Methodological Framework for Truck-Factor Estimation Considering Vehicle–Pavement Interaction

Abstract

Truck traffic is usually characterized by using truck factors (TFs). A TF converts a mixed truck traffic stream over the pavement design lifetime into a number of equivalent single-axle loads (ESALs). This conversion requires equivalent single-axle load factors (EALFs), which can either be empirical or theoretical. The mechanistic-empirical pavement design guide (MEPDG) considers axle load spectra and uses it to run the response model, considering implicitly theoretical EALFs. This paper presents a methodology for TF estimation based on theoretical EALFs calculated by using simulated axle loads, thus overcoming the unavailability of data to define axle load spectra. Once the EALFs are calculated for several simulations, TFs are established and regression models are defined to predict TFs. To reach this point, the study considered the two most common Portuguese truck configurations and pavement structures. The methodology development and application revealed its flexibility and upgradability. The results indicated that vehicle–pavement interaction increases TFs by up to 27% when the initial international roughness index (IRI) increases