Quantifying long-term rates of texture change on road networks

Abstract

ABSTRACT Texture is required on pavements to provide safe and comfortable ride performance for users. This paper provides the first meaningful analysis of a long-term study of texture data obtained using TRACS (TRAffic Speed Condition Survey) at a site in the UK. TRACS data were collected annually, over a 2 km stretch of motorway from 1995 to 2019. A new data analysis approach utilising time series data with spectral analysis and spatial filtering procedures is presented. The results reveal that the approach enables legacy TRACS laser profile Sensor Measured Texture Depth (SMTD) data to be used to determine long term rates of change in road surface macrotexture. Thus, the technique has unlocked the potential for SMTD data collected annually for 7000 km of the Strategic Road Network in the UK, to inform road maintenance programmes by extrapolation. Additionally, results expose a systematic periodicity occurring each year within the SMTD data studied, corresponding to longitudinal oscillations with wavelengths between 33 and 62 m. The time-invariant periodicity of these oscillations suggests that it is ‘imprinted’ in the early life of the pavement. ‘Imprinting’ may theoretically arise with cyclic tyre loading applied by the suspension systems of heavy vehicles or during road construction.