Noise maps and action plans represent the main tools in the fight against citizens’ exposure to noise, especially that produced by road traffic. The present and the future in smart traffic control is represented by Intelligent Transportation Systems (ITS), which however have not yet been sufficiently studied as possible noise-mitigation tools. However, ITS dedicated to traffic control rely on models and input data that are like those required for road traffic noise mapping. The present work developed an instrumentation based on low-cost cameras and a vehicle recognition and counting methodology using modern machine learning techniques, compliant with the requirements of the CNOSSOS-EU noise assessment model. The instrumentation and methodology could be integrated with existing ITS for traffic control in order to design an integrated method, which could also provide updated data over time for noise maps and action plans. The test was carried out as a follow up of the L.I.S.T. Port project, where an ITS was installed for road traffic management in the Italian port city of Piombino. The acoustic efficacy of the installation is evaluated by looking at the difference in the acoustic impact on the population before and after the ITS installation by means of the distribution of noise exposure, the evaluation of G_den and G_night, and the calculation of the number of highly annoyed and sleep-disturbed citizens. Finally, it is shown how the ITS system represents a valid solution to be integrated with targeted and more specific sound mitigation, such as the laying of low-emission asphalts.

The knowledge of the acoustic impedance of a material allows for the calculation of its acoustic absorption. Impedance can also be linked to structural and physical proprieties of materials. However, while the impedance of pavement samples in laboratory conditions can usually be measured with high accuracy using devices such as the impedance tube, complete in-situ evaluation results are less accurate than the laboratory results and is so time consuming that a full scale implementation of in-situ evaluations is practically impossible. Such a system could provide information on the homogeneity and the correct laying of an installation, which is proven to be directly linked to its acoustic emission properties. The present work studies the development of a measurement instrument which can be fastened through holding elements to a moving laboratory (i.e., a vehicle). This device overcomes the issues that afflict traditional in-situ measurements, such as the impossibility to perform a continuous spatial characterization of a given pavement in order to yield a direct evaluation of the surface’s quality. The instrumentation has been uncoupled from the vehicle’s frame with a system including a Proportional Integral Derivative (PID) controller, studied to maintain the system at a fixed distance from the ground and to reduce damping. The stabilization of this device and the measurement system itself are evaluated and compared to the traditional one.

In almost all urban contexts and in many extra-urban conurbations, where road traffic is the main noise pollution source, the use of barriers is not allowed. In these cases, low-noise road surfaces are the most used mitigation action together with traffic flow reduction. Selecting the optimal surface is only the first problem that the public administration has to face. In the second place, it has to consider the issue of assessing the efficacy of the mitigation action. The purpose of the LEOPOLDO project was to improve the knowledge in the design and the characterization of low-noise road surfaces, producing guidelines helpful to the public administrations. Several experimental road surfaces were tested. Moreover, several measurement methods were implemented aiming to select those that are suitable for a correct assessment of the pavement performances laid as mitigation planning. In this paper, the experience gained in the LEOPOLDO project will be described, focusing on both the measurement methods adopted to assess the performance of a low-noise road surface and the criteria by which the experimental results have to be evaluated, presenting a comparison of the obtained results and their monitoring along time.

The different sources of noise in a vehicle have long been known, and they include noise from the engine and other mechanical parts, aerodynamic noise, and rolling noise. More specifically, the latter concerns the interaction between the tire and the road surface, and so it is also known as Tire–Road Noise (TRN). One of the parameters influencing TRN is pavement stiffness. The empirical measurement of pavement stiffness, and in particular, its frequency spectrum (dynamic stiffness), is not easy to determine, and only in the last decade have studies emerged about this subject. In these works, two different instrumental chains are employed as follows: the impact hammer one and the dynamic exciter (shaker) one, which has established itself over time as a reference. The objective of this work is to develop a system for the dynamic stiffness measurements of road pavements using the impact hammer capable of producing a similar performance to the shaker while minimizing costs. During the work, a measurement aid device named Test Automation Device (TAD) was designed and implemented to increase the quality of the measurements. In line with the practical execution of the measurement, the analysis and the representation of the results were optimized to obtain results that adhere to the stiffness model proposed in the literature. In the present paper, the TAD, the measurement optimization work, the data analysis performed, and the proposed representation method will be described. Finally, we will present the results obtained and possible future perspectives.

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