The last decade has witnessed increased attention toward products, services, and works with reduced environmental impacts. In the field of road construction, the use of alternative materials, wastes, or by-products obtained from industries is attracting considerable interest. The Life Cycle Assessment (LCA) is a powerful project-level tool that allows the assessment of the environmental impacts of a road infrastructure, from raw materials production to end of life phase. In this study, the environmental impacts (in terms of global warming potential-GWP) of an embankment construction project are investigated by a cradle-to-gate approach. The analysis focuses on all the processes involved in the construction of an embankment section, from the base to the preparation of the pavement formation level. The results are provided for two different road types and two different stabilization methods, including the use of lignin and lime. All processes that contribute towards global warming are investigated and described in detail. The most important finding of the LCA, in terms of GWP, is that the production of materials is the phase that contributes the significant share of the total environmental impact (more than 90%) for all scenarios. The lowest production-related emissions can be recorded for the scenarios involving lignin treatment for the stabilization of the embankment body. Furthermore, the percentage increase in GWP ranges between 51% and 39% for transportation activities and 10–11% for construction activities, comparing the scenarios including lime stabilization with the scenarios involving lignin treatment.

The era of intensive construction of new roads in Croatia is behind us. Today road agencies are focused on maintaining and preserving existing roads. Selection of an appropriate maintenance strategy is a complex task, which includes...

Challenges that emerge in roundabout design are mostly related to space constrictions and provision of appropriate deflection around the central island. This can result in speed profiles on roundabouts that might reduce their potential as a noise abatement measure. Because of this, the impact of a roundabout on noise levels and its applicability as a traffic calming device and a noise abatement measure should be investigated in the early design stage, by modeling noise levels. In this paper, the following hypothesis is tested: vehicle movement trajectories, defined during the fastest path performance check in roundabout early design phase, can be used as the road traffic noise sources when modeling noise at roundabouts using static noise model. This procedure (1) simplifies the preparation of the noise model, (2) results in a model that is closer to the real-world in terms of traffic flow conditions, (3) allows the noise calculations in the early stages of roundabout design, and (4) includes the influence of roundabout deflection on calculated noise levels. The abovementioned simplifications of the road traffic noise modeling process should encourage the optimization of roundabout geometry in terms of its noise reduction capabilities in the preliminary design phase of these intersections.

Information on pavement layer thickness is very important for determining bearing capacity, estimating remaining life and strengthening planning. Ground-penetrating radar (GPR) is a nondestructive testing (NDT) method used for determining the continuous pavement layer thickness in the travel direction. The data obtained with GPR in one survey line is suitable for the needs of repair and rehabilitation planning of roads and highways, but not for wider traffic areas such as airfield pavements. Spatial representation of pavement thickness is more useful for airfield pavements but requires a 3D model. In the absence of 3D GPR, a 3D model of pavement thickness can be created by additional processing of GPR data obtained from multiple survey lines. Five 3D models of asphalt pavements were created to determine how different numbers of survey lines affect their accuracy. The distance between survey lines ranges from 1 to 5 m. The accuracy of the 3D models is determined by comparing the asphalt layer thickness on the model with the values measured on 22 cores. The results, as expected, show that the highest accuracy is achieved for the 3D model created with a distance of 1 m between survey lines, with an average relative error of up to 1.5%. The lowest accuracy was obtained for the 3D model created with a distance of 4 m between the survey lines, with an average relative error of 7.4%.

Urban transport networks face pressure from urbanization, climate change, and the growing share of connected and automated vehicles, yet intelligent transport systems (ITS) and pavement engineering have evolved largely in parallel. Traffic control is rarely informed by the structural state of the pavement it loads, and pavement management rarely uses real-time traffic data. This structured narrative review synthesizes 85 sources, most published between 2020 and 2026, identified through publisher-platform searches and citation tracking, and checked against a documented Scopus and Web of Science search. Studies are compared across three interacting layers, namely, the smart city information layer (ITS services, V2X communication, cooperative ITS, and traffic management centers), the geometric layer (intersections, multimodal hubs, and lane management), and the physical layer (sustainable materials, climate-resilient pavements, and data-driven pavement management), using explicit rules for coding agreement, contradiction, and strength of evidence. Within each layer, methods converge, but the benefits are demonstrated mainly in simulation, and their magnitude, validation, and transferability remain contested. Across layers, the main gap lies at the digital–physical interface. The authors propose a pavement-aware ITS architecture in which traffic and pavement states share one decision layer, specify its inputs and control objective, outline a validation scenario and its side effects, and derive six priority research directions.