"Artificial intelligence at the service of cities: a digital twin to manage traffic and parking."

Urban mobility management is one of the most complex challenges of contemporary cities: traffic, parking shortages, pollution and inefficient transportation affect citizens' quality of life on a daily basis. A research group led by Francesco Piccialli, professor of Computer Science at the Department of Mathematics and Applications "R. Caccioppoli" of the University of Naples Federico II, tries to answer these problems, published in the prestigious international journal Nature Communications.

The study presents an urban digital twin, a model based on artificial intelligence and real-time data capable of simulating, predicting and optimizing the functioning of city mobility. Through the integration of data from parking meters, environmental sensors, infraction logs and weather conditions, the system can anticipate parking demand, analyze the impact of events or road closures and propose alternative scenarios to improve traffic organization.

The trial demonstrated how the coordinated use of machine learning and generative intelligence techniques can support municipal governments in making strategic decisions, reducing inefficiencies and environmental impacts. Indeed, the digital twin makes it possible to virtually test new mobility policies-such as changes to the road system or the construction of multi-story car parks-before their actual implementation.

The research marks an important step toward cities capable of predictive and sustainable planning, where artificial intelligence becomes a concrete tool to improve the quality of urban life and guide more informed public decisions. At the same time, it reinforces Federico II's commitment to applied research in intelligent systems and big data, confirming its role as a reference in the digital transformation of the territory.

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