Flexible Airport Passenger Flow Estimation

Accurately determining Airport passenger Flow (APF) is critical to efficiently manage airport processes and allocate resources and is fundamental to the provision of a seamless passenger journey experience.

Currently, the estimation for APF have several limitations. One major limitation is the lack of explainable ability for the APF estimation model. An explainable network will allow the design of a transparency network that helps to clearly identify reasons behind the bottlenecks in airport operations and resources that relate to passenger flow, by providing a traceable inference process that enables effective decision-making to optimise operations.

The PhD will demonstrate explainable time-series data modelling with the particular focus on flexible airport passenger flow prediction. The research outcomes will have significant opportunity to accelerate the development of smart airport.