Monitoring and managing the skid resistance of the highway network is necessary for controlling and reducing the number of road accidents. High-speed measurements of surface texture can be used as a surrogate parameter for controlling a pavement's surface friction on the highway network. The two components of surface texture that affect skid resistance are the macrotexture and the microtexture. However, the technologies commonly used for measuring pavement texture at highway speeds account only for the macrotexture. This study explored ways to characterize the microtexture of pavement surfaces with the main objective of quantifying the effect of accounting for both components of the texture on the prediction of skid resistance, as measured by a British pendulum tester. Various methods for characterizing the microtexture were compared to determine which one better predicted surface friction. The study used field measurements of surface texture and friction performed on various in-service flexible pavements. The surface microtexture was characterized by a series of texture parameters calculated in both the spectral and the spatial domains. The impact of incorporating the microtexture on the prediction of the British pendulum number was evaluated through analysis of a series of models specified by each of the proposed parameters. The results of the analysis showed a drastic improvement in predicting the British pendulum value when the authors accounted for both components of the surface texture, as opposed to only the macrotexture. In a comparison of the analyzed methods for characterizing the microtexture, the use of spectral parameters led to the best prediction of the pavement surface friction. A series of recommendations is provided for the calculation of microtexture parameters.

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Collecting accurate rutting data is important in order to assess network-level pavement conditions and to determine maintenance and rehabilitation needs and funding levels in order to optimize the use of available economic resources. The technical objective of this study was the assessment of the rut-depth (RD) accuracy and precision of different continuous automated systems (CAS), which represent the state-of-the-art for the automated data collection of rutting, and discrete automated systems (DAS), which are still used by several Department of Transportations (DOTs) in the United States. The RD values analyzed in this study were obtained by 1) field measurements at highway speeds using five different optical CAS, and 2) calculation simulating the use of DAS with different configurations. The analysis of the first type of values assessed the closeness of the RD produced by the different CAS to the RD manually measured for this study. The analysis of the second type of values assessed the effects of the number of sensors and the width of measurement on the DAS's accuracy and precision. In addition, the impact of the RD accuracy and precision on the assessed pavement condition at network-level was analyzed for both the CAS that participated in the experiment and the simulated DAS.

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