An approach for identifying and locating pavement sections subject to high dynamic wheel loads

Abstract

A study was conducted to assess the effectiveness of the International Roughness Index (IRI) and Heavy Articulated Truck Index (HATI) to identify pavement sections subject to high dynamic wheel loads (DWL). HATI is a profile-based roughness index used by some Australian road agencies to identify road sections providing poor ride quality for heavy trucks. The longitudinal surface profile data of ten pavement sections were used to simulate DWL caused by a typical fully laden articulated truck and to calculate relevant IRI and HATI values. The results of this limited study showed that HATI could be a good indicator of road sections subject to high DWL. For the sections tested herein, it was found to have strong correlation with the Dynamic Aggregate Force Coefficient (DAFC), a measure of road damage due to DWL. The study also included using wavelet analysis to identify and locate the sources of DWL excitation for sections with different HATI values. Wavelet signals of longitudinal profile data in relevant roughness subbands proved to be effective in identifying and locating profile characteristics responsible for exciting truck body motions that induce high DWL. The approach proposed herein would help road agencies to adopt maintenance programs to eliminate or minimise the additional damage and ensure sustainability of their assets' and mobility of road users.