Prediction of Heavy-Vehicle Weight Distributions

Abstract

A new methodology for predicting heavy-vehicle weight distributions and pavement loadings in terms of the governing weight limits and the intensity of enforcement is presented. Gross vehicle weight (GVW) predictive models are developed for defined reference truck types in two identifiable weight-distribution families under steady-state conditions. These models determine the probability of trucks operating at or less than a given GVW expressed as a percent of the prevailing weight limit and as a function of the intensity of enforcement of the governing regulations. A concept of truck substitution ratios is introduced to translate the predicted GVW distributions of the reference trucks into those of other truck types. The predicted GVW distributions are then converted into pavement loading on the basis of the weight split factors of the various axle units on the configuration. The methodology has strong predictive capabilities, with the models being stable both in time and space.