The evolution of macrotexture on asphalt pavements using non-contact field techniques

Edmondson, Victoria (2021) The evolution of macrotexture on asphalt pavements using non-contact field techniques. Doctoral thesis, Northumbria University.

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Abstract

Adequate skid resistance is required to ensure vehicle safety on pavements in wet conditions and depends upon road surface characteristics, particularly texture. Texture is composed of a range of different scales each of which contributes differently to the generation of adequate friction at the tyre-road interface. Macrotexture acts to disperse water, under wet conditions, through the gaps in between road aggregates, and influences the way skid resistance reduces with increasing speed in wet conditions. Increasingly, correlations between macrotexture measurements captured using non-contact techniques and tyre-pavement contact friction are being investigated. There is a notable scarcity of research into the respective accuracy of the non-contact measurement techniques at these scales. This thesis compares three non-contact techniques: a laser profile scanner, Structure from Motion photogrammetry (SfM) and Terrestrial Laser Scanning (TLS). Spectral analysis, areal surface texture parameters and 2D cross-correlation analysis are used to evaluate the suitability of each approach for characterising and monitoring pavement macrotexture. The results show that SfM can produce successful measures of the areal root mean square height (Sq), which represents pavement texture depth and is positively correlated with skid resistance. Significant noise in the TLS data prevented agreement with the laser profiler but new filtering procedures result in improved values for the peak density (Spd) and the arithmetic peak mean curvature (Spc), which together define the shape and distribution of pavement aggregates forming macrotexture. However, filtering the TLS data results in a trade-off with vertical accuracy, thus altering the reliability of Sq. The work undertaken reveals that the functional areal parameters Spd and Spc are sensitive to sample size. This means that pavement specimen size of 150 mm x 150 mm or smaller, when used in laboratory or field observations, are inadequate to capture the true value of areal surface texture parameters. Therefore, the deployment of wider scale approaches such as SfM are required in order to successfully capture the functional areal parameters (Spc and Spd) for road surfaces.

This thesis also provides the first meaningful analysis of a long-term study of legacy texture data obtained using TRACS (TRAffic Speed Condition Survey). A new data analysis approach utilising time series data with spectral analysis and spatial filtering procedures is presented, to determine long term rates of change in road surface macrotexture and compared with meteorological and traffic datasets. The results reveal for hot rolled asphalt (HRA) surfaces that changes to Sensor Measured Texture Depth (SMTD) follow a linearly increasing trend with time. The ‘rate of change’ is influenced by the order of magnitude of annual average daily traffic (AADT), when factored for the percentage of heavy goods vehicles. This linear trend is disrupted by environmental parameters such as rainfall events and seasonal conditioning. In the summer this signal is evident as a transient peak in the ‘rate of change’ of texture greater than 0.04 mm, and in the winter as a reduction. The transient changes in texture corresponded to above average rainfall occurring in the week prior to SMTD measurement. The signal observed demonstrates an inverse pattern to the classically understood seasonal variation of skid resistance in the UK, where values are low in the summer and high in the winter. The findings demonstrate for the first time that texture measurements experience a seasonal signal, and provide compelling evidence pointing toward surface processes (such as polishing and the wetting and drying of surface contaminants) causing changes to texture that are affecting seasonal variation in skid resistance. Furthermore, results expose a systematic periodicity occurring each year within the SMTD data studied, corresponding to longitudinal oscillations with wavelengths between 33 m to 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.

Finally, this thesis contributes to understanding of the role of the different scales of texture on the development of skid resistance. A signal processing technique termed Empirical Mode Decomposition was used to decompose the texture measurements into a set of component profiles of different wavelengths. The Dynamic Friction Model, a computational friction model already validated on real road surfaces, was then used to determine the relative effect of partially recomposed profiles with their components on skid resistance. The results demonstrate the importance of not only “small-scale” and “large-scale” textures but also their spatial arrangement and shape. Indeed, on wet road surfaces, “small-scale-texture” was found to be key to achieving good skid resistance at low speeds, whilst “large-scale-texture” was found to be crucial to maintaining it with increasing speed. The distribution of the summits of the large-scale-textures was established as being able to compensate for a lack of small-scale-texture. Conversely, the reverse was established as also being true, with the small sharp local summits of small-scale-texture being found to compensate for a lack of large-scale-texture.

The work undertaken in this PhD scrutinises the measurement of pavement macrotexture using non-contact techniques and defines new approaches to analyse legacy data sets to visualise spatially macrotexture evolution. Significantly, the work provides compelling evidence of a ‘seasonal signal’ in texture data, linked to environmental conditions, particularly precipitation. These results place a new emphasis on the future need to quantify the contribution of pavement surface processes to the phenomenon of seasonal variation of skid resistance, to improve texture evolution assessment and frictional measurement on road networks.

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