The Effects of Commercial Electronic Variable Message Signs ...

cameras are mounted very high, multiple vehicle images may occlude each other. For a long
stretch of roadway, such as might required for CEVMS exposure, a relatively large array of
cameras may be needed. Thus, a large amount of data needs to be collected and analyzed in such
a study. Automatic machine vision video analysis algorithms can help in the data analysis
process, but such algorithms are not yet sufficiently sensitive and robust to reliably identify all of
the subtle indicators of driver errors, conflicts, or maladaptive performance which might
accompany CEVMS exposure. The use of other sensors instead of or in addition to cameras may
mitigate some of these data analysis problems to a certain extent.
B.3.3 Advantages/Disadvantages
The unobtrusive observation method possesses one major advantage over the other two methods:
the data are derived from the natural flow of traffic. Other than erecting camouflaged camera
arrays at various locations along the roadway, the experimenter does not disturb the natural flow
of human driving. As opposed to the other two methods, the vast majority of drivers are
completely unaware that they are part of a study depending on how well the camera camouflage
works. Other sensors used for this application can also be hidden and made extremely hard to
detect. This is the major advantage of the unobtrusive observation method. Another strong
advantage is the large number of vehicles which pass by the CEVMS and other comparison
stimuli every day. Sample sizes can be relatively large.
Like the other techniques, the unobtrusive observation method has disadvantages as well. First,
with present technology, it is not possible to implement eye-tracking measurements in such a
study. The inability to measure eye glance behavior makes it difficult to investigate important
constructs, like self-regulated attention and unconscious distraction as they relate to CEVMS
exposure. The method is left to rely on safety surrogate measures, such as driver errors and
maladaptive maneuvers. These relatively subtle pre-crash and near-crash driving behaviors are
difficult to measure by means of distal video cameras. Such driving behaviors also occur very
seldom and need to be observed over great distances, leading to the necessity to collect large
amounts of video data from extended camera arrays over long periods of time. The collection,
reduction and analysis of such large amounts of data tend to make this method time-consuming
and expensive.
B.3.4 Budgetary Cost
A rough budgetary estimate for conducting such an unobtrusive observation study is between
$1 million and $3 million. The main cost drivers for this method include designing camera arrays
which can measure subtle vehicle maneuvers, installing camera arrays to record a large extent of
roadway for all CEVMS and comparison stimuli, and collecting and analyzing data covering a
long period of time. The range in this budgetary estimate relates to the number of study sites,
adequacy of the sites, number and location of cameras in an array, method of recognizing safety
surrogate measures, length of the study at any given site, ability to turn the CEVMS off and on,
and numerous other factors which cannot be determined without further planning.
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