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Among the available techniques for pavement maintenance/rehabilitation, recycling of pavements is becoming more acceptable. It is based on sustainable development, by reusing materials reclaimed from the pavements and reducing the disposal of asphalt materials.Based on the results of an earlier study of asphalt mixtures containing 30 to 50% recycled asphalt, using the Marshall mix design methodology, additional mixtures of identical composition, containing 50% recycled asphalt, were produced at a range of bitumen contents and were all tested in more detail for permanent deformation and fatigue behaviour.The results from both investigations were analysed, with the objective of verifying if the Marshall mix design method was suitable to design bituminous mixtures with 50% reclaimed material. However, it is important to mention that this study is still not finished and that, it will evolve towards the validation of the manufacturing processes and the mechanical properties of the mixture using tests related with the field performance.A conventional mixture of identical gradation and material composition, made of 100% virgin aggregates, was also studied to compare with the recycled mixtures' behaviour.

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks.

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Liquid waste containing lignin, a biopolymer of vegetable origin, is generated from the production of wood hardboards. Because polymers improve the performance of asphalt mixtures, this work studies the possibility of using this industrial waste as a bitumen extender in the production of asphalt mixtures. Thus, asphalt mixtures with 0% (control), 5%, 10%, 20%, and 40% of industrial waste were produced. The bitumen-aggregate adhesion, moisture damage resistance, resilient modulus, permanent deformation resistance, and thermal susceptibility of such mixtures were analysed. Asphalt mixtures with 20% of industrial waste have shown the best moisture damage resistance. As the percentage of industrial waste increased, the thermal susceptibility of the mixture also increased. Therefore, it can be stated that it is appropriate to use this industrial waste containing lignin as a bitumen extender. It can be used in asphalt mixtures for road pavement, mainly by substituting 20% of the bitumen by this liquid waste. It reduces the consumption of bitumen and improves the performance of asphalt mixtures, contributing to the purpose of sustainable construction. The industrial waste was not subjected to any transformation process, thus facilitating its use. The reduction in the use of bitumen in asphalt mixtures by adding this industrial waste contributes to the goals of sustainable development and cleaner production of asphalt mixtures.

Three road profile signal-processing methods that give parameters or indices used for the detection of road unevenness in Europe are compared: international roughness index (IRI) analysis, power spectral density analysis, and constant percent bandwidth spectrum analysis. This comparison is carried out with road rideability prediction models, car vibration prediction models, and careful diagnosis and definition of rehabilitation work. The IRI meets the profiling needs with regard to the assessment of road condition, the road serviceability level, and the setting of priorities for planning for road maintenance and repair. This index is not suitable for specification of rehabilitation work or for diagnosis of possible problems with road sections. Power spectral density (PSD) analysis by the International Organization for Standardization’s Standard 8608 is a suitable method with regard to the evaluation of evenness level only if, on the basis of the averaging length, the road profile can be considered a stationary stochastic process and if a single regression line can be fitted. PSD is valuable for the detection of periodic defects in the road profile. Constant percent bandwidth spectrum analysis of consecutive segments along the section under investigation is well adapted to both the road serviceability evaluation and the diagnosis of possible problems with road sections.