For decades, cities grew in chaotic fashion — or from the 19th century onwards, through rigid and linear plans. Today, however, thanks to the convergence of sensors, data and algorithms, urban environments are shifting towards adaptive models that evolve in real time, based on the continuous collection and analysis of information. In this article, we explore the potential of AI in urban planning and look at real-world examples showing the direction cities are taking.
AI applications in urban planning
The AMIGOS project
Launched in June 2023, the AMIGOS (Active Mobility Innovations for Green and Safe City Solutions) project received €9.1 million in funding from the Horizon Europe programme. Led by Hamburg, the initiative involves 14 cities and 14 partner organisations from 16 countries.
Its goal is to promote active, inclusive and safe mobility solutions through five urban “Living Labs” (Hamburg, Gabrovo, Lappeenranta, Istanbul and Las Rozas) and ten additional “Safety Improvement Areas”, including cities such as Reykjavik, Bologna and Ankara.
Among its core tools is a cloud-based Big Data platform that gathers, stores and analyses large volumes of urban data—on vehicles, pedestrians, air quality, noise, and more—to build predictive models and digital twins that inform urban planning.
The project’s methodology focuses on co-creation with local stakeholders—especially vulnerable users—to optimise public spaces, promote active transport, enhance road safety and cut emissions, all while assessing environmental and social impacts, as well as the potential for replication.
The ELABORATOR project
Another Horizon Europe initiative, ELABORATOR (European Living Lab on designing sustainable urban mobility towards climate neutral cities) has a budget of nearly €12.4 million and brings together a consortium of 38 partners, including cities, academic institutions and technology providers.
This holistic approach includes interventions such as smart control tools, dynamic redistribution of public space, shared mobility services, and active transport options — all co-designed with vulnerable users and local authorities.
These measures will be implemented in six Lighthouse Cities (Milan, Copenhagen, Helsinki, Issy-les-Moulineaux, Zaragoza and Trikala) and six Follower Cities (Lund, Liberec, Velenje, Split, Krusevac and Ioannina), following a model of replication and knowledge transfer.
In Helsinki, for example, the project is rolling out solutions to improve safety at pedestrian crossings (especially where bikes and e-scooters are involved), optimise parking for micromobility, and deliver real-time alerts using the city’s digital twin.
Other city-level initiatives
Beyond these large-scale projects, many cities are developing their own AI-based initiatives to improve traffic flow, protect the environment, or support the design of more socially inclusive spaces. Here are just a few examples we have come across:
- Aveiro Tech City Living Lab (Portugal): The city of Aveiro has deployed a network of 44 urban nodes — such as smart lampposts and sensor boxes on buildings — equipped with radar, LiDAR, video surveillance, environmental sensors, and multi-protocol communications (5G, ITS-G5, LoRaWAN, etc.), with edge processing capabilities. The platform enables real-time analysis of traffic, pedestrian safety, emergencies and experimental services for industry and universities.
- SmartSantander (Spain): Santander is home to a large-scale urban IoT lab where technologies are tested in real-world settings across transport, environment and connectivity applications.
- Bologna Civic Digital Twin (Italy): Bologna is working on a “civic digital twin” that simulates social and spatial dynamics in real time to foster inclusive and participatory urban planning.
As these examples show, AI is becoming a key tool in reimagining our cities in smarter, more participatory ways. The benefits — better mobility, more human-centred spaces, optimised services — are already tangible. But like any technology, urban AI brings its own challenges: from safeguarding privacy and building public trust to ensuring no one is left behind in the digital transformation.
In the end, the goal is not simply more technology — it is applying it in ways that truly respond to people’s needs.
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