Modelling pavement surface characteristics for noise prediction through Bailey-related indicators

Abstract

The aggregate gradation of bituminous mixtures (hot mix asphalts, HMA) is one of the major factors affecting their surface texture. In turn, this latter is a crucial factor and influences drivers and bystanders’ safety, comfort, and health. Despite this, the design of texture levels still lacks sound bases and dedicated algorithms and this negatively affects the acoustic design of bituminous mixtures. Consequently, the objectives of this study were confined into the derivation of relationships to be used in mix design to predict texture levels. Experimental data were analyzed, in the pursuit of setting up appropriate models and algorithms. Analyses involved the consideration of Bailey-related indicators. Algorithms were then calibrated and tested, in order to allow the validation of the algorithms set up. Results demonstrate that the texture level is well correlated to the asphalt mixture composition. Researchers can benefit from the results obtained for improving understanding of noise-related and rolling resistance-related implications. Furthermore, the same results can be useful for practitioners facing the need to design mixtures complying with ISO or project-specific requirements.