III - Joining the dots to enhance regional transport
Our AI-enabled solution will help extend new transport opportunities to more isolated populations, improving quality of life and benefiting local economies.
Lucía Menéndez-Pidal, PRIAM technical coordinator
Current innovative air mobilityInnovative air mobility(IAM) refers to the broader concept of integrating new types of air vehicles and operations into the airspace system. This includes both passenger and cargo transport using drones, eVTOLs and other emerging technologies, across a range of environments – urban, suburban, rural and interregional. IAM encompasses urban air mobility, but also extends to services such as emergency response, infrastructure inspection, logistics and regional air mobility. (IAM) opportunities – such as large drones known as ‘electric vertical take-off and landing vehiclesElectric vertical take-off and landing vehicles(eVTOLs) are aircraft that can take off, hover and land vertically using electric propulsion. They are designed for urban and regional air mobility, offering quiet, efficient and flexible transport solutions without the need for traditional runways.’ (eVTOLs) – promise more efficient, sustainable and accessible air transportation. “eVTOLs can overcome geographical barriers, better connecting regional populations when rail or roads are not viable,” says Lucía Menéndez-Pidal, aviation engineer at project host Nommon(opens in new window) and technical coordinator of PRIAM(opens in new window). Yet questions remain about wider coordination with other transport modes, alongside meeting passenger demand and expectations. Consequently, the project PRIAM, funded by SESAR JU(opens in new window), is helping to build a more ambitious, passenger-centric, transport system linking European rural and urban hubs, powered by a suite of artificial intelligence (AI) tools. PRIAM built a virtual representation of Europe’s current regional transport network (known as a digital twindigital twinis a virtual model of a physical system, such as an airport, used to simulate and monitor operations in real time. It supports decision-making by providing predictive insights and enabling more efficient planning and coordination.), augmented by data analytics and AI modelling. This enables the team to conduct scenario simulations before real-world deployment. The team’s analysis of mobile network data using machine learning offers a deeper understanding of passenger mobility patterns (journeys, transportation modes, frequency and so on). Combined with survey data, PRIAM can estimate likely IAM adoption levels. Optimisation techniques will suggest the best locations for vertiports, alongside how best to integrate IAM services within current multimodal transport networks.
Towards a passenger-centric transport system
Two case studies will validate PRIAM’s tools and algorithms. One will be performed in the La Gomera-Tenerife region of Spain’s Canary Islands, a mountainous region reliant on ferry transport, while the other will be run in the Catalan Pyrenees, another sparsely populated mountainous region that is a hotspot for tourism. “Our AI-enabled solution will help extend new transport opportunities to more isolated populations, improving quality of life and benefiting local economies,” adds Menéndez-Pidal. Alongside an impact assessment framework, building upon work carried out by sister SESAR projects such as TRANSIT(opens in new window), MultiModX(opens in new window) and MUSE(opens in new window), PRIAM will develop a digital toolset to support IAM implementation, complemented by deployment recommendations.
