Pavement Performance Measures and Forecasting and The Effects of Maintenance and Rehabilitation Strategy on Treatment Effectiveness (Revised)

CHAPTER 8. STATE DATA ANALYSES

BACKGROUND

Results of the analyses of the LTPP time-series pavement condition and distress data measured along flexible and rigid pavement test sections were presented and discussed in previous chapters. The results are presented based on treatment type, climatic regions, and various other factors. This chapter addresses the similarities and differences between the LTPP data and the pavement condition and distress data measured by Colorado, Louisiana, and Washington along various pavement segments of their respective pavement networks. The following differences between the LTPP and the State data were observed:

• The LTPP data were measured along a 500-ft (152.4-m)-long test and control sections located throughout the United States and Canada, whereas the State data were measured along 0.5-mi (0.8-km)-long to 8-mi (13-km)-long pavement projects and stored in the databases for each 0.1-mi (0.16-km)-long pavement segment along the project. Thus, the data for an 8-mi (13-km)-long pavement project were stored in 80different fields, 1 field per 0.1 mi (0.16 km).
  
  
• The units of measurement used by the LTPP Program were not the same as those used by the State transportation departments. For example, the LTPP unit of measurement for IRI was m/km, while it was inches/mi for the States. Therefore, before the analyses of the State data, the data were converted to the same units as the LTPP data.
  
  
• The pavement condition and distress along one single LTPP test section represented one single data point in time, whereas for each pavement project, the State data contained as many data points at one time as the number of 0.1-mi (0.16-km)-long pavement segments along the project. For example, the data from one survey of an 8-mi (13‑km)-long pavement project was equivalent to 80 LTPP test sections.
  
  
• The State transportation departments’ databases were based on their distress identification definitions and procedures, which may or may not have been compatible with the Distress Identification Manual for the Long-Term Pavement Performance Program.⁽⁸⁰⁾
  
  
• The State transportation department’s databases lacked details of the types, classifications, and properties of the pavement layers and roadbed soils.

The LTPP data contained the pavement conditions and distresses of flexible, rigid and composite pavements test and control sections. Although the data from CDOT, LADOTD, and WSDOT contained the same data, the number of rigid and composite pavement projects that received treatments for which the database contained three or more data points was very limited. Hence, it was decided to limit the comparison to flexible pavement sections only.

The research team developed a step-by-step procedure to mine, handle, organize, and analyze the data based on one of the objectives of this study. This objective was to compare the results of the analyses of the LTPP and State data and to determine whether the methodologies used in the analyses of the LTPP data applied equally to the State data. Therefore, the pavement condition and distress data for the pavement networks of CDOT, LADOTD, and WSDOT were requested, received, organized, and subjected to the same types of analyses as the LTPP data using the step-by-step procedure detailed in the next section.

ANALYSIS STEPS

This section presents the steps of the procedure used in the analyses of the State. These steps are similar to those used in the analyses of the LTPP data. The difference is that the LTPP test sections were analyzed individually. On the other hand, a State pavement project consisted of many 0.1-mi (0.16-km)-long pavement segments where the pavement condition and distress varied substantially along the project. Although each 0.1-mi (0.16-km)-long pavement segment along a given pavement project was analyzed individually, results of the analyses of each project in a State transportation department that received the same treatment were grouped into the five-CS system based on the RFPs and RSPs of each 0.1-mi (0.16-km) segment. The system was developed in this study and presented in chapter 3 (Pavement Condition Classification) of this report. Finally, the benefits of a given treatment type were calculated as the weighted average benefits of each 0.1-mi (0.16-km)-long pavement segment in each State using RFP or RSP, CFP or CSP, and FCROP or SCROP. For the LTPP data, the benefits were calculated using the same parameters based on the weighted average benefits of each test section that received the same treatment type and located in any of the four climatic regions. The analyses procedure used the following steps:

• Step 1: The pavement condition and distress data were converted into Microsoft® Excel spreadsheet format and separated per pavement type.
  
  
• Step 2: For each pavement network, the treatment data were searched, and each 0.1-mi (0.16-km)-long segment of several pavement projects that received one of the following treatments were identified, copied, and stored in a separate Microsoft® Excel datasheet:
  
  
  • Thin overlay (≤ 2.5 inches (63.6 mm)).
    
    
  • Thick overlay (> 2.5 inches (63.6 mm)).
    
    
  • Thin mill and fill (≤ 2.5 inches (63.6 mm)).
    
    
  • Thick mill and fill (> 2.5 inches (63.6 mm)).
    
    
  • Single chip seal.
  
  
  
• Step 3: The pavement condition and distress data for each identified 0.1-mi (0.16‑km)-long pavement segment were examined to determine whether the segment had a minimum of three time-series data that could be modeled using the proper mathematical function. Those segments that did not pass the test were not included in the analyses. Table 117 summarizes the number of 0.1-mi (0.16-km)-long pavement segments that were accepted for analyses for each treatment type in each State. The table also lists the number of LTPP test sections that received similar treatment type and were analyzed. The results of these LTPP test sections were compared with those of the 0.1-mi (0.16-km)-long) pavement segments.

Table 117. Number of 0.1-mi (0.16-km)-long pavement segments and LTPP test sections for each treatment type available for analyses.

• Step 4: The data for each 0.1-mi (0.16-km)-long pavement segment of each project were analyzed, and RFPs and RSPs before treatment were calculated.
  
  
• Step 5: For each 0.1-mi (0.16-km)-long pavement segment, the treatment benefits were calculated in terms of RFP or RSP after treatment, CFPs or CSPs, and FCROPs or SCROPs. The treatment benefits were then compared with the treatment benefits obtained from the LTPP test sections. One issue that should be noted is that the history of the 0.1-mi (0.16-km)-long pavement segments and the treatment dates were different from one pavement project to another and from one LTPP test section to another. To compare the benefits using an equivalent reference, RFP and RSP were calculated from the treatment time to the time when the pavement reached the prespecified threshold value. Stated differently, the calculated RFP and RSP of each 0.1‑mi (0.16-km)-long pavement segment and of the LTPP test sections represented the time in years from the treatment date to the time when the prespecified threshold value was reached. Further, the same threshold values were used in the analyses of the State and the LTPP data.
  
  
• Step 6: The results of the analyses of the 0.1-mi (0.16-km)-long pavement segments were grouped into six T²Ms, which were submitted to FHWA and are available from the LTPP Customer Support Services.⁽⁷⁹⁾ The T²Ms list the before and after treatment CSs for all 0.1-mi (0.16-km)-long pavement segments that were analyzed. The T²Ms also list the benefits of the treatments in term of RFP/RSP, CFP/CSP, and FCROP/SCROP and their averages.
  
  
• Step 7: Results of the analyses of all LTPP test sections (the numbers are also listed in table 117) that were subjected to one of the previously listed treatments and located in any climatic region were grouped for each pavement condition and distress type. The weighted average benefits in terms of RFP/RSP, CFP/CSP, and FCROP/SCROP were then calculated.
  
  
• Step 8: The two sets of benefits were then compared per pavement condition and distress type, as detailed in the following sections.

IRI

Table 118 summarizes the calculated benefits (in terms of IRI) for all 0.1-mi (0.16-km)-long pavement segments in each State transportation department that received the indicated treatment type and the comparable LTPP test sections. The table also lists the number of 0.1-mi (0.16-km)-long segments and the number of LTPP test sections involved in the analyses. For ease of visual comparison of the benefits, they were plotted in bar graph format as shown in figure 102 through figure 104. Examination of the three figures indicated that the benefits, for IRI in terms of the RFP, CFP, and FCROP of each treatment type of the LTPP SPS and GPS test sections and of the 0.1-mi (0.16-km)-long pavement segments in each of the cited State transportation departments, were very similar. The conclusions and recommendations based on these observations are included in a separate section at the end of this chapter.

Table 118. Comparison of the weighted average treatment benefits based on IRI of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 102. Graph. Comparison of the weighted average RFP based on IRI of five treatment types performed on LTPP test sections and on various pavement projects of CDOT, LADOTD, and WSDOT.

Figure 103. Graph. Comparison of the weighted average CFP based on IRI of five treatment types performed on LTPP test sections and on various pavement projects of CDOT, LADOTD, and WSDOT.

Figure 104. Graph. Comparison of the weighted average FCROP based on IRI of five treatment types performed on LTPP test sections and on various pavement projects of CDOT, LADOTD, and WSDOT.

RUT DEPTH

Table 119 summarizes the calculated benefits (in terms of rut depth) for all 0.1-mi (0.16‑km)-long pavement segments in each cited State transportation department that received the indicated treatment type and the comparable LTPP test sections. The table also lists the number of 0.1-mi (0.16-km)-long segments and the number of LTPP test sections involved in the analyses. For ease of visual comparison of the benefits, they were plotted in bar graph format as shown in figure 105 through figure 107. Examination of the three figures indicated that the benefits, in terms of the RFP/RSP, CFP/CSP, and FCROP/SCROP of each treatment type of the LTPP test sections and of the 0.1-mi (0.16-km)-long pavement segments in each of the cited State transportation departments were very similar. Once again, the conclusions and recommendations based on these observations are included in a separate section at the end of this chapter.

Table 119. Comparison of the weighted average treatment benefits based on rut depth of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 105. Graph. Comparison of the weighted average RFP/RSP based on rut depth of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 106. Graph. Comparison of the weighted average CFP/CSP based on rut depth of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 107. Graph. Comparison of the weighted average FCROP/SCROP based on rut depth of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

ALLIGATOR CRACKING

Table 120 summarizes the average calculated benefits (relative to alligator cracking) for all 0.1‑mi (0.16-km)-long pavement segments in each cited State transportation department that received the indicated treatment type and the comparable LTPP test sections. The table also lists the number of 0.1-mi (0.16-km)-long segments and the number of LTPP test sections involved in the analyses. For ease of visual comparison of the benefits, they were plotted in bar graph format as shown in figure 108 through figure 110. Examination of the three figures indicated that the benefits of each treatment type of the LTPP test sections and of the 0.1-mi (0.16-km)-long pavement segments in each of the cited State transportation departments were very similar. The conclusions and recommendations based on these observations are included in a separate section at the end of this chapter.

Table 120. Comparison of the weighted average treatment benefits based on alligator cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 108. Graph. Comparison of the weighted average RSP based on alligator cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 109. Graph. Comparison of the weighted average CSP based on alligator cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 110. Graph. Comparison of the weighted average SCROP based on alligator cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

LONGITUDINAL CRACKING

Table 121 summarizes the average calculated benefits (in terms of longitudinal cracking) for all 0.1-mi (0.16-km)-long pavement segments in each cited State transportation department that received the indicated treatment. For ease of visual comparison of the benefits, they were plotted in bar graph format as shown in figure 111 through figure 113. Examination of the three figures indicated that the benefits of each treatment type of the LTPP test sections and of the 0.1‑mi (0.16-km)-long pavement segments in each of the cited State transportation departments were very similar. The conclusions and recommendations based on these observations are included in a separate section at the end of this chapter.

Table 121. Comparison of the weighted average treatment benefits based on longitudinal cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 111. Graph. Comparison of the weighted average RSP based on longitudinal cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 112. Graph. Comparison of the weighted average CSP based on longitudinal cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 113. Graph. Comparison of the weighted average SCROP based on longitudinal cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

TRANSVERSE CRACKING

Table 122 summarizes the average calculated benefits (relative to transverse cracking) for all 0.1‑mi (0.16-km)-long pavement segments in each cited State transportation department that received the indicated treatment type and the comparable LTPP test sections. The table also lists the number of 0.1-mi (0.16-km)-long segments and the number of LTPP test sections involved in the analyses. For ease of visual comparison of the benefits, they were plotted in bar graph format as shown in figure 114 through figure 116. Examination of the three figures indicated that the benefits, in terms of RSP, CSP, and SCROP of each treatment type of the LTPP test sections and of the 0.1-mi (0.16-km)-long pavement segments in each of the cited State transportation departments were very similar. The conclusions and recommendations based on these observations are included in a separate section at the end of this chapter.

Table 122. Comparison of the weighted average treatment benefits based on transverse cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 114. Graph. Comparison of the weighted average RSP based on transverse cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 115. Graph. Comparison of the weighted average CSP based on transverse cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

Figure 116. Graph. Comparison of the weighted average SCROP based on transverse cracking of five treatment types performed on LTPP test sections and on pavement projects of CDOT, LADOTD, and WSDOT.

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

Pavement condition and distress databases of three pavement networks were requested and received from three State transportation departments—CDOT, LADOTD, and WSDOT. Each database was searched and pavement projects that received one of the following five treatment types were identified.

• Thin overlay (≤ 2.5 inches (63.5 mm)).
  
  
• Thick overlay (> 2.5 inches (63.5 mm)).
  
  
• Thin mill and fill (≤ 2.5 inches (63.5 mm)).
  
  
• Thick mill and fill (> 2.5 inches (63.5 mm)).
  
  
• Single chip seal.

The pavement condition and distress data for each of the 0.1-mi (0.16-km)-long pavement segments along each selected pavement project that was treated using one of these five treatments was analyzed. Results of the analyses included RFPs and RSPs before and after treatment, CFPs and CSPs after treatment, and FCROPs and SCROPs after treatment. The pavement segments of all pavement projects in one State transportation department that received the same treatment type were grouped based on their RFPs or RSPs into the proper CSs before treatment. Each of the 0.1-mi (1.6-km)-long pavement segments in each CS group before treatment was listed in the after treatment CS based on its after treatment RFP or RSP. For each treatment type, the weighted average treatment benefits, in terms of each pavement condition and distress type, were then calculated. The results were submitted to FHWA and are available from the LTPP Customer Support Services.⁽⁷⁹⁾ These weighted average treatment benefits were then compared with the weighted average treatment benefits of the LTPP test sections. The results are listed in table 118 through table 122 and shown in figure 102 through figure 116. The data in the 15 figures indicated the following:

• The weighted average benefits of each of the five treatment types, in terms of each pavement condition and distress type, obtained from the analyses of the LTPP data were similar to the benefits obtained from the State data. The implication of this is that the treatment benefits described in this report that were found using the LTPP data, could be used as benchmark values for the national practice. State transportation departments could use such data to do the following:
  
  
  • Gauge the effectiveness of their current practices using similar analyses.
    
    
  • Conduct lifecycle cost analyses of various treatment alternatives to optimize the pavement network rehabilitation and treatment strategy.
    
    
• The methodologies described in this report for the analyses of the LTPP pavement condition and distress data applied to the State data.
  
  
• The three-level (poor, fair, and good) and five-level (very poor, poor, fair, good, and very good) pavement rating systems developed in this study, and presented in chapter 4 based on the time-series pavement condition and distress, were equally applicable to the LTPP and State data.
  
  
• The average variability in the measured pavement condition and distress data over time for the LTPP test sections was very similar to the variability of the State-measured data along most pavement projects.
  
  
• The percent of the LTPP test sections that were excluded from the analyses because of an inadequate number of data points or because of improving pavement condition and/or distress over time without the application of treatments was equivalent to the percent of the 0.1-mi (0.16-km)-long segments of a pavement project that was excluded from the analyses for the same reasons.

Based on the results of the analyses, the following is strongly recommended:

• The dual pavement condition rating systems should be submitted for approval and adoption by FHWA, AASHTO, and the State transportation departments.
  
  
• The algorithms developed in this study should be standardized and used on future research studies.
  
  
• The benchmark values regarding the benefits of the five treatment types included in this study should be expanded to include additional pavement treatments.