As connected, cooperative, and automated mobility (CCAM) and unmanned aerial vehicles (UAVs) rapidly gain traction, the transportation sector faces significant disruptions. These innovations hold immense potential for urban mobility, offering sustainable, efficient, and scalable options. Airports, being crucial nodes in global travel, are uniquely positioned to benefit from these new modes of transport. However, integrating CCAMs and UAVs into airport access systems poses challenges in predicting passenger behaviour, understanding mode choice, and assessing demand. Addressing these challenges is critical to ensuring that airports remain accessible, efficient, and adaptable to evolving traveller expectations.

MAIA-Engine is a toolset designed to tackle the complexities of integrating CCAMs and UAVs into airport access services. Focusing on a passenger-centric approach, MAIA-Engine employs advanced data analytics, monitoring systems, and predictive modelling techniques to understand how these emerging mobility solutions can alter airport access patterns. By analysing passenger mode choices and by predicting demand, this toolset enables airports to plan for the future, ensuring a seamless and efficient traveller experience.

At its core, MAIA-Engine focuses on generating robust predictions for how CCAM and UAV fleets will influence airport access. It provides the tools needed to estimate demand and anticipate modal shifts as travellers adopt these new transportation modes. MAIA-Engine offers actionable insights for decision-makers to improve airport infrastructure and optimise services in response to emerging mobility trends.

BENEFITS
Anticipate infrastructure upgrades based on future demands for CCAMs and UAMs
Optimised passenger experience
Environmental sustainability of airport access journeys