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19 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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20 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