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Current environmental awareness interests several aspects of civil engineering, including road construction. Indeed, new challenges related to environmental pollution and landscape preservation must be faced. In this sense, clear road pavement surfaces represent an effective technology aimed at guaranteeing environmental-friendly aesthetic pavements. The use of clear synthetic resin as a binder involves several benefits for the mitigation of in-service reached temperatures and the heat distribution within pavements (with appreciable effects on pavement mechanical performance too). The present paper illustrates an experimental study aimed at analysing the chromatic and mechanical properties of a clear synthetic resin and thus its suitability as a binder for road pavement mixes. Chromatic characteristics were assessed through digital image analysis at different aging conditions. A dynamic shear rheometer was used to evaluate the linear viscoelastic properties as well as fatigue and rutting potential of the binder in a wide range of temperatures and frequencies. A conventional 35/50 penetration grade bitumen was also investigated for comparison purposes. The clear resin exhibited limited changes in colour (darkening effects), mainly in the case of short-term aging. On the other hand, a low temperature-dependency of such a binder was observed up to 58°C. Slightly increased aptitude to rutting at the higher temperatures was detected, even if it is worth noting that clear in-service mixtures would achieve lower temperatures than traditional “black” materials at a given environmental condition (air temperature, solar radiation, etc.). The resin also exhibited a softer behaviour, along with an enhanced fatigue resistance. Overall, the studied innovative binder showed promising results in view of its effective use in road paving.

The current paper deals with the numerical prediction of the mechanical response of asphalt concretes for road pavements, using artificial neural networks (ANNs). The asphalt concrete mixes considered in this study have been prepared with a diabase aggregate skeleton and two different types of bitumen, namely, a conventional bituminous binder and a polymer-modified one. The asphalt concretes were produced both in a road materials laboratory and in an asphalt concrete production plant. The mechanical behaviour of the mixes was investigated in terms of Marshall stability, flow, quotient, and moreover by the stiffness modulus. The artificial neural networks used for the numerical analysis of the experimental data, of the feedforward type, were characterized by one hidden layer and 10 artificial neurons. The results have been extremely satisfactory, with coefficients of correlation in the testing phase within the range 0.98798–0.91024, depending on the considered model, thus demonstrating the feasibility to apply ANN modelization to predict the mechanical and performance response of the asphalt concretes investigated. Furthermore, a closed-form equation has been provided for each of the four ANN models developed, assuming as input parameters the production process, the bitumen type and content, the filler/bitumen ratio, and the volumetric properties of the mixes. Such equations allow any other researcher to predict the mechanical parameter of interest, within the framework of the present study.

The paper introduces and analyses the results of an experimental trial on the fatigue resistance of recycled hot mix asphalt for road pavements. Based on the gyratory compaction and the indirect tensile strength test, the mix design procedure has optimized nine different mixes, considering both conventional limestone and Reclaimed Asphalt Pavement (RAP), the latter used at different quantities, up to 40% by weight of the aggregate. A standard bitumen and two polymer modified binders were used for the production of the mixes. The fatigue study was carried out with four-point bending tests, each one performed at 20°C and 10 Hz. The empirical stiffness reduction method, along with the energy ratio approach, based on the dissipated energy concept, was adopted to elaborate the experimental data. Unaged and aged specimens were checked, to analyse the ageing effects on the fatigue performance. In comparison with the control mixes, produced only with limestone, improved fatigue performance was noticed for the mixtures prepared with RAP, especially when made with polymer modified binders, under both aged and unaged conditions. Both the approaches adopted for the experimental data analysis have outlined the same ranking of the mixes.

Driving is the result of a psychological process that translates data, signals and direct/indirect messages into behavior, which is continuously adapted to the exchange of varying stimuli between man, environment and vehicle. These stimuli are at times not perceived and at others perceived but not understood by the driver, even if they derive from tools (vertical signs, horizontal marking) specifically conceived for his safety. The result is unsafe behavior of vehicle drivers. For this reason, the road environment needs to be radically redesigned. The paper describes a research, based on real and virtual environment surveys, aimed to better understand drivers' action-reaction mechanisms inside different scenarios, in order to gain informations useful for a correct organization (design) of the road space. The driving simulator can help in developing, from road to laboratory, the study of new road design tools (geometrical, compositional, constructive ones, street furniture, etc.), because it can be used to evaluate solutions before their usefulness is proved on the road.