The possibility of using some warnings inside modern vehicles should be an aid to driving activity. However, the information transferred to users is not always received in the expected way due to the variability and complexity of the road environment. This study, therefore, aims to identify a procedure that allows to ascertain whether drivers receive the data in an appropriate way even during particular maneuvers, such as passing cyclists on a winding road or, on the contrary, if they represent an unnecessary overload. To answer this question, an experimentation in a simulated environment was set up for recording the drivers’ visual behavior in both the presence and absence of a driving aid device (On-Board Unit, OBU). The results show that, in some situations, the information provided by the OBU helps to maintain a more virtuous driving behavior but, in the most complex ones, drivers acquire information from a smaller number of sources, excluding the aid devices inside the cockpit. This procedure is useful for Advanced Driver Assistance Systems (ADAS) designers to refine these instruments, but also for road managers who can improve safety by inserting appropriate signs or speed limits.

The presence of numerous sensors inside modern vehicles leads to the development of new driving assistance tools, the real usefulness of which depends, however, on the environmental context. This study proposes a procedure capable of quantifying the effectiveness of some warnings produced by an On-Board Unit (OBU) inside the vehicle in a specific environmental context, even if limited only to the considered road. The experimentation was carried out by means of a driving simulator with a sample of young users with sufficiently homogeneous characteristics. The collected data were treated by ANOVA to highlight any differentiation between a traditional driving condition, without any instrumental support, and another involving the OBU was present. The results showed that only in relation to the investigated road, the OBU ensured the advantage of sending information of interest to the driver without invalidating their performance in terms of longitudinal and transverse acceleration, speeding, and steering angle. This research could be of interest to the infrastructure managers who, in case of inappropriate use of a road, could intensify active and passive safety devices for users’ safety.

The design of road geometry is based on a rather elementary assumption that the user strictly follows the lane axis. Based on this hypothesis, the ideal trend of some factors related to the driver’s performance, such as steering angle and speed, can be derived to optimize the most appropriate design choices. In practice, driving behavior differs from the assumed one and produces trends in these variables, which are very different from the ideal functions. The purpose of this research is therefore to propose synthetic performance indicators useful for highlighting the real characteristics of users’ driving behavior during road travel. Toward this aim, some driving experiments along four different curves in a simulated environment were studied in order to evidence possible criticisms. The proposed indicators showed a remarkable ability to represent and synthesize even very complex performance function trends. The proposed performance indicators can have multiple uses, such as, for example, in statistical analyses—which are generally carried out at a later stage—or constitute sufficient information to guide the decisions of infrastructure managers. In the long term, in a “smart road” perspective, they can be used by road administrators for information exchange among users (with each other and with the infrastructure) to improve road operation and safety.

Ripple formation and evolution as well as vortex separation along the bedform profile strongly influence surface waves and sediment transport. These features were investigated in a U-Tube at the Hydraulics Laboratory of the University of Messina. During the experimental campaign, tests in the presence of wave only, current only, and collinear wave plus current in wave dominated regime were carried out. The experiments involved both live bed and fixed bed conditions. It was observed that, when the current superimposes to the wave, a longer time is required for the bedforms to stabilize; the vortex separating at the ripple crest reduces with respect to the wave only case. Accordingly, in the fixed rippled bed case, velocity measured in current only condition is larger than that in the wave plus current flow. As vortex shedding influences the way sediments are transported close to the bed, the obtained results may improve the present knowledge on wave current interaction in the presence of bedforms with repercussions in turn on sediment dynamics.

Road maintenance management aims to satisfy quality, comfort, and safety requirements for the various assets. To overcome delays and barriers in the widespread adoption of road management systems, the Building Information Modeling (BIM) approach may offer significant advantages as a convenient alternative for road maintenance management. Although existing BIM platforms are not fully equipped for this purpose, defining original modules and scripts can extend their capabilities, allowing for the handling of road condition information and maintenance management. In this context, this paper presents an operative framework designed to leverage BIM benefits for road maintenance management, particularly in terms of virtual inspection, asset condition assessment, and maintenance design. To achieve this, specific original and customized smart objects and routines were coded in I-BIM platforms, tailored to different scales, aims, and detail levels. These smart objects incorporate user-defined extended attributes related to pavement condition and maintenance planning (such as roughness, rutting, structural capacity). In particular, the authors have developed original virtual smart objects in different platforms, serving as “containers” for the survey information. These objects are adapted to display quality levels of the pavement segments in a realistic and user-friendly environment. Additionally, original routines were coded to automatically import survey data from external datasets and associate this information with the appropriate objects. This customized and extended approach, not available in commercial platforms, can effectively support maintenance operators.