The Effects of Commercial Electronic Variable Message Signs ...

As mentioned above, the more detailed analysis underlying the combined list of key measures
shown above may be found in table 2 in appendix A. Table 2 for the dependent variables
has the same general structure as table 1 for the independent variables. The approximately 65
types of dependent variables listed in table 2 are further broken down into 105 specific subtypes
or levels of variables which could play an important role in measuring the possible effects of
CEVMS on driver distraction. As noted before, it is encouraged to carefully examine the
many dependent variables and their advantages and disadvantages, as described in table 2 in
appendix A, to gain a greater appreciation of the wide variety of ways that driver safety can
be measured as they relate to possible influences from CEVMS. With so many potential
measurement techniques available, care must be taken in selecting appropriate dependent
variables for any proposed program of research.
Only the key dependent variables are listed in the combined list of 28 key measures given above.
They were selected by the same process used to select the key independent variables in the list of
key factors. As indicated before, the criterion for selection was importance in conducting
research on CEVMS effects. Thus, the list of key measures indicates critical measures which
need to be considered in future research. Eye glance behavior can serve as a particularly
important potential indicator of specific visual distractions. The concept of self-regulated
attention is very important for establishing excessive levels of distraction, despite difficulties in
establishing a criterion threshold. This concept refers to attention that is under the driver’s
conscious control, as opposed to involuntary attention, which may compel the driver to glance
away from the road for an excessive amount of time. Increases in driving conflicts and errors are
likewise effective measures of safety. The next level of importance relates to other observations
of vehicle behaviors, including determinations of acceleration, lane position, and speed.
Similarly important infrastructure interactions, such as driver responses to roadway geometry
and traffic control devices, need to be considered.
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