify an allowable average
billboard luminance level that would ensure that the glare it produces does not exceed certain
limits. These limits would be based on the level of highway lighting that is present. For
example, higher billboard luminances would be allowed where a high level of street lighting is
provided. Publication RP-8-00 classifies highways into many different types, and there is a set
of recommendations for the lighting of each type. Thus using these principles for digital
billboard specifications, there would be many different recommended billboard luminance limits,
dependent upon the form of roadway lighting provided in the area.
After much consideration. Lighting Sciences does not recommend this approach for establishing
digital billboard luminance limits. The reasons include the following:
1. Publication RP-8-00 describes 14 different roadway classifications. These are based on
different roadway types (for example, fireeways, major roadways, local roadways). There is a
■" further breakdovm basedmn the level ofpedestrian activity,-which may be high, medium or-
low. Basing billboard luminances on this wide range would produce a complex system of
specifications that would lack the simplicity and clarity that is our goal.
2. Digital billboards are firequently visible from numerous vantage points. This creates an issue
of deciding which of the 14 different categories would be applicable if different levels of
roadway lighting exist in a general ai'ea.
3. There is further complexity in determining the amount of glare produced by a digital
billboard using the metliodology of publication RP-8-00. The amount of glare is affected not
only by the luminance of a digital billboard, but by its distance from the driver. What
distance would be selected to perform the necessary calculations when the driver might view
tlie billboard fi:om a wide range of distances?
4. The amount of glare is affected also by tlie location of the billboard with respect to the
driver's line of sight. Tliis changes as tlie driver looks in different dhections and as his
location changes. What billboard position would be used?

5. The extent of any glare produced is dependent upon the billboard size. Recommended lumts
of luminance, if based on glare control, would be different for each billboai'd size.
Thus it can be seen that, because of all tlie variables involved, the establishing of realistic
-billboard-luminanGe-iimitsbased-on-the-RR-8=00-methodology-wouldhe-exceedingly^complex^
Even if simplifications were introduced, there would be problems in deciding which luminance
limit would be applicable to a given billboard. Checking and enforcement similarly would be
highly problematic. For these reasons, Lighting Sciences Inc. has not developed and is not
recommending a billboard luminance specification system based upon glare limitations.
However, in conducting the detailed study of this metliod and the second method that follows
below, it has been determined that if the method provided below is adopted, billboard
luminances will be such that producing a significant amount of glare to drivers from a single
digital billboard is unlikely, (although a multiplicity of such billboards appearing in the driver's
field of view simultaneously may possibly create a problem.) Further evaluations of this topic
are suggested using documents produced by other research organizations.
A3. 
Method 2, Specification Based on Light Trespass
A3.1 Method Overview
"Light trespass" is a term used in the outdoor lighting industry to describe light that falls outside
of theareathatis primarily intended to be lighted. "For example, if the lighting system for a
shopping center parking lot causes light to spill over into an adjacent residential neighborhood,
this would be considered to be light trespass. High levels of light trespass, as well as bemg
wasteful of energy, may have an appearance that is objectionable. Publication TM-11-00 of the
lESNA provides a table of limits of light trespass for various "lighting zones." These zones
range from "no ambient electric light" (dark rural areas) to "high ambient electric light"
(typically high use urban areas.) The limits are expressed in terms of the illuminance in
footcandles that the light source in question can produce at a person's eyes, measured above the
ambient lighting that is produced by all other sources of light. The limitation values were
determined from an extensive human factors research project into the levels of light trespass that
may or may not be considered objectionable in the various zones. Application of the limits keep
light trespass to a low level that is unlikely to be considered objectionable to most persons.
Digital billboards are not the form of lighting that TM-11-00 was developed to limit. In fact,
digital billboai'ds ai*e specifically intended to be seen over a wide area, much of which may be
remote from the billboard itself. Nevertheless, the principles of TM-l 1-00, in terms of the
calculation meOiod and the limits it provides, can be examined to determine whether the
methodology can form a useful metliod of specifying billboard luminance limits.

Numerous calculations have been performed to evaluate billboard luminance in terms of the TM-
11 -00 procedures. The calculations involved are simpler than those discussed above for RP-8-00
procedures, as they simply involve determining the illuminance in footcandles (fc) at the location
of the eyes of a viewer. (Referred to as "eye illuminance.") TM-11-00 provides four different
_e.ye-illuminanGe-limits-depending-on-the-lightmg-zone,^i-to-E4,-ranging-fconi:y-e3yJo-W_ambient_
electric light to high ambient electric light. See table 1. (A description of each type of ambient
electric light zone is included in Appendix B.)
Table 1
Eye Illuminance Limits (Light Produced by Billboard, a>ove Ambient)
Zone
Eye Illuminance Limit (fc)
El
Very low ambient electric light
0.1
E2
Low ambient electric light
0.3
E3
Medium ambient electric light
0.8
E4
High ambient electric light
1.5
To simplify billboard luminance specifications, it is proposed that all billboard luminance limits,
no matter where a billboard is located, are governed by the values given in the above table for
zone E2. This will then produce a uniform method that does not require the lighting zone to be
known. The logic for choosing zone E2 
is based on two considerations. Firstly, it is highly
unlikely that digital billboards will ever be used in areas described as zone El. El applies to
inherently very dark rural areas where there is almost no electric lighting, such as national parks.
Distal billboards'are likely to be used ih zones E2'through E4 
."By u^^ 
the limitations
specified by lESNA for zone E2, the specifications are very stringent; any billboard meeting the
E2 limits will be satisfactory for the higher ambient light conditions of zones E3 and E4. On this
basis, while any eye illuminance value could be used, this report recommends using only that
provided for zone E2.
Providing that a method is available to calculate the billboard luminance that will generate a
certain illuminance at the eye of a viewer, the illuminance limits of TM-11-00 can be converted
to billboai'd luminance limits. The conversion formula is provided below. It must be noted,
however, that this method is not totally straightforward, for there are variables that must be
considered for any given billboard, also discussed below.
A3.2 Determining the Maximum Allowable Billboard Average Luminance
The system for relating billboard luminance to the illuminance produced at tlie eye is briefly
summaiized in this section. A more detailed coverage of this topic, and lighting units and terms
in general, is provided in Appendix A.

Billboard luminance (which refers to the average luminance or brightness of billboard) is
expressed in candelas per square meter, cd/sq.m., sometimes termed "nits." The illuminance
produced at the eye, considered as landing on a vertical plane at the eye, is designated Ey and is
measured in footcandles.
To determine the Tnaximnm billboard average luminance, L, that can be allowed so as to meet a
given illuminance limit at the viewer's eye. By in footcandles, the following must be know:
• Area of billboard = S sq. ft.
• Distance from billboard center to observation point = D feet (as measured from a plan
view. Differences in height of the billboard and viewer normally can be disregarded,
as can lateral angle effects from the billboard face.)
Allowable maximum billboard average luminance, L = 
—- 
cd./sq.m. (nits)
1
For example, to determine whether a billboard meets a particular limit for the lESNA publication
TM-11-00, the following steps are taken:
1. Select the applicable lighting zone. It is proposed that E2, an area with a low level of electric
lighting, be selected as a st^dard._ 
_ 
_
2. Find the applicable eye illuminance limit from table 1. If zone E2 is assumed, this will be
0.3 fc.
3. Determine the billboard size. Assume for example a billboard measuring 10 ft. 6 ins. x 36 ft.,
giving an area of 378 sq. ft.
4. Assume a distance to the viewer. Use 200 ft. (See discussion below).
These values are entered into formula 1 above.
10.76.200'-0.3
Allowable maximum billboard average luminance =
378
= 342 cd/sq.m. (nits)

A3.2.1 Viewer Distance
The distance from the billboard to the viewer, D in the above formula, has a significant effect on
the calculated allowable maximum billboard luminance. Billboards ai*e typically viewed over a
range of distances, and so the choice of the value of D will be somewhat arbitrary. A short
distance such as 100 ft. is probably too small for normal situations, and can produce a very low
luminance limit. On the other hand, a very large distance such as 1000 ft. will rarely be
applicable because viewers will normally be closer when reading the billboard.
It may be questioned whether a short distance should be used as a standard to guard against
possible glare effects produced at the eyes of a person driving past a digital billboard.
Considering this, as a driver moves closer to a billboard that is positioned to the side of the
roadway and the driver is viewing the road ahead, the lateral angle firom the driver's line of sight
to the billboard increases. This angular effect causes any glare ^at the billboard may produce to
reduce significantly. (Reference: American National Standard for Roadway Lighting,
publication ANSI/IESNA RP-8-00, section A7. Glare reduces as the square of the angle from
the line of sight.) Further, as this angle iucreases, the light intensity (candelas) directed toward
the driver's eye decreases, as shown by photometric testing of a sample billboard. (Lighting
Sciences Inc. test report no. LSI 21628). This effect also contributes to the reduction in glare as
the driver approaches and then passes the billboard. These two effects more than offset other
factors in determining the glare produced at the driver's changing location: that is, glare actually
reduces as the driver's distance to a billboard that is off the side of the road becomes smaller,
assuming attention is on the road ahead.
In discussions with members of the advertising industry, it is apparent that billboard size and
viewing distance are related. Larger billboards are used to attract viewers at a greater distance,
while small billboards are provided where the observer is fairly close. On this basis, the viewing
distances, D, provided below are suggested for use with the formula, based on four prevalent
standard billboard sizes:
Proposec
Table 2
Viewer Distance Values, D
Billboard Size
Billboard
Dimensions (ft)
D
ft.
Small
11x22
150
Medium
10.5x36
200
Large
14x48
250
Very large
20x60
350

If there is a specific reason why a value of D other than as given above should be applied for a
particular billboard installation, this different value may be substituted accordingly in the
formula. It should be noted, however, that use of the above distances for the various billboard
sizes, and the billboard luminance values so produced, have been field evaluated and appear to
-be-reasonable
A3.2.2 Allowable Average Luminance and Billboard Size
For any given billboard size, formula 1 can be used to compute the allowable average luminance
by incoiporating the suggested distance value fi'om table 2. The results for the standard
dimension billboards are provided in table 3.
Table 3
Maximum Level of Digital Billboard Average Luminance
Candelas per Sq.M. (Nits)
Proposed Standard
(Based on lESNA Lighting Zone E2)
Billboard
Luminance
--Dimensions (ft.) --
ft;
(Gd-./sqim;)- 
-
11x22
150
300
10.5x36
200
342
14x48
250
300
20x60
350
330
♦Based on an illuminance produced at the viewer's eye of 0.3 footcandles.
** Distance measured at groiind level to observer facing the billboard perpendicularly
A3.3 Digital Billboard Photometric Testing
A small sample digital billboard was supplied to Lighting Sciences' laboratories in Scottsdale,
Arizona for photometric evaluation. This was a model as commercially produced in November
2006 by Young Electric Sign Company. Tliis was tested using a model 6440 goniophotometer.
Tests were run for the device displaying entirely wliite, red, green and blue colors respectively.
The white color is not formed by illuminating white LED's but rather by a combination of red,
green and blue LED's.
10

The digital billboard was progi*ammable for different levels of dimming. Tests were conducted
to measure the luminance at 10% dimming steps from 100% down to 10%.
-It.was determined that the actual luminance reduction achieved using the various dimming steps
accurately corresponded to within a few percent of the dimming settings indicated on the
controller.
Data from the series of tests allow the calculation of the luminance of any digital billboard color
for full intensity or any level of dimming. Of specific interest were the luminances of a white
display because this is the maximum luminance color, as it is generated by the combination of
the red, blue and green LED's.
A3.4 Determining the Allowable Dimmer Setting
If a billboard luminance limit has been established by the methodology described above, the
photometric data can also provide the dimming setting to be used.
Results of the testing indicated that the digital billboard produced a maximum average luminance
of approximately 7000 cd/sq.m. when displaying a completely white image at full power. In the
above example, to limit the luminance to 342 cd/sq.m. the dimmer setting can be computed as - -
follows:
.
 
Allowable luminance
% 
dimmer settmg = 
— 
x 100
7000
xlOO
7000
= 
4.9%
This example is for amedium billboard size measuring 10.5 x 36'. The dimmer setting will be
different for other billboard sizes because tlie allowable luminance changes per table 3. Table 4
presents the dimming settings calculated in an equivalent manner for the standard billboard
sizes.
TT

Table 4
Suggested Dimming Settings
Proposed Standard
(Based on lESNA Lighting Zone E2)
Billboard
Dimensions (ft.)
Dimming
Setting
11x22
4.3%
10.5x36
4.9%
14x48
4.3%
20x60
4.7%
It should be noted that table 4 is applicable only to the digital billboard that was tested.
Different types of billboards will produce different results, and therefore require separate
photometric testing.
A3.5 Non-white Billboards
If the digital image will never be totally white, higher % 
dimming settings can be used while
still meeting the luminance limit: The actual measured luminances for the sample billboard
measured in 2006 for a 100% luminance setting for different colors are:
White
Red
Green
Blue
7000 cd/sq.m.
,1500 cd/sq.m.
5100 cd/sq.m.
700 cd/sq.m.
For a normal image diat includes multiple colors, the average luminance for a 100% setting will
depend on tlie proportion of colors in the mix. Software and instrumentation is available to
analyze billboard luminance when the billboard is being programmed,
A3.6 Adoption of the Method
This method uses the established and recommended procedures of lESNA to develop billboard
luminance limits. The procedm'e can be adopted by referrmg to the limits of lESNA publication
TM-11 -00 as provided in table 1 above, with the suggestion that lighting zone E2 values be
12

used as a standard. Billboard-to-viewer distances are proposed to be as provided in table 2
above.
Table 3 summarizes the recommended maximum billboard luminance values based on tables 1
j^r»d
, Thftsft r.an be adopted directly into an ordinance or set of guidelines.
The limitations of TM-11-00 were established through research conducted by Lighting Sciences
Inc. under a contract from the Lighting Research Office of EPRI (Electrical Producers'
Research Institute). The basis of TM-11-00 was subsequently provided to lESNA to form the
publication. Field use of the values for various forms of outdoor fighting confirm that the
values are realistic and prevent undue annoyance to a majority of viewers, and thus appear to
have formed a satisfactory basis for specifying such fighting limits.
The procedures outlined in this section of this report, method 2, specifications based on light
trespass, are recommended by Lighting Sciences Inc. for evaluation and possible subsequent
adoption by OAAA.
A3.7 Enforcement
After a billboard is installed, there wiU be cases where it is desired to evaluate the billboard
luminance to ensure that it does not exceed the specified value. This procedure is extremely
simple and requires only a footcandle meter.
Tliehillboard-luminance specification is based on ensuring-that a-eertain footcandle level— -
created by the billboard is not exceeded at a chosen distance. Thus all that is needed to check
compliance is the measurement of the footcandles level at that distance with the billboard on
and off. The footcandle meter would be held at a height of 5 ft. (which is approximately eye
height) and aimed towards the billboard, from a distance as selected from table 2. If the
difference in illuminance between the billboard-on and billboard-off conditions is 0.3 fc, then
the billboard luminance is in compliance. When conducting this check, the meter should be at a
location perpendicular to the billboard center (as seen in plan view) as this angle has the highest
lumioance.
This check should include the measurement of an aU white image displayed by the billboard to
evaluate the worst case condition.
A4. Summary of Proposed Method
Specification based on the fight trespass limits adopted by lESNA in publication TM-11-00
appears to provide a manageable and technically viable technique.
13

It is proposed to use the lESNA recommended limits for environmental lighting zone E2, low
level electric lighting, as a standard. This limits the maximum illuminance produced by the
billboard and measured at tlie eye of a viewer to 0.3 footcandles over ambient. It is further
proposed that the viewer be positioned from the billboard at ground level and facing in a
Himctinn peipendicnlarto the billboard. The distance will be dependent upon the billboard size.
Under these conditions, to meet the 0.3 fc limitations, the maximum allowable billboard average
luminance will be as given in table 3 for various standard billboard sizes. The percentage
dimmer setting, expressed as a percentage of the billboard maximum luminance, can be
calculated from the table 3 luminance value, based on the maximum luminance of a billboard
being 7000 cd/sq.m. or some other known value.
Because these values have been derived from lESNA publication TM-11-00, which in turn is
based on an extensive human factors research project, adoption of such values should satisfy the
requirement that most persons will not find these billboard luminances to be objectionable.
SECTION B - 
BILLBOARD LUMINANCE : 
DIGITAL VERSUS CONVENTIONAL
The foregoing has provided recommendations for the average luminance limits for digital
billboards. It is of interest to compare these to frie luminance levels found with conventional
billboards. Such billboards are most commonly lighted using liiminaires designed for this
specific purpose, manufactured by the Holophane Company. Most installations consist of a
series of fixtures that use 400 watt Metal-Halide lampSi- Typically a I4 x 48 
large billboard-is
lighted by four such fixtures moimted along the bottom edge of the billboard. Some billboards,
employ a lighting system using only three bottom moimted luminaires. Other designs may use
top mounted lighting in various configurations. An optical refractor or lens is used on each
luminaire to direct light onto the billboard, which increases the billboard luminance.
The luminance of conventional billboards has been addressed in a study by the Lighting
Research Center of Rensselaer Polytechnic Institute that was sponsored by frie New York State
Department of Transportation. A technical memorandum has been developed titled "Evaluation
ofBillboard Luminances" dated March 31, 2008. This memorandum states the following:
"... it is probably reasonable to expect that the luminance of a conventional billboard would not
be likely to exceed about 280 cd/sq.nu during the nighttime (assuming typical lighting practice
as represented by the lESNA and industry recommendations, and by the lighting systems used
on the billboards that were measured in the field)..."
The report indicates that the value of 280 cd/sq.m. (nits) is consistent with clean billboard
lighting systems using new lamps. This is also the condition used for testing the digital
billboard at Lighting Sciences' laboratories as referenced above.
TT

It is thus anticipated that digital billboards operated in accordance with the recommendations
developed above, (300 to 342 nits, depending on size), will be brighter, but only slightly
brighter, than the maximum luminance of conventional billboards.
SECTION C 
~ SKY GLOW
C1 
Introduction
A hirther factor, "sky glow," has been addressed in relation to both conventional and digital
billboards.
Sky glow is caused by light at night entering the atmosphere and being scattered by airborne
particulates. Sky glow may result from the use of lighting fixtures that emit light above a
horizontal plane so that it enters the atmosphere directly. The effect also is caused by light
reflecting from lighted objects, such as a road surface, a building or a billboard.
It is highly desirable to reduce sky glow in order to preserve dark skies. This is an
environmental concern, as well as a significant factor influencing the ability of astronomers to
study the night sky.
The amount of light entering the atmosphere from a variety of lighting installations has been
evaluated.- -Measured in "sky lumenSj" the results allow a-comparison to be made-of different —
lighting systems relative to sky glow. Specifically calculations have been made to compare the
sky lumens produced by a typical billboard lighting system to the sky lumens caused by roadway
and parking lot lighting. Extensive work was conducted for conventional billboards, then later
work compared newer digital billboards to the conventional billboards.
Various scenarios were used for the roadway lighting, combining residential and major highway
lighting in a typical neighborhood. Areas were considered that consist only of roadway lighting,
as well as areas that contain both roadway and parking lot lighting.
C2.1 Conventional Billboards
A 14 X 48 ft. billboard was evaluated using both three and four bottom mounted Holophane
"Panel Yue" fixtures. Each was equipped with a 400 watt metal halide lamp rated at 40,000
lumens. Photometric test data were obtained from the manufacturer and computerized
calculations were performed.
15