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indicators used in the optimal timing methodology should oxidation, or reduced rutting. For a specific condition indi-
have the following characteristics: cator, the benefit is determined by the difference in computed
areas associated with the post-treatment condition indicator
· Be measurable (able to be tracked over time), curve and the do-nothing curve. For condition indicators that
· Indicate pavement performance (especially functional decrease over time (e.g., serviceability, friction, or a typical
performance for preventive maintenance), and composite index) the area under the curve becomes relevant
· Change value following the application of a preventive to benefit computations, while for condition indicators that
maintenance treatment. increase over time (e.g., roughness, cracking, rutting, fault-
ing, and spalling) the area above the curve becomes relevant.
Condition monitoring data are needed for all condition indi- Figure 1 illustrates the benefit resulting from the application
cators that are used in the analysis; the methodology permits of a preventive maintenance treatment. As shown in the fig-
the analysis of multiple condition indicators. ure, a defined lower benefit cutoff value limits the areas.
The benefit (difference in areas) is generally positive, as a
preventive maintenance treatment should improve condition
Do-Nothing Relationships or extend the time until the pavement needs rehabilitation;
however, negative benefits may result (e.g., the decrease in
The benefit associated with the application of a preven- friction that follows the application of a fog seal).
tive maintenance treatment at any given time is based on the As different condition indicators are expressed in different
improvement in condition compared with that for the "do- units, the methodology normalizes all individual condition
nothing" alternative. The do-nothing alternative defines the indicator benefit values by dividing the benefit area by the
performance over time (in terms of the condition indicator) original do-nothing area. The result is that all individual ben-
that would be expected if only minor routine maintenance efit values are similarly expressed in units of percent. For
were conducted. In a plot of pavement condition versus example, if the do-nothing and benefit areas in Figure 1 are
time, the baseline performance relationship is referred to as calculated to be 30 and 12, respectively, the individual ben-
a do-nothing curve. If benefit is defined in terms of multiple efit value associated with the condition indicator would be
distress types, a do-nothing performance curve is required 12/30 = 0.4, or 40 percent.
for each relevant condition indicator. The best source for
this information is existing pavement management systems,
although the necessary relationships can also be approxi- Benefit Weighting Factors
mated without the assistance of a pavement management
database. When more than one condition indicator is included in the
analysis, a method is needed to combine the individual ben-
efit values associated with the different indicators. This is
Post-Treatment Relationships done by using benefit weighting factors and a normalization
process.
Determining optimal timing also requires an understanding
of how performance is changed once the preventive mainte-
nance treatment has been applied. A separate performance Computation of Overall Benefit
relationship (condition versus age) is needed for each unique
combination of condition indicator and treatment application Benefit weighting factors are used to differentially weight
age; it is generally assumed that this relationship changes the computed individual benefits associated with each included
depending on when the treatment is applied. For example, if
performance is measured by 3 indicators for a treatment
applied at 5 ages, 15 (3 × 5) different performance relation-
ships must be defined. Benefit Area
Condition Indicator
Benefit Associated with Lower Benefit
Individual Condition Indicators Cutoff value
Benefit is the quantitative influence on condition indicators Do-Nothing Area
resulting from the application of a preventive maintenance
treatment. Using this definition, different types of benefit may
Age, years
be associated with an application of a given preventive main-
tenance treatment. For example, applying a chip seal could Figure 1. Conceptual illustration of the do-nothing
result in benefits in the form of improved friction, retarded and benefit areas.
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condition indicator. Each condition indicator is assigned an ment, an investigation can be conducted to provide feedback
integer weighting factor between 0 and 100, where all the on multiple condition indicators used in the analysis. Some
entered weighting factors must total 100 for a given analy- general steps that can be followed to gather feedback for use
sis. Each chosen weighting factor is then converted to an in the factor selection process are described in this section.
associated weighting percentage by dividing each individ-
ual weighting factor by 100 (i.e., the total of all assigned Initial Selection of Benefit Weighting Factors. Engineering
benefit weighting factors). The individual contributions to the judgment is a good starting point in the process of selecting
overall benefit are then determined by multiplying the bene- relative weights associated with each performance measure.
fit weighting factor percentages by the individual benefit val- The initially selected weights represent attempts to quantify
ues. This approach is explained with the following example. the relative purpose or benefit of applying the treatment. For
Assume that a particular preventive maintenance treatment example, if the use of a slurry seal is proposed to reduce or
timing results in individual benefit values of 27 percent for eliminate a historical problem with raveling and low friction
rutting, 12 percent for cracking, and 47 percent for friction. characteristics, and if the agency feels that the problems with
That is, the preventive maintenance treatment application raveling and low friction are of equal importance, then initial
increases performance by 27, 12, and 47 percent over the do- benefit weighting factors of 50 would be appropriate for
nothing benefit area performances for rutting, cracking, and both. However, if the preventive pavement program is pri-
friction, respectively. Next, assume that the agency chooses marily being driven by a desire to improve friction charac-
benefit weighting factors of 60, 30, and 10 for rutting, crack- teristics, this difference in purpose may be reflected by assign-
ing, and friction, respectively (note that these factors add up ing a much larger factor to friction (e.g., 80 for friction and
to 100). Overall benefit contributions are then determined by 20 for raveling).
multiplying the benefit weighting factor percentages by the
individual benefit values (e.g., for rutting 27 percent × 60 = Analyze Each Condition Indicator Separately. The initial
16.2 percent). The total overall benefit contribution is then selection of benefit weighting can be improved by investi-
the total of those values calculated for each individual con- gating the sensitivity of the results. This can be accomplished
dition indicator. In this example, the total overall benefit con- by analyzing the effects of one condition indicator at a time
tribution is 24.5 percent (see Table 16). The total benefit val- (set the associated benefit weighting factor for one of the
ues computed for different timing scenarios are then used in condition indicators to 100 and all other benefit weighting
combination with costs to compare the effectiveness of the factors to 0). The effects on treatment timing can then be
different timing scenarios. interpreted to identify the condition indicators that are rela-
tively more important than others.
To demonstrate the importance of the benefit weighting
Selecting Benefit Weighting Factor Values process, assume an individual analysis of three different con-
dition indicators (rutting, cracking, and friction). When the
Selecting benefit weighting factors that correctly represent optimal timing results are relatively similar (e.g., 3, 4, and
the relative importance of different condition indicators is a 4 years of age, respectively), the weighting process is less
difficult task. Because each condition indicator is expressed important than if the optimal treatment times are substan-
in different units, an incremental change in the magnitude of tially different. The weighting process will be completed by
one indicator does not necessarily provide the same effect as considering a weighted average of the benefits associated
an incremental change of equal magnitude in another condi- with each condition indicator (the overall optimal timing will
tion indicator. For example, a 10 percent increase in the area still be in a range from 3 to 4 years). However, if the individ-
(benefit) associated with roughness is not likely to have the ual analysis results show a wider range of optimal timings
same impact on performance as a 10 percent increase in the (e.g., 4, 2, and 7 years, respectively), the effect of assigned
friction area. Although the selection of benefit weighting fac- weighting factors on the final optimal timing cannot be easily
tors is a subjective process that requires engineering judg- assessed. In such cases, investigations similar to that described
TABLE 16 Example computation of overall benefit
Assigned
Individual Benefit Overall Benefit
Condition Benefit Values, Weighting Benefit Weighting Contribution,
Indicator % Factor Factor Percentage %
Rutting 27 60 60/100 = 0.6 16.2
Cracking 12 30 30/100 = 0.3 3.6
Friction 47 10 10/100 = 0.1 4.7
TOTAL -- 100 1.0 24.5
