Robin Ghosh

A concept of forecasting origin-destination air passenger demand between global city pairs using future socio-economic scenarios

This study introduces a concept of a new method of forecasting air passenger flows on a global level using socio-economic scenarios. The method has two steps: forecasting the topology of origin-destination demand network and predicting the number of passengers on existing and new connections. Network theory is applied to simulate demand connections between cities utilizing weighted similarity based algorithms. The number of passengers on a connection is defined using quantitative analogies. Preliminary calculations show promising results. This concept of the global passenger demand prediction will be applied in a modular environment modeling the future air transport system.

Future Passenger Air Traffic Modelling: Trend Analysis of the Passenger Air Travel Demand Network

This paper is about the architecture for modelling future global air traffic on city pair level. Here, the focus lies on the initial trend analysis of global demand data required as a foundation for predicting the global demand network based on socio-economic scenarios. We present a 4-layer philosophy to model the future passenger air transportation system in a generic way on a global scale over time until 2050. The evolutions of demand passengers, demand connections, and airfares are analyzed as global aggregates and as distributions over the great circle distance between city pairs. Further, global trends of key network metrics are displayed.