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 mobility (IAM) opportunities – such as large drones known as ‘electric vertical take-off and landing vehicles’ (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 twin), 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.
