Atlantia (Italy)

Accurate and reliable vehicle positioning is a prerequisite for the development of cooperative intelligent transportation systems (C-ITSs), especially for automated driving applications and in scenarios where global navigation satellite systems (GNSSs) fail to meet the requirements of safety-critical services. This article presents an experimental assessment of a roadside infrastructure-based localization system that exploits a wideband wireless technology to estimate a vehicle’s position and communicates this information in real time to the vehicle via a vehicle-to-everything (V2X) link. We highlight the need to use advanced tracking methods to cope with heterogeneous vehicle dynamics. We validate the proposed system experimentally in both racetrack and highway tunnel scenarios using an ultra wideband (UWB) positioning network, showcasing the system’s feasibility through on-field implementations. The findings reveal that the wideband radio technology obtains positioning accuracy comparable to GNSS real-time kinematic with a mismatch lower than 30 cm in 95% of the cases. This capability provides a seamless high-accuracy positioning service and successfully unlocks autonomous navigation in tunnels. This article underscores the key role of the roadside infrastructure in enhancing autonomous vehicle navigation by integrating a precise positioning technology as UWB with V2X communication, thereby meeting the stringent requirements of safety-critical C-ITS applications.

Nowadays, when battery-powered electric vehicles (EVs) travel along motorways, their drivers decide where to recharge their cars’ batteries with no or scarce information on the occupancy status of the next charging stations. While this may still be acceptable in most countries, due to the limited number of EVs on motorways, long queues may build-up in the coming years with increased electric mobility, unless smart allocation strategies are designed and implemented. For instance, as we shall investigate in this manuscript, a centralised coordination of the charging strategies of individual EVs has the potential to significantly reduce the queuing time at charging stations. In particular, in this paper we explain how the charging problem on motorways can be modelled as an optimisation problem, we propose some strategies based on dynamic optimisation to solve it, and we explain how this may be implemented in practice using a centralised charge manager that exchanges information with the EVs and solves the optimisation problems. Finally, we compare in a realistic scenario the current decentralised recharging strategies with a centralised one, and we show that, under simplifying assumptions, queueing times can be reduced by more than 50%. Such a significant reduction allows one to greatly improve vehicular flows and general journey durations without requiring building new infrastructure. Reducing queuing times has a positive impact on traffic congestion and emissions, and the more geographically balanced energy demand of the proposed methodology mitigates energy consumption peaks.

Aortic dissection is an uncommon finding in both dogs and cats. The precise pathophysiological mechanisms responsible for the development of aortic dissection remain unclear. In humans, aortic dissection is usually secondary to another systemic disease, such as systemic arterial hypertension, an abnormality of connective tissues or a parietal trauma. This is a case of an aortic dissection in a hypertensive hyperthyroid cat, presenting with haemorrhagic pericardial effusion. The dissection affected both thoracic and abdominal aorta, with histopathological confirmation. This case is an example of the utility of both thoracic and abdominal ultrasound for the diagnosis of aortic dissection in cats and it highlights the importance of rigorous clinical examination. Aortic dissection should be considered in the differential diagnosis of pericardial effusion in cats. Further investigations are fundamental to understand how dissections develop and extend to achieve good clinical results.
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As new models of electric vehicles are put on the market, with larger batteries and higher charging rates, there are growing concerns about how the charging infrastructure should be upgraded and modernized to cope with the challenges they pose. Governmental directives and rules dictate minimal requirements for the future charging infrastructure, but would these be enough to handle massive numbers of electric vehicles? In this manuscript we describe an electric mobility simulator that can be used to mimic highway vehicular flows and evaluate the queues at charging stations under different penetration levels of electric vehicles. Based on actual vehicular flows from the most important Italian motorway, we find that non-homogeneous queues at charging stations can be predicted, and the infrastructure planned by the EU rules may not be able to accommodate a penetration level of more than 3% of electric vehicles in the highway without giving rise to unacceptably high waiting times at charging stations. Also, we note that smart assignments of electric vehicles at charging stations may significantly improve waiting times, opening the discussion on the need for allocation policies and guidelines. Extensive Monte Carlo simulations on an accurate reconstruction of the Italian case study support the discussion and our findings.

Abstract Many Italian bridges were built more than 50 years ago and are subjected to significant phenomena of deterioration that in some cases, especially in presence of hidden structural defects due to design or construction errors, have triggered catastrophic collapses. The current situation would require in‐depth analyses to be carried out on all infrastructures to assess the current level of safety, according to in‐force national standard, and to define appropriate construction or operational interventions. However, taking account of the large number of infrastructures, the necessity to define the priorities for detailed assessments arises and, this is why the recent Italian ‘Guidelines for risk classification and management, safety assessment and structural health monitoring of existing bridges’ includes, for the first time in Italy, a stepwise approach with increasing level of detail. In this article the main difficulties and limitations arisen in recent assessments of existing bridges according to these guidelines are discussed. The aim is to highlight either if they can be solved e.g. by improving the guidelines and/or the current codes of practice, or if they should be taken into account when setting the acceptable level of risk and the relevant assessment and rehabilitation requirements.

In the framework of ongoing design activities focused on the rehabilitation works of almost 600 highway tunnels of Autostrade per l'Italia's network, a smart analysis method which mixes historical calculation techniques with innovative standards has been developed. The key point of the method is the reliability of measurements regarding the actual stress level acting in existing linings, since it directly involves tunnels stability during the construction stages as well as tunnels' strength and resilience in the long term. The experimental measurement of the stress level in the tunnel linings typically leads to a set of uncertainties and issues: the need to define standardized survey procedures which can be carried out under objective conditions, significance level/surrounding conditions/validity of measurements and, finally, how to use measurements for design purposes. Following the statistical analysis related to a large database consisting of over 1,500 results of standard flat-jack tests, an experimental stage ranging from the depth of lining cutting and to the collection of strain measurements in the surrounding lining intrados by means of highly dynamic and sensitive sensors has been developed. This experimental stage has provided the main elements to assess the reliability of flat-jack test results and, in particular, to assess whether its actual representativeness is limited to the stress level acting on the lining intrados side or -and, in case, how -it can be extended to the whole lining thickness.

The objective of ASPI Network's Tunnel Renewal Strategy is the extension of tunnel linings' life cycle (i.e., additional 50 years) through the construction of new, structurally autonomous shell structures, replacing the original linings and ensuring suitable performance under seismic events. Since there is the need to limit the impact on highway traffic, program implementation requires innovative technical and technological solutions, that is the optimization of structural interventions, the automation and speeding up of operations, the maximization of work productivity and flexibility in terms of sites and logistics in order to allow rapid job site start-up and dismantling, by only closing at night time. For the design of pilot interventions aimed at testing alternative technical solutions, following tunnels -built in the late 1950s and early 1970s -were identified: Castello 1 left (Highway A10 Genoa -Ventimiglia), San Fermo right (Highway A09 Milan -Como) and Colle Marino left (Highway A14 Bologna -Taranto). In all the cases, preservation of original intrados profile was planned (crown radius and platform width). In Castello 1 left and San Fermo right tunnels, the new shells remain within the original lining intrados profile, after partial milling or hydrodemolition (required in presence of temporary nailing or concrete containing asbestos fibers), while in Colle Marino left the new crown is inscribed in the existing one thanks to platform lowering 65cm, which was made possible by the absence of altimetric constraints at tunnel portals. New shells consist of Steel Liner Plates in Castello 1 left, a high-performing shotcrete arch integrated with three-dimensional steel mesh panels (Ram-Arch system) in San Fermo right, and prefabricated arch slabs with rear concrete casting (on new cast in place invert) in Colle Marino left.

This paper outlines a logical process based on Bayesian inference to exploit monitoring observations to improve the accuracy in the reliability estimates of civil structures that are retrofitted during their service lives. The proposed approach is particularly effective for complex structures, whose response prediction is affected by structural parameters with significant uncertainty; typical examples are prestressed concrete bridges, heavily influenced by the inherent uncertainties of the material’s creep and shrinkage. The methodology is applied to a real-life complex bridge in Italy, as opposed to academic problems and laboratory tests; the structural model developed for this study includes the original creep law of the Model B3 proposed by Bazant rather than linear approximation or response surfaces. The Bayesian inference is performed using a Markov Chain Monte Carlo (MCMC) method, while the reliability assessment utilises importance sampling (IS) for computational efficiency. The results show the extent to which structural health monitoring (SHM) and Bayesian inference reduce the uncertainty in structural parameters and the prediction of the structural demand. At the same time, they increase structural reliability. Particular attention is given to computational effort, structural modelling and algorithm optimisation.