Comprehensive Truck Size and Weight Limits Study: Linkage between the Revised Desk Scans and Project Plans Report
Chapter 5: Pavement Comparative Analysis
5.1 Purpose
This section highlights linkages between the Desk Scan and the Project Plan developed for Pavement Comparative Analysis. The focus is on how the desk scan informed the general technical approach outlined in the project plans and the specific data and analytical techniques available to produce information needed to meet overall 2014 CTSW Study objectives.
5.2 Pavement Analysis Linkages
The 2014 CTSW Study pavement team's review of previous studies and techniques for analyzing pavement costs associated with changes in traffic loads reveals approaches that fit into three broad categories: (1) using traditional "equivalent single axle loads" (ESALs) derived from the half-century-old AASHO Road Test as a measure of pavement damage, and therefore pavement damage costs, (2) applying pavement deterioration models to a representative group of pavement sections with a large number of traffic loading conditions to derive a new set of load equivalence factors (LEFs) and deterioration curves that vary by distress type, or (3) directly applying current pavement design models to a small number of sample pavement sections under scenario traffic loadings to derive estimates of changes in pavement life and therefore pavement cost changes. Each of these three alternative approaches has been applied to varying degrees to previous studies identified and discussed in the pavement desk scan report.
The first approach, using ESALs as a measure of pavement damage, is ruled out because it relies on ESALs-- widely discredited because (a) calculating ESALs for tridems has no empirical or theoretical validity since it requires extrapolating a dummy variable, and (b) ESALs apply primarily to pavement smoothness which has many components that vary in their sensitivity to magnitude of axle load.
The second approach, deriving and applying pavement damage relationships from pavement performance models, is ruled out because it (a) relies upon LEFs derived from an earlier version of AASHTOWare Pavement ME Design® that need to be verified using the latest version, and (b) requires an inventory of distress observations that is currently incomplete.
The third approach, directly applying current pavement design models to a small number of pavement sections, was selected to be the best option based on the information gathered during the desk scan.
The AASHTOWare Pavement ME Design® model was used in this analysis and run for each of these sections to determine a base case of the expected pavement performance under traffic conditions appropriate for each thickness (mix of vehicle types and operating weights as well as truck traffic levels). Locations were selected that avoid climate extremes and thus represent typical weather effects for several groups of states. To the extent possible, Long Term Pavement Performance Program (LTPP) sections was used as a basis for each sample section and will adjust base case parameters as required to make sure that each sample section represents the pavement performance history that would typically be expected.
For each sample section, the first step will be to perform a base traffic performance analysis. Next, traffic inputs will be varied in ways that represent traffic shifts that occur as a result of the various truck scenarios. This will require a series of runs of AASHTOWare Pavement ME Design® during which all factors except traffic are held constant.
The multiple runs for each sample section enabled an evaluation of changes in pavement service life as a result of changes in truck travel associated with each modal shift scenario. These changes in pavement service life were translated into pavement cost changes associated with size and weight scenarios using rudimentary life cycle cost analysis.
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