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

Abstract

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.

Mitigating the Climate Impact from Aviation: Achievements and Results of the DLR WeCare Project

“…As a starting point passenger demand networks are directly initialized from exogenous socio-economic scenarios [54,55]. As inputs the forecast published by Randers (2012) [56] and the five scenarios of the International Futures Global Modeling System (IFs) [57] are adapted.…”

From passenger growth to aircraft movements

“…Here, the presented FoAM model can also be integrated in a global flexible framework as presented in Ghosh et al (2015). The input for the model is the forecasted passenger demand from an external passenger demand model described in Terekhov et al (2015aTerekhov et al ( , 2015b. FoAM does not generate new routes itself but the new routes shall be integrated in the demand model such that passenger demand is given on these new routes.…”

Forecasting a Global Air Passenger Demand Network Using Weighted Similarity-Based Algorithms

“…The modular environment AIRCAST 1,2 aims to forecast future development of the air transportation system (ATS) based on socio-economic scenarios. AIRCAST allows to simulate a range of possible outcomes for the future ATS and assess, for example, the impact of new technology on the number of demand passengers or the size and number of aircraft on particular routes.…”

“…AIRCAST allows to simulate a range of possible outcomes for the future ATS and assess, for example, the impact of new technology on the number of demand passengers or the size and number of aircraft on particular routes. An air passenger demand (APD) forecast model of 'origin-destination air travel passenger demand between city-pairs' on a global level called D-CAST 1 is the first layer in a chain of models within AIRCAST 2 . In D-CAST, the APD model forecasts the number of passengers as well as changes in the number of connected cities within the forecast period.…”