A Rational mechanistically-based approach for allocating highway costs

Abstract

Paper presented at the 26th Annual Southern African Transport Conference 9 - 12 July 2007 "The challenges of implementing policy?", CSIR International Convention Centre, Pretoria, South Africa. ABSTRACT:The allocation of highway costs is constantly debated among legislatures, highway agencies, and highway users as it directly relates to concerns about equity in terms of cost responsibility and actual user charges. One of the major challenges in highway cost allocation stems from the need to estimate pavement damage by different vehicle classes. Normally, the calculation of damage caused by heavy vehicles to the highway infrastructure utilizes the concept of Equivalent Single Axle Load (ESAL) or E80. This concept was empirically established after the AASHO Road Test almost half a century ago. Although the E80 concept is widely used in pavement design, it has a number of shortcomings when applied for the estimation of pavement damage by different vehicle classes. Some of these limitations include: failure to account for specific infrastructure and environmental conditions, disregard of the differences in traffic configurations and composition, and the inability to capture different distress types. This leads to a fairly inaccurate and generic estimation of pavement damage by vehicle class. This paper proposes an innovative and more rational highway cost allocation approach based on the recently completed guide for the “Mechanistic-Empirical Design Guide of New and Rehabilitated Pavement Structures” developed under the National Cooperative Highway Research Program (NCHRP) Project 1-37A. The Guide accounts for all factors that contribute to pavement deterioration, thereby addressing the shortcomings of an ESAL-based analysis listed earlier. Estimates for pavement damage attributable to each vehicle class can thus be accurately simulated. For the purposes of this study, traffic data collected at a weigh-in-motion station in Texas were used to estimate the highway cost shares of different vehicle classes, given varying pavement structural capacity.