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Comprehensive Truck Size and Weight Limits Study: Pavement Comparative Analysis Technical Report

Chapter 1: Pavement Comparative Analysis

1.1 Background

MAP-21 directs the Secretary of Transportation, in consultation with State and other Federal agencies, to conduct a series of analyses assessing the impacts from trucks operating at or within current Federal size and weight regulations as compared to the impacts from trucks operating above those limits with a particular focus on impacts to:

  • Highway safety and truck crash rates;
  • Infrastructure (pavement) service life;
  • Highway bridge performance; and
  • Delivery of effective enforcement programs.

The United States Department of Transportation (USDOT), in conjunction with a group of independent stakeholders, identified six different vehicle configuration scenarios, each involving one of the alternative truck configurations, to assess the likely results of allowing widespread alternative truck configurations to operate on different highway networks.

The results of this 2014 Comprehensive Truck Size and Weight Limits Study (2014 CTSW Study) study are presented in a series of technical reports. These include:

  • Volume I: Comprehensive Truck Size and Weight Limits Study – Technical Summary Report. This document gives an overview of the legislation and the study project itself, provides background on the scenarios selected, explains the scope and general methodology used to obtain the results, and gives a summary of the findings.
  • Volume II: Comprehensive Truck Size and Weight Limits Study. This volume comprises a set of five comparative assessment documents that meet the technical requirements of the legislation:
    • Modal Shift Comparative Analysis
    • Pavement Comparative Analysis,
    • Highway Safety and Truck Crash Comparative Analysis,
    • Compliance Comparative Analysis, and
    • Bridge Structure Comparative Analysis

This Volume II: Pavement Comparative Analysis presents the analysis of the six alternative truck size and weight configurations (scenarios) selected for study and describes in detail the approach, data, models, limitations, and assumptions underlying estimates of potential pavement impacts associated with the six scenarios.

1.2 Introduction

The pavement comparative analysis for the 2014 CTSW Study consisted of a step-wise approach to determining the effects of the various truck traffic configuration scenarios on performance and life-cycle costs. The process started with the selection of representative pavement sections (flexible and rigid along with their local materials and design inputs) within each of the four primary geographic locations in the United States. The AASHTOWare Pavement ME Design® software (or MEPDG) was used to evaluate each of these sections to determine a base case of the expected pavement life prior to any needed rehabilitation under representative base case traffic conditions (e.g., representative of the mix of vehicle types and operating weights that might be expected based on compilation and analysis of large quantities of WIM data). An initial analysis of climatic variability within the vicinity of each geographic location was performed to ensure that the sites selected were representative of typical weather effects and inclusive of typical subgrade soils in that area. The data from Long-Term Pavement Performance (LTPP) sections were used as a starting point for each sample section.

The analysis then considered the four pavement types (new flexible pavement, flexible overlay of existing flexible pavement, new jointed plain concrete pavement (JPCP), and composite (flexible overlay of existing JPCP pavement)) that represent the overwhelming majority of pavements used on the Interstate and National Highway System (NHS) in the United States. The basic premise was that the analysis should isolate the impacts of traffic shifts while holding other parameters constant. In order to achieve this goal, the baseline pavement sections were based on the following criteria: 1) use actual current traffic characteristics; 2) use sections with modern designs and materials as were constructed over the past two or three decades (as close to actual site sections as possible); and 3) use the subgrade properties on site. The flexible and rigid pavement surface layer thicknesses were selected from the ranges reported in the 2012 HPMS database for Interstates and other NHS arterial roadways in each of the four geographic locations.

One limitation of the current version of Pavement ME Design® software is that it cannot suitably evaluate the impact of traffic loadings on the predicted service life of either asphalt overlays of existing flexible pavements or asphalt overlays of existing JPCP pavements because the current reflection cracking models are totally empirical, cannot predict level of severity, and are not related to traffic loadings similar to other distresses in the Pavement ME Design® software. For this reason, this study does not attempt to evaluate the impact of the scenarios on the performance of overlaid pavements.

After compiling the input data required for each of the sections, the USDOT study team analyzed base case traffic volumes for each geographic location and pavement type. Another set of analyses were then run for each of the six modal shift scenarios in order to estimate the change in initial service interval.

The multiple runs for each sample section enabled the study team to evaluate changes in the initial pavement service interval (defined as one or more condition measures at a level that would trigger rehabilitation) as a result of changes in truck travel associated with each of the six scenarios.

A life cycle cost analysis was then performed for the base case and each scenario on each sample section.

The computation of expected cost impacts included only the present value of a typical highway agency pavement rehabilitation strategy that represents the agency costs over a 50-year analysis period. These costs included HMA overlays for the rehabilitation of flexible pavement and diamond grinding and HMA overlays of rigid pavement. User costs related to pavement roughness, work zones and lane closures, and traffic delays were not considered in this effort out of concern that the large number of assumptions required to include them would confound that analysis. These costs, however, can be expected to have a significant impact on the traveling public and freight users of the Nation’s transportation system.

1.3 Key Assumptions

The models used in the study for the pavement analysis considered an array of factors in the prediction of pavement service lives, but did not consider all possible factors. One key assumption is that a substantial amount of confidence can be placed in the relative initial service intervals predicted for each traffic scenario, while all other factors are held constant. It is important to recognize that impacts related to both materials- and post-construction durability are assumed to impact the initial service intervals of pavements under each size and weight scenario equally.

Since pavement overlays were not modeled, it was implicitly assumed that modeling new pavements adequately covers the effects of changing vehicle usage patterns on rehabilitated pavements. At the same time, however, the cost analysis assumes that relative levels of use have no effect on the performance of rehabilitated pavements. The inconsistency in these two assumptions results from the current inability of the pavement models to analyze the performance of pavement overlays.

Similarly, it was assumed that temporal travel distributions, tire pressures, vehicle widths, or power-unit wheelbases (vehicle-related inputs to Pavement ME Design® software) will not change under any of the scenarios. While vehicle speeds may change incrementally on some highway segments, it was assumed that the changes are not significant enough to impact rutting or any other pavement distresses. It was further assumed that damage (such as scuffing) caused by increases in lateral pavement friction from tridems and other multiple-axle sets will not significantly impact pavement costs.

As in all other parts of this study, the pavement analysis assumed that the limited available data on vehicle characteristics and travel patterns, and the predicted changes in those characteristics and travel patterns as estimated in the Volume II: Modal Shift Comparative Analysis, adequately describe the before-and-after conditions associated with each size and weight scenario.

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